<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Frenkel-Morgenstern, M.</style></author><author><style face="normal" font="default" size="100%">Lacroix, V.</style></author><author><style face="normal" font="default" size="100%">Ezkurdia, I.</style></author><author><style face="normal" font="default" size="100%">Levin, Y.</style></author><author><style face="normal" font="default" size="100%">Gabashvili, A.</style></author><author><style face="normal" font="default" size="100%">Prilusky, J.</style></author><author><style face="normal" font="default" size="100%">Del Pozo, A.</style></author><author><style face="normal" font="default" size="100%">Tress, M. L.</style></author><author><style face="normal" font="default" size="100%">Johnson, R.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Calloni, G.</style></author><author><style face="normal" font="default" size="100%">Chen, T.</style></author><author><style face="normal" font="default" size="100%">Schermann, S.M.</style></author><author><style face="normal" font="default" size="100%">Chang, H.</style></author><author><style face="normal" font="default" size="100%">Genevaux, P.</style></author><author><style face="normal" font="default" size="100%">Agostini, F.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, G. G.</style></author><author><style face="normal" font="default" size="100%">Hayer-Hartl, M.</style></author><author><style face="normal" font="default" size="100%">Hartl, F.U.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DnaK Functions as a Central Hub in the E. coli Chaperone Network</style></title><secondary-title><style face="normal" font="default" size="100%">Cell Reports</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Speretta, E.</style></author><author><style face="normal" font="default" size="100%">Jahn, T. R.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, G. G.</style></author><author><style face="normal" font="default" size="100%">Favrin, G.</style></author><author><style face="normal" font="default" size="100%">Barros, T. P.</style></author><author><style face="normal" font="default" size="100%">Imarisio, S.</style></author><author><style face="normal" font="default" size="100%">Lomas, D. A.</style></author><author><style face="normal" font="default" size="100%">Luheshi, L. M.</style></author><author><style face="normal" font="default" size="100%">Crowther, D. C.</style></author><author><style face="normal" font="default" size="100%">Dobson, C. M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expression in Drosophila of Tandem Aβ Peptides Provides Insights Into the Link Between Aggregation and Neurotoxicity</style></title><secondary-title><style face="normal" font="default" size="100%">J Biol Chem</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dessimoz, C.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Roos, DS.</style></author><author><style face="normal" font="default" size="100%">Sonnhammer, EL.</style></author><author><style face="normal" font="default" size="100%">Herrero, J.</style></author><author><style face="normal" font="default" size="100%">the Quest for Orthologs Consortium</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Toward community standards in the quest for orthologs.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics (Oxford, England)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/bts050</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">900–904</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The identification of orthologs-genes pairs descended from a common ancestor through speciation, rather than duplication-has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second 'Quest for Orthologs' meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications. CONTACT: dessimoz@ebi.ac.uk.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ollivier, M.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Poulain, J.</style></author><author><style face="normal" font="default" size="100%">Gavory, F.</style></author><author><style face="normal" font="default" size="100%">Leterme, N.</style></author><author><style face="normal" font="default" size="100%">Gauthier, JP.</style></author><author><style face="normal" font="default" size="100%">Legeai, F.</style></author><author><style face="normal" font="default" size="100%">Tagu, D.</style></author><author><style face="normal" font="default" size="100%">Simon, JC.</style></author><author><style face="normal" font="default" size="100%">Rispe, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of gene repertoires and patterns of evolutionary rates in eight aphid species that differ by reproductive mode.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol Evol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/gbe/evr140</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">155–167</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In theory, the loss of sexual reproduction is expected to result in the accumulation of deleterious mutations. In aphids, two main types of life cycle, cyclic and obligate parthenogenesis, represent respectively &quot;sexual&quot; and &quot;asexual&quot; reproductive modes. We used the complete pea aphid genome and previously published expressed sequence tags (ESTs) from two other aphid species. In addition, we obtained 100,000 new ESTs from five more species. The final set comprised four sexual and four asexual aphid species and served to test the influence of the reproductive mode on the evolutionary rates of genes. We reconstructed coding sequences from ESTs and annotated these genes, discovering a novel peptide gene family that appears to be among the most highly expressed transcripts from several aphid species. From 203 genes found to be 1:1 orthologs among the eight species considered, we established a species tree that partly conflicted with taxonomy (for Myzus ascalonicus). We then used this topology to evaluate the dynamics of evolutionary rates and mutation accumulation in the four sexual and four asexual taxa. No significant increase of the nonsynonymous to synonymous ratio or of nonsynonymous mutation numbers was found in any of the four branches for asexual taxa. We however found a significant increase of the synonymous rate in the branch leading to the asexual species Rhopalosiphum maidis, which could be due to a change in the mutation rate or to an increased number of generations implied by its change of life cycle.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Torrent, M.</style></author><author><style face="normal" font="default" size="100%">Di Tommaso, P.</style></author><author><style face="normal" font="default" size="100%">Pulido, D.</style></author><author><style face="normal" font="default" size="100%">Nogués, MV.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Boix, E.</style></author><author><style face="normal" font="default" size="100%">Andreu, D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">AMPA: an automated web server for prediction of protein antimicrobial regions.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btr604</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">130–131</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">AMPA is a web application for assessing the antimicrobial domains of proteins, with a focus on the design on new antimicrobial drugs. The application provides fast discovery of antimicrobial patterns in proteins that can be used to develop new peptide-based drugs against pathogens. Results are shown in a user-friendly graphical interface and can be downloaded as raw data for later examination.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ng, SY.</style></author><author><style face="normal" font="default" size="100%">Johnson, R.</style></author><author><style face="normal" font="default" size="100%">Stanton, LW.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Human long non-coding RNAs promote pluripotency and neuronal differentiation by association with chromatin modifiers and transcription factors.</style></title><secondary-title><style face="normal" font="default" size="100%">EMBO J.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/emboj.2011.459</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">522–533</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Long non-coding RNAs (lncRNAs) are a numerous class of newly discovered genes in the human genome, which have been proposed to be key regulators of biological processes, including stem cell pluripotency and neurogenesis. However, at present very little functional characterization of lncRNAs in human differentiation has been carried out. In the present study, we address this using human embryonic stem cells (hESCs) as a paradigm for pluripotency and neuronal differentiation. With a newly developed method, hESCs were robustly and efficiently differentiated into neurons, and we profiled the expression of thousands of lncRNAs using a custom-designed microarray. Some hESC-specific lncRNAs involved in pluripotency maintenance were identified, and shown to physically interact with SOX2, and PRC2 complex component, SUZ12. Using a similar approach, we identified lncRNAs required for neurogenesis. Knockdown studies indicated that loss of any of these lncRNAs blocked neurogenesis, and immunoprecipitation studies revealed physical association with REST and SUZ12. This study indicates that lncRNAs are important regulators of pluripotency and neurogenesis, and represents important evidence for an indispensable role of lncRNAs in human brain development.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erb, I.</style></author><author><style face="normal" font="default" size="100%">González-Vallinas, JR.</style></author><author><style face="normal" font="default" size="100%">Bussotti, G.</style></author><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Eyras, E.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Use of ChIP-Seq data for the design of a multiple promoter-alignment method.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkr1292</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">e52</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We address the challenge of regulatory sequence alignment with a new method, Pro-Coffee, a multiple aligner specifically designed for homologous promoter regions. Pro-Coffee uses a dinucleotide substitution matrix estimated on alignments of functional binding sites from TRANSFAC. We designed a validation framework using several thousand families of orthologous promoters. This dataset was used to evaluate the accuracy for predicting true human orthologs among their paralogs. We found that whereas other methods achieve on average 73.5% accuracy, and 77.6% when trained on that same dataset, the figure goes up to 80.4% for Pro-Coffee. We then applied a novel validation procedure based on multi-species ChIP-seq data. Trained and untrained methods were tested for their capacity to correctly align experimentally detected binding sites. Whereas the average number of correctly aligned sites for two transcription factors is 284 for default methods and 316 for trained methods, Pro-Coffee achieves 331, 16.5% above the default average. We find a high correlation between a method's performance when classifying orthologs and its ability to correctly align proven binding sites. Not only has this interesting biological consequences, it also allows us to conclude that any method that is trained on the ortholog data set will result in functionally more informative alignments.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Derrien, T.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Johnson, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Long Non-Coding RNAs: A New (P)layer in the &quot;Dark Matter&quot;</style></title><secondary-title><style face="normal" font="default" size="100%">Front Genet.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.frontiersin.org/Non-Coding_RNA/10.3389/fgene.2011.00107/abstract</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">107</style></number><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">1–6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The transcriptome of a cell is represented by a myriad of different RNA molecules with and without protein-coding capacities. In recent years, advances in sequencing technologies have allowed researchers to more fully appreciate the complexity of whole transcriptomes, showing that the vast majority of the genome is transcribed, producing a diverse population of non-protein coding RNAs (ncRNAs). Thus, the biological significance of non-coding RNAs (ncRNAs) have been largely underestimated. Amongst these multiple classes of ncRNAs, the long non-coding RNAs (lncRNAs) are apparently the most numerous and functionally diverse. A small but growing number of lncRNAs have been experimentally studied, and a view is emerging that these are key regulators of epigenetic gene regulation in mammalian cells. LncRNAs have already been implicated in human diseases such as cancer and neurodegeneration, highlighting the importance of this emergent field. In this article, we review the catalogs of annotated lncRNAs and the latest advances in our understanding of lncRNAs.</style></abstract><issue><style face="normal" font="default" size="100%">107</style></issue></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Djebali, S.</style></author><author><style face="normal" font="default" size="100%">Lagarde, J.</style></author><author><style face="normal" font="default" size="100%">Kapranov, P.</style></author><author><style face="normal" font="default" size="100%">Lacroix, V.</style></author><author><style face="normal" font="default" size="100%">Borel, C.</style></author><author><style face="normal" font="default" size="100%">Mudge, JM.</style></author><author><style face="normal" font="default" size="100%">Howald, C.</style></author><author><style face="normal" font="default" size="100%">Foissac, S.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Chrast, J.</style></author><author><style face="normal" font="default" size="100%">Ribeca, P.</style></author><author><style face="normal" font="default" size="100%">Martin, D.</style></author><author><style face="normal" font="default" size="100%">Murray, RR.</style></author><author><style face="normal" font="default" size="100%">Yang, X.</style></author><author><style face="normal" font="default" size="100%">Ghamsari, L.</style></author><author><style face="normal" font="default" size="100%">Lin, C.</style></author><author><style face="normal" font="default" size="100%">Bell, I.</style></author><author><style face="normal" font="default" size="100%">Dumais, E.</style></author><author><style face="normal" font="default" size="100%">Drenkow, J.</style></author><author><style face="normal" font="default" size="100%">Tress, ML.</style></author><author><style face="normal" font="default" size="100%">Gelpí, JL.</style></author><author><style face="normal" font="default" size="100%">Orozco, M.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">van Berkum, NL.</style></author><author><style face="normal" font="default" size="100%">Lajoie, BR.</style></author><author><style face="normal" font="default" size="100%">Vidal, M.</style></author><author><style face="normal" font="default" size="100%">Stamatoyannopoulos, J.</style></author><author><style face="normal" font="default" size="100%">Batut, P.</style></author><author><style face="normal" font="default" size="100%">Dobin, A.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Hubbard, T.</style></author><author><style face="normal" font="default" size="100%">Dekker, J.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Salehi-Ashtiani, K.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evidence for Transcript Networks Composed of Chimeric RNAs in Human Cells</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pone.0028213</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e28213</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Derrien, T.</style></author><author><style face="normal" font="default" size="100%">Estell</style></author><author><style face="normal" font="default" size="100%">Marco Sola, S.</style></author><author><style face="normal" font="default" size="100%">Knowles, DG.</style></author><author><style face="normal" font="default" size="100%">Raineri, E.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Ribeca, P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fast computation and applications of genome mappability.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pone.0030377</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e30377</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a fast mapping-based algorithm to compute the mappability of each region of a reference genome up to a specified number of mismatches. Knowing the mappability of a genome is crucial for the interpretation of massively parallel sequencing experiments. We investigate the properties of the mappability of eukaryotic DNA/RNA both as a whole and at the level of the gene family, providing for various organisms tracks which allow the mappability information to be visually explored. In addition, we show that mappability varies greatly between species and gene classes. Finally, we suggest several practical applications where mappability can be used to refine the analysis of high-throughput sequencing data (SNP calling, gene expression quantification and paired-end experiments). This work highlights mappability as an important concept which deserves to be taken into full account, in particular when massively parallel sequencing technologies are employed. The GEM mappability program belongs to the GEM (GEnome Multitool) suite of programs, which can be freely downloaded for any use from its website (http://gemlibrary.sourceforge.net).</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Adams, D.</style></author><author><style face="normal" font="default" size="100%">Altucci, L.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, S. E.</style></author><author><style face="normal" font="default" size="100%">Ballesteros, J.</style></author><author><style face="normal" font="default" size="100%">Beck, S.</style></author><author><style face="normal" font="default" size="100%">Bird, A.</style></author><author><style face="normal" font="default" size="100%">Bock, C.</style></author><author><style face="normal" font="default" size="100%">Boehm, B.</style></author><author><style face="normal" font="default" size="100%">Campo, E.</style></author><author><style face="normal" font="default" size="100%">Caricasole, A.</style></author><author><style face="normal" font="default" size="100%">Dahl, F.</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, E. T.</style></author><author><style face="normal" font="default" size="100%">Enver, T.</style></author><author><style face="normal" font="default" size="100%">Esteller, M.</style></author><author><style face="normal" font="default" size="100%">Estivill, X.</style></author><author><style face="normal" font="default" size="100%">Ferguson-Smith, A.</style></author><author><style face="normal" font="default" size="100%">Fitzgibbon, J.</style></author><author><style face="normal" font="default" size="100%">Flicek, P.</style></author><author><style face="normal" font="default" size="100%">Giehl, C.</style></author><author><style face="normal" font="default" size="100%">Graf, T.</style></author><author><style face="normal" font="default" size="100%">Grosveld, F.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Gut, I.</style></author><author><style face="normal" font="default" size="100%">Helin, K.</style></author><author><style face="normal" font="default" size="100%">Jarvius, J.</style></author><author><style face="normal" font="default" size="100%">Kuppers, R.</style></author><author><style face="normal" font="default" size="100%">Lehrach, H.</style></author><author><style face="normal" font="default" size="100%">Lengauer, T.</style></author><author><style face="normal" font="default" size="100%">Lernmark, A.</style></author><author><style face="normal" font="default" size="100%">Leslie, D.</style></author><author><style face="normal" font="default" size="100%">Loeffler, M.</style></author><author><style face="normal" font="default" size="100%">Macintyre, E.</style></author><author><style face="normal" font="default" size="100%">Mai, A.</style></author><author><style face="normal" font="default" size="100%">Martens, J. H.</style></author><author><style face="normal" font="default" size="100%">Minucci, S.</style></author><author><style face="normal" font="default" size="100%">Ouwehand, W. H.</style></author><author><style face="normal" font="default" size="100%">Pelicci, P. G.</style></author><author><style face="normal" font="default" size="100%">Pendeville, H.</style></author><author><style face="normal" font="default" size="100%">Porse, B.</style></author><author><style face="normal" font="default" size="100%">Rakyan, V.</style></author><author><style face="normal" font="default" size="100%">Reik, W.</style></author><author><style face="normal" font="default" size="100%">Schrappe, M.</style></author><author><style face="normal" font="default" size="100%">Schubeler, D.</style></author><author><style face="normal" font="default" size="100%">Seifert, M.</style></author><author><style face="normal" font="default" size="100%">Siebert, R.</style></author><author><style face="normal" font="default" size="100%">Simmons, D.</style></author><author><style face="normal" font="default" size="100%">Soranzo, N.</style></author><author><style face="normal" font="default" size="100%">Spicuglia, S.</style></author><author><style face="normal" font="default" size="100%">Stratton, M.</style></author><author><style face="normal" font="default" size="100%">Stunnenberg, H. G.</style></author><author><style face="normal" font="default" size="100%">Tanay, A.</style></author><author><style face="normal" font="default" size="100%">Torrents, D.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Vellenga, E.</style></author><author><style face="normal" font="default" size="100%">Vingron, M.</style></author><author><style face="normal" font="default" size="100%">Walter, J.</style></author><author><style face="normal" font="default" size="100%">Willcocks, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BLUEPRINT to decode the epigenetic signature written in blood</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Biotechnol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">224–226</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lee, JH.,</style></author><author><style face="normal" font="default" size="100%">Wan KL.,</style></author><author><style face="normal" font="default" size="100%">Mohd-Adnan A.,</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of the ferritin family in vertebrates</style></title><secondary-title><style face="normal" font="default" size="100%">Trends in Evol Biol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.pagepress.org/journals/index.php/eb/article/view/eb.2012.e3/3486</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Ferritins are ubiquitous, highly-conserved proteins that constitute one of the most important components of the cellular machinery devoted to the management of iron levels. Various ferritins have been described in vertebrates, though their exact functions and phylogenetic relationships remain to be established. Our attempts to properly annotate two ferritin subunits isolated from the Asian sea bass Lates calcarifer, prompted us to investigate the evolutionary relationships among vertebrate ferritins and their relationships with non-vertebrate homologs. We carried out a detailed screening of mined ferritin sequences by examining the regulatory elements and gene structures. Subsequently, we performed comprehensive phylogenetic analyses involving the various metazoan and vertebrate ferritin chain types, respectively. Our analyses suggest that a single ferritin chain duplicated in the early vertebrates and that the various ferritin chain types in vertebrate and non-vertebrate species evolved independently through lineage-specific duplications. Notably, this includes the mitochondrial ferritin found only in insects and mammals that we show to result from two parallel lineage-specific duplications followed by convergent events of mitochondrial targeting. Regarding the various cytosolic ferritin chains in vertebrates, our results suggest a scenario of a duplication at the base of vertebrates followed by more recent duplications in teleosts and amphibians. This scenario implies that the light chain in mammals is orthologous to the middle chain in teleosts, in contrast to previous claims of a paralogous relationship coupled with differential gene loss. We hypothesise that the extensive differences in sequence and function between these two orthologous chains may have been driven by the adaptation of tetrapods to terrestrial environments, which involved changes in the dynamics of iron uptake and storage. Altogether, our analyses clarify the evolutionary relationships among vertebrate ferritins and pave the way for the interpretation of functional adaptations within an evolutionary framework.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mariotti, M.</style></author><author><style face="normal" font="default" size="100%">Ridge, P. G.</style></author><author><style face="normal" font="default" size="100%">Zhang, Y.</style></author><author><style face="normal" font="default" size="100%">Lobanov, A. V.</style></author><author><style face="normal" font="default" size="100%">Pringle, T. H.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Hatfield, D. L.</style></author><author><style face="normal" font="default" size="100%">Gladyshev, V. N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Composition and evolution of the vertebrate and Mammalian selenoproteomes</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e33066</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bohle, HM.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selection of marker genes using whole-genome DNA polymorphism analysis.</style></title><secondary-title><style face="normal" font="default" size="100%">Evol. Bioinform. Online</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.4137/EBO.S8989</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">161–169</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Molecular markers serve to assign individual samples to specific groups. Such markers should be easily identified and have a high discrimination power, being highly conserved within groups while showing sufficient variability between the groups that are to be distinguished. The availability of a large number of complete genomic sequences now enables the informed selection of genes as molecular markers based on the observed patterns of variability. We derived a new scoring system based on observed DNA polymorphic differences, and which uses the Bayes theorem as adapted by Wilcox. For validation, we applied this system to the problem of identifying individual species within a prokaryotic (Vibrio) and a eukaryotic (Diphyllobothrium) genus for validation. Top-scoring candidates genes Chromosome segregation ATPase and ATPase-subunit 6 showed better discrimination power in Vibrio and Diphyllobothrium, respectively, as compared to standard molecular markers (recA, dnaJ and atpA for Vibrio, and 18s rRNA, ITS and COX1 for Diphyllobothrium).</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chang, JM.</style></author><author><style face="normal" font="default" size="100%">Di Tommaso, P.</style></author><author><style face="normal" font="default" size="100%">Taly, JF.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2105-13-S4-S1</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">13 Suppl 4</style></volume><pages><style face="normal" font="default" size="100%">S1</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Transmembrane proteins (TMPs) constitute about 20 30% of all protein coding genes. The relative lack of experimental structure has so far made it hard to develop specific alignment methods and the current state of the art (PRALINE™) only manages to recapitulate 50% of the positions in the reference alignments available from the BAliBASE2-ref7.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnold, P.</style></author><author><style face="normal" font="default" size="100%">Erb, I.</style></author><author><style face="normal" font="default" size="100%">Pachkov, M.</style></author><author><style face="normal" font="default" size="100%">Molina, N.</style></author><author><style face="normal" font="default" size="100%">van Nimwegen, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MotEvo: integrated Bayesian probabilistic methods for inferring regulatory sites and motifs on multiple alignments of DNA sequences</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><publisher><style face="normal" font="default" size="100%">Oxford University Press</style></publisher><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">487–494</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bussotti, G.</style></author><author><style face="normal" font="default" size="100%">Raineri, E.</style></author><author><style face="normal" font="default" size="100%">Erb, I.</style></author><author><style face="normal" font="default" size="100%">Zytnicki, M.</style></author><author><style face="normal" font="default" size="100%">Wilm, A.</style></author><author><style face="normal" font="default" size="100%">Beaudoing, E.</style></author><author><style face="normal" font="default" size="100%">Bucher, P</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BlastR–fast and accurate database searches for non-coding RNAs.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkr335</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">16</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">6886–6895</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kedzierska, AM.</style></author><author><style face="normal" font="default" size="100%">Drton, M.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Casanellas, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SPIn: model selection for phylogenetic mixtures via linear invariants.</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular biology and evolution</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/molbev/msr259</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In phylogenetic inference an evolutionary model describes the substitution processes along each edge of a phylogenetic tree. Misspecification of the model has important implications for the analysis of phylogenetic data. Conventionally, however, the selection of a suitable evolutionary model is based on heuristics or relies on the choice of an approximate input tree. We introduce a method for model Selection in Phylogenetics based on linear INvariants (SPIn), which uses recent insights on linear invariants to characterize a model of nucleotide evolution for phylogenetic mixtures on any number of components. Linear invariants are constraints among the joint probabilities of the bases in the operational taxonomic units that hold irrespective of the tree topologies appearing in the mixtures. SPIn therefore requires no input tree and is designed to deal with non-homogeneous phylogenetic data consisting of multiple sequence alignments showing different patterns of evolution, e.g. concatenated genes, exons and/or introns. Here we report on the results of the proposed method evaluated on multiple sequence alignments simulated under a variety of single-tree and mixture settings for both continuous and discrete-time models. In the simulations, SPIn successfully recovers the underlying evolutionary model and is shown to perform better than existing approaches.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Murakami, T.</style></author><author><style face="normal" font="default" size="100%">Yang, S. P.</style></author><author><style face="normal" font="default" size="100%">Xie, L.</style></author><author><style face="normal" font="default" size="100%">Kawano, T.</style></author><author><style face="normal" font="default" size="100%">Fu, D.</style></author><author><style face="normal" font="default" size="100%">Mukai, A.</style></author><author><style face="normal" font="default" size="100%">Bohm, C.</style></author><author><style face="normal" font="default" size="100%">Chen, F.</style></author><author><style face="normal" font="default" size="100%">Robertson, J.</style></author><author><style face="normal" font="default" size="100%">Suzuki, H.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, G. G.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Kaminski Schierle, G. S.</style></author><author><style face="normal" font="default" size="100%">Chan, F. T.</style></author><author><style face="normal" font="default" size="100%">Moloney, A.</style></author><author><style face="normal" font="default" size="100%">Crowther, D.</style></author><author><style face="normal" font="default" size="100%">Kaminski, C. F.</style></author><author><style face="normal" font="default" size="100%">Zhen, M.</style></author><author><style face="normal" font="default" size="100%">St George-Hyslop, P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ALS mutations in FUS cause neuronal dysfunction and death in Caenorhabditis elegans by a dominant gain-of-function mechanism</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">It is unclear whether mutations in fused in sarcoma (FUS) cause familial amyotrophic lateral sclerosis via a loss-of-function effect due to titrating FUS from the nucleus or a gain-of-function effect from cytoplasmic overabundance. To investigate this question, we generated a series of independent Caenorhabditis elegans lines expressing mutant or wild-type (WT) human FUS. We show that mutant FUS, but not WT-FUS, causes cytoplasmic mislocalization associated with progressive motor dysfunction and reduced lifespan. The severity of the mutant phenotype in C. elegans was directly correlated with the severity of the illness caused by the same mutation in humans, arguing that this model closely replicates key features of the human illness. Importantly, the mutant phenotype could not be rescued by overexpression of WT-FUS, even though WT-FUS had physiological intracellular localization, and was not recruited to the cytoplasmic mutant FUS aggregates. Our data suggest that FUS mutants cause neuronal dysfunction by a dominant gain-of-function effect related either to neurotoxic aggregates of mutant FUS in the cytoplasm or to dysfunction in its RNA-binding functions.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Silva, LL.</style></author><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Zerlotini, A.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Oliveira, G.</style></author><author><style face="normal" font="default" size="100%">Nahum, LA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolutionary histories of expanded peptidase families in Schistosoma mansoni.</style></title><secondary-title><style face="normal" font="default" size="100%">Mem. Inst. Oswaldo Cruz</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov/2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/22124560</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">106</style></volume><pages><style face="normal" font="default" size="100%">864–877</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Schistosoma mansoni is one of the three main causative agents of human schistosomiasis, a major health problem with a vast socio-economic impact. Recent advances in the proteomic analysis of schistosomes have revealed that peptidases are the main virulence factors involved in the pathogenesis of this disease. In this context, evolutionary studies can be applied to identify peptidase families that have been expanded in genomes over time in response to different selection pressures. Using a phylogenomic approach, we searched for expanded endopeptidase families in the S. mansoni predicted proteome with the aim of contributing to the knowledge of such enzymes as potential therapeutic targets. We found three endopeptidase families that comprise leishmanolysins (metallopeptidase M8 family), cercarial elastases (serine peptidase S1 family) and cathepsin D proteins (aspartic peptidase A1 family). Our results suggest that the Schistosoma members of these families originated from successive gene duplication events in the parasite lineage after its diversification from other metazoans. Overall, critical residues are conserved among the duplicated genes/proteins. Furthermore, each protein family displays a distinct evolutionary history. Altogether, this work provides an evolutionary view of three S. mansoni peptidase families, which allows for a deeper understanding of the genomic complexity and lineage-specific adaptations potentially related to the parasitic lifestyle.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Merhej, V.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Royer-Carenzi, M.</style></author><author><style face="normal" font="default" size="100%">Pontarotti, P.</style></author><author><style face="normal" font="default" size="100%">Raoult, D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The rhizome of life: the sympatric Rickettsia felis paradigm demonstrates the random transfer of DNA sequences.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol. Biol. Evol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/molbev/msr239</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">3213–3223</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The intracellular flea symbiont, Rickettsia felis, may meet other organisms intracellularly such as R. typhi. We used a single-gene phylogenetic approach of the 1375 R. felis genes to look for horizontal transfers that occurred as a result of the bacterial promiscuity with other organisms. Our results showed that besides genes that are linked to the Spotted Fever Group, 165 genes have a different history and are linked to other Rickettsia such as R. bellii (107 genes), R. typhi (15 genes), or to other bacteria such as Legionella sp. and Francisella sp. or to eukaryotes. Among these genes, we identified 73 individual genes and 34 spatial clusters containing 2-4 adjacent genes, a total of 79 genes, with evidence of en bloc transfer. We described 13 chimeric genes resulting from gene recombination with sympatric R. typhi. The transferred DNA sequences present different sizes and functions, suggesting that the horizontal transfer in R. felis is random and neutral within its specific host. Our study shows that the strict intracellular bacteria R. felis exhibits a mosaic genome. We therefore developed a new representation for the evolutionary history of R. felis showing its different putative ancestors in the form of a rhizome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Taly, JF.</style></author><author><style face="normal" font="default" size="100%">Magis, C.</style></author><author><style face="normal" font="default" size="100%">Bussotti, G.</style></author><author><style face="normal" font="default" size="100%">Chang, JM.</style></author><author><style face="normal" font="default" size="100%">Di Tommaso, P.</style></author><author><style face="normal" font="default" size="100%">Erb, I.</style></author><author><style face="normal" font="default" size="100%">Espinosa-Carrasco, J.</style></author><author><style face="normal" font="default" size="100%">Kemena, C.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using the T-Coffee package to build multiple sequence alignments of protein, RNA, DNA sequences and 3D structures.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Protoc</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nprot.2011.393</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">1669–1682</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">T-Coffee (Tree-based consistency objective function for alignment evaluation) is a versatile multiple sequence alignment (MSA) method suitable for aligning most types of biological sequences. The main strength of T-Coffee is its ability to combine third party aligners and to integrate structural (or homology) information when building MSAs. The series of protocols presented here show how the package can be used to multiply align proteins, RNA and DNA sequences. The protein section shows how users can select the most suitable T-Coffee mode for their data set. Detailed protocols include T-Coffee, the default mode, M-Coffee, a meta version able to combine several third party aligners into one, PSI (position-specific iterated)-Coffee, the homology extended mode suitable for remote homologs and Expresso, the structure-based multiple aligner. We then also show how the T-RMSD (tree based on root mean square deviation) option can be used to produce a functionally informative structure-based clustering. RNA alignment procedures are described for using R-Coffee, a mode able to use predicted RNA secondary structures when aligning RNA sequences. DNA alignments are illustrated with Pro-Coffee, a multiple aligner specific of promoter regions. We also present some of the many reformatting utilities bundled with T-Coffee. The package is an open-source freeware available from http://www.tcoffee.org/.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gonzalez-Porta, M.</style></author><author><style face="normal" font="default" size="100%">Calvo, M.</style></author><author><style face="normal" font="default" size="100%">Sammeth, M.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of alternative splicing variability in human populations</style></title><secondary-title><style face="normal" font="default" size="100%">Genome research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.121947.111</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">DNA arrays have been widely used to perform transcriptome wide analysis of gene expression and many methods have been developed to measure gene expression variability and to compare gene expression between conditions. As RNA-seq is also becoming increasingly popular for transcriptome characterization, the possibility exists for further quantification of individual alternative transcript isoforms, and therefore for estimating the relative ratios of alternative splice forms within a given gene. Changes in splicing ratios, even without changes in overall gene expression, may have important phenotypic effects. Here we have developed statistical methodology to measure variability in splicing ratios within conditions, to compare it between conditions and to identify genes with condition specific splicing ratios. Furthermore, we have developed methodology to deconvolute the relative contribution of variability in gene expression vs variability in splicing ratios to the overall variability of transcript abundances. As a proof of concept, we have applied this methodology to estimates of transcript abundances obtained from RNA-seq experiments in lymphoblastoid cells from Caucasian and Yoruban individuals. We have found that protein coding genes exhibit low splicing variability within populations, with many genes exhibiting constant ratios across individuals. When comparing these two populations, we have found that up to 10% of the studied protein coding genes exhibit population-specific splicing ratios. We estimate that about 60% of the total variability observed in the abundance of transcript isoforms can be explained by variability in transcription. A large fraction of the remaining variability can likely result from variability in splicing. Finally, we also detected that variability in splicing is uncommon without variability in transcription.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maxwell, CA.</style></author><author><style face="normal" font="default" size="100%">Benítez, J.</style></author><author><style face="normal" font="default" size="100%">Gómez-Baldó, L.</style></author><author><style face="normal" font="default" size="100%">Osorio, A.</style></author><author><style face="normal" font="default" size="100%">Bonifaci, N.</style></author><author><style face="normal" font="default" size="100%">Fernández-Ramires, R.</style></author><author><style face="normal" font="default" size="100%">Costes, SV.</style></author><author><style face="normal" font="default" size="100%">Guinó, E.</style></author><author><style face="normal" font="default" size="100%">Chen, H.</style></author><author><style face="normal" font="default" size="100%">Evans, GJ.</style></author><author><style face="normal" font="default" size="100%">Mohan, P.</style></author><author><style face="normal" font="default" size="100%">Català, I.</style></author><author><style face="normal" font="default" size="100%">Petit, A.</style></author><author><style face="normal" font="default" size="100%">Aguilar, H.</style></author><author><style face="normal" font="default" size="100%">Villanueva, A.</style></author><author><style face="normal" font="default" size="100%">Aytes, A.</style></author><author><style face="normal" font="default" size="100%">Serra-Musach, J.</style></author><author><style face="normal" font="default" size="100%">Rennert, G.</style></author><author><style face="normal" font="default" size="100%">Lejbkowicz, F.</style></author><author><style face="normal" font="default" size="100%">Peterlongo, P.</style></author><author><style face="normal" font="default" size="100%">Manoukian, S.</style></author><author><style face="normal" font="default" size="100%">Peissel, B.</style></author><author><style face="normal" font="default" size="100%">Ripamonti, CB.</style></author><author><style face="normal" font="default" size="100%">Bonanni, B.</style></author><author><style face="normal" font="default" size="100%">Viel, A.</style></author><author><style face="normal" font="default" size="100%">Allavena, A.</style></author><author><style face="normal" font="default" size="100%">Bernard, L.</style></author><author><style face="normal" font="default" size="100%">Radice, P.</style></author><author><style face="normal" font="default" size="100%">Friedman, E.</style></author><author><style face="normal" font="default" size="100%">Kaufman, B.</style></author><author><style face="normal" font="default" size="100%">Laitman, Y.</style></author><author><style face="normal" font="default" size="100%">Dubrovsky, M.</style></author><author><style face="normal" font="default" size="100%">Milgrom, R.</style></author><author><style face="normal" font="default" size="100%">Jakubowska, A.</style></author><author><style face="normal" font="default" size="100%">Cybulski, C.</style></author><author><style face="normal" font="default" size="100%">Gorski, B.</style></author><author><style face="normal" font="default" size="100%">Jaworska, K.</style></author><author><style face="normal" font="default" size="100%">Durda, K.</style></author><author><style face="normal" font="default" size="100%">Sukiennicki, G.</style></author><author><style face="normal" font="default" size="100%">Lubiński, J.</style></author><author><style face="normal" font="default" size="100%">Shugart, YY.</style></author><author><style face="normal" font="default" size="100%">Domchek, SM.</style></author><author><style face="normal" font="default" size="100%">Letrero, R.</style></author><author><style face="normal" font="default" size="100%">Weber, BL.</style></author><author><style face="normal" font="default" size="100%">Hogervorst, FB.</style></author><author><style face="normal" font="default" size="100%">Rookus, MA.</style></author><author><style face="normal" font="default" size="100%">Collee, JM.</style></author><author><style face="normal" font="default" size="100%">Devilee, P.</style></author><author><style face="normal" font="default" size="100%">Ligtenberg, MJ.</style></author><author><style face="normal" font="default" size="100%">van der Luijt, RB.</style></author><author><style face="normal" font="default" size="100%">Aalfs, CM.</style></author><author><style face="normal" font="default" size="100%">Waisfisz, Q.</style></author><author><style face="normal" font="default" size="100%">Wijnen, J.</style></author><author><style face="normal" font="default" size="100%">van Roozendaal, CE.</style></author><author><style face="normal" font="default" size="100%">HEBON</style></author><author><style face="normal" font="default" size="100%">EMBRACE</style></author><author><style face="normal" font="default" size="100%">Easton, DF.</style></author><author><style face="normal" font="default" size="100%">Peock, S.</style></author><author><style face="normal" font="default" size="100%">Cook, M.</style></author><author><style face="normal" font="default" size="100%">Oliver, C.</style></author><author><style face="normal" font="default" size="100%">Frost, D.</style></author><author><style face="normal" font="default" size="100%">Harrington, P.</style></author><author><style face="normal" font="default" size="100%">Evans, DG.</style></author><author><style face="normal" font="default" size="100%">Lalloo, F.</style></author><author><style face="normal" font="default" size="100%">Eeles, R.</style></author><author><style face="normal" font="default" size="100%">Izatt, L.</style></author><author><style face="normal" font="default" size="100%">Chu, C.</style></author><author><style face="normal" font="default" size="100%">Eccles, D.</style></author><author><style face="normal" font="default" size="100%">Douglas, F.</style></author><author><style face="normal" font="default" size="100%">Brewer, C.</style></author><author><style face="normal" font="default" size="100%">Nevanlinna, H.</style></author><author><style face="normal" font="default" size="100%">Heikkinen, T.</style></author><author><style face="normal" font="default" size="100%">Couch, FJ.</style></author><author><style face="normal" font="default" size="100%">Lindor, NM.</style></author><author><style face="normal" font="default" size="100%">Wang, X.</style></author><author><style face="normal" font="default" size="100%">Godwin, AK.</style></author><author><style face="normal" font="default" size="100%">Caligo, MA.</style></author><author><style face="normal" font="default" size="100%">Lombardi, G.</style></author><author><style face="normal" font="default" size="100%">Loman, N.</style></author><author><style face="normal" font="default" size="100%">Karlsson, P.</style></author><author><style face="normal" font="default" size="100%">Ehrencrona, H.</style></author><author><style face="normal" font="default" size="100%">von Wachenfeldt, A.</style></author><author><style face="normal" font="default" size="100%">SWE-BRCA</style></author><author><style face="normal" font="default" size="100%">Bjork Barkardottir, R.</style></author><author><style face="normal" font="default" size="100%">Hamann, U.</style></author><author><style face="normal" font="default" size="100%">Rashid, MU.</style></author><author><style face="normal" font="default" size="100%">Lasa, A.</style></author><author><style face="normal" font="default" size="100%">Caldés, T.</style></author><author><style face="normal" font="default" size="100%">Andrés, R.</style></author><author><style face="normal" font="default" size="100%">Schmitt, M.</style></author><author><style face="normal" font="default" size="100%">Assmann, V.</style></author><author><style face="normal" font="default" size="100%">Stevens, K.</style></author><author><style face="normal" font="default" size="100%">Offit, K.</style></author><author><style face="normal" font="default" size="100%">Curado, J.</style></author><author><style face="normal" font="default" size="100%">Tilgner, H.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Aiza, G.</style></author><author><style face="normal" font="default" size="100%">Brunet, J.</style></author><author><style face="normal" font="default" size="100%">Castellsagué, J.</style></author><author><style face="normal" font="default" size="100%">Martrat, G.</style></author><author><style face="normal" font="default" size="100%">Urruticoechea, A.</style></author><author><style face="normal" font="default" size="100%">Blanco, I.</style></author><author><style face="normal" font="default" size="100%">Tihomirova, L.</style></author><author><style face="normal" font="default" size="100%">Goldgar, DE.</style></author><author><style face="normal" font="default" size="100%">Buys, S.</style></author><author><style face="normal" font="default" size="100%">John, EM.</style></author><author><style face="normal" font="default" size="100%">Miron, A.</style></author><author><style face="normal" font="default" size="100%">Southey, M.</style></author><author><style face="normal" font="default" size="100%">Daly, MB.</style></author><author><style face="normal" font="default" size="100%">BCFR</style></author><author><style face="normal" font="default" size="100%">Schmutzler, RK.</style></author><author><style face="normal" font="default" size="100%">Wappenschmidt, B.</style></author><author><style face="normal" font="default" size="100%">Meindl, A.</style></author><author><style face="normal" font="default" size="100%">Arnold, N.</style></author><author><style face="normal" font="default" size="100%">Deissler, H.</style></author><author><style face="normal" font="default" size="100%">Varon-Mateeva, R.</style></author><author><style face="normal" font="default" size="100%">Sutter, C.</style></author><author><style face="normal" font="default" size="100%">Niederacher, D.</style></author><author><style face="normal" font="default" size="100%">Imyamitov, E.</style></author><author><style face="normal" font="default" size="100%">Sinilnikova, OM.</style></author><author><style face="normal" font="default" size="100%">Stoppa-Lyonne, D.</style></author><author><style face="normal" font="default" size="100%">Mazoyer, S.</style></author><author><style face="normal" font="default" size="100%">Verny-Pierre, C.</style></author><author><style face="normal" font="default" size="100%">Castera, L.</style></author><author><style face="normal" font="default" size="100%">de Pauw, A.</style></author><author><style face="normal" font="default" size="100%">Bignon, YJ.</style></author><author><style face="normal" font="default" size="100%">Uhrhammer, N.</style></author><author><style face="normal" font="default" size="100%">Peyrat, JP.</style></author><author><style face="normal" font="default" size="100%">Vennin, P.</style></author><author><style face="normal" font="default" size="100%">Fert Ferrer, S.</style></author><author><style face="normal" font="default" size="100%">Collonge-Rame, MA.</style></author><author><style face="normal" font="default" size="100%">Mortemousque, I.</style></author><author><style face="normal" font="default" size="100%">GEMO Study Collaborators</style></author><author><style face="normal" font="default" size="100%">Spurdle, AB.</style></author><author><style face="normal" font="default" size="100%">Beesley, J.</style></author><author><style face="normal" font="default" size="100%">Chen, X.</style></author><author><style face="normal" font="default" size="100%">Healey, S.</style></author><author><style face="normal" font="default" size="100%">kConFab</style></author><author><style face="normal" font="default" size="100%">Barcellos-Hoff, MH.</style></author><author><style face="normal" font="default" size="100%">Vidal, M.</style></author><author><style face="normal" font="default" size="100%">Gruber, SB.</style></author><author><style face="normal" font="default" size="100%">Lázaro, C.</style></author><author><style face="normal" font="default" size="100%">Capellá, G.</style></author><author><style face="normal" font="default" size="100%">McGuffog, L.</style></author><author><style face="normal" font="default" size="100%">Nathanson, KL.</style></author><author><style face="normal" font="default" size="100%">Antoniou, AC.</style></author><author><style face="normal" font="default" size="100%">Chenevix-Trench, G.</style></author><author><style face="normal" font="default" size="100%">Fleisch, MC.</style></author><author><style face="normal" font="default" size="100%">Moreno, V.</style></author><author><style face="normal" font="default" size="100%">Pujana, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interplay between BRCA1 and RHAMM Regulates Epithelial Apicobasal Polarization and May Influence Risk of Breast Cancer</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pbio.1001199</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">e1001199</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Differentiated mammary epithelium shows apicobasal polarity, and loss of tissue organization is an early hallmark of breast carcinogenesis. In BRCA1 mutation carriers, accumulation of stem and progenitor cells in normal breast tissue and increased risk of developing tumors of basal-like type suggest that BRCA1 regulates stem/progenitor cell proliferation and differentiation. However, the function of BRCA1 in this process and its link to carcinogenesis remain unknown. Here we depict a molecular mechanism involving BRCA1 and RHAMM that regulates apicobasal polarity and, when perturbed, may increase risk of breast cancer. Starting from complementary genetic analyses across families and populations, we identified common genetic variation at the low-penetrance susceptibility HMMR locus (encoding for RHAMM) that modifies breast cancer risk among BRCA1, but probably not BRCA2, mutation carriers: n = 7,584, weighted hazard ratio ((w)HR) = 1.09 (95% CI 1.02-1.16), p(trend) = 0.017; and n = 3,965, (w)HR = 1.04 (95% CI 0.94-1.16), p(trend) = 0.43; respectively. Subsequently, studies of MCF10A apicobasal polarization revealed a central role for BRCA1 and RHAMM, together with AURKA and TPX2, in essential reorganization of microtubules. Mechanistically, reorganization is facilitated by BRCA1 and impaired by AURKA, which is regulated by negative feedback involving RHAMM and TPX2. Taken together, our data provide fundamental insight into apicobasal polarization through BRCA1 function, which may explain the expanded cell subsets and characteristic tumor type accompanying BRCA1 mutation, while also linking this process to sporadic breast cancer through perturbation of HMMR/RHAMM.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mudge, JM.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Fernandez-Banet, J.</style></author><author><style face="normal" font="default" size="100%">Alioto, T.</style></author><author><style face="normal" font="default" size="100%">Derrien, T.</style></author><author><style face="normal" font="default" size="100%">Howald, C.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Hubbard, T.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The origins, evolution and functional potential of alternative splicing in vertebrates</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular biology and evolution</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/molbev/msr127</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['Alternative splicing (AS) has the potential to greatly expand the functional repertoire of mammalian transcriptomes. However, few variant transcripts have been characterized functionally, making it difficult to assess the contribution of AS to the generation of phenotypic complexity and to study the evolution of splicing patterns. We have compared the AS of 309 protein-coding genes in the human ENCODE pilot regions against their mouse orthologs in unprecedented detail, utilizing traditional transcriptomic and RNAseq data. The conservation status of every transcript has been investigated, and each functionally categorized as coding (separated into CDS or nonsense-mediated decay (NMD)-linked) or non-coding. 36.7% of human and 19.3% of mouse coding transcripts are species specific, and we observe a 3.6 times excess of human NMD transcripts compared with mouse; in contrast to previous studies, the majority of species specific AS is unlinked to transposable elements. We observe one conserved CDS variant and one conserved NMD variant per 2.3 and 11.4 genes respectively. Subsequently, we identify and characterize equivalent AS patterns for 22.9% of these CDS or NMD-linked events in non-mammalian vertebrate genomes, and our data indicate that functional NMD-linked AS is more widespread and ancient than previously thought. Furthermore, whilst we observe an association between conserved AS and elevated sequence conservation, as previously reported, we emphasize that 30% of conserved AS exons display sequence conservation below the average score for constitutive exons. In conclusion, we demonstrate the value of detailed comparative annotation in generating a comprehensive set of AS transcripts, increasing our understanding of AS evolution in vertebrates. Our data support a model whereby the acquisition of functional AS has occurred throughout vertebrate evolution, and is considered alongside amino acid change as a key mechanism in gene evolution.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Di Tommaso, P.</style></author><author><style face="normal" font="default" size="100%">Moretti, S.</style></author><author><style face="normal" font="default" size="100%">Xenarios, I.</style></author><author><style face="normal" font="default" size="100%">Orobitg, M.</style></author><author><style face="normal" font="default" size="100%">Montanyola, A.</style></author><author><style face="normal" font="default" size="100%">Chang, JM.</style></author><author><style face="normal" font="default" size="100%">Taly, JF.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information and homology extension.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic acids research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkr245</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This article introduces a new interface for T-Coffee, a consistency-based multiple sequence alignment program. This interface provides an easy and intuitive access to the most popular functionality of the package. These include the default T-Coffee mode for protein and nucleic acid sequences, the M-Coffee mode that allows combining the output of any other aligners, and template-based modes of T-Coffee that deliver high accuracy alignments while using structural or homology derived templates. These three available template modes are Expresso for the alignment of protein with a known 3D-Structure, R-Coffee to align RNA sequences with conserved secondary structures and PSI-Coffee to accurately align distantly related sequences using homology extension. The new server benefits from recent improvements of the T-Coffee algorithm and can align up to 150 sequences as long as 10 000 residues and is available from both http://www.tcoffee.org and its main mirror http://tcoffee.crg.cat.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pryszcz, LP.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MetaPhOrs: orthology and paralogy predictions from multiple phylogenetic evidence using a consistency-based confidence score.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkq953</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">e32</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['Reliable prediction of orthology is central to comparative genomics. Approaches based on phylogenetic analyses closely resemble the original definition of orthology and paralogy and are known to be highly accurate. However, the large computational cost associated to these analyses is a limiting factor that often prevents its use at genomic scales. Recently, several projects have addressed the reconstruction of large collections of high-quality phylogenetic trees from which orthology and paralogy relationships can be inferred. This provides us with the opportunity to infer the evolutionary relationships of genes from multiple, independent, phylogenetic trees. Using such strategy, we combine phylogenetic information derived from different databases, to predict orthology and paralogy relationships for 4.1 million proteins in 829 fully sequenced genomes. We show that the number of independent sources from which a prediction is made, as well as the level of consistency across predictions, can be used as reliable confidence scores. A webserver has been developed to easily access these data (http://orthology.phylomedb.org), which provides users with a global repository of phylogeny-based orthology and paralogy predictions.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bellucci, M.</style></author><author><style face="normal" font="default" size="100%">Agostini, F.</style></author><author><style face="normal" font="default" size="100%">Masin, M.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, G. G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting protein associations with long noncoding RNAs</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Methods</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">444–445</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martin, D.</style></author><author><style face="normal" font="default" size="100%">Pantoja, C.</style></author><author><style face="normal" font="default" size="100%">Miñán, AF.</style></author><author><style face="normal" font="default" size="100%">Valdes-Quezada, C.</style></author><author><style face="normal" font="default" size="100%">Moltó, E.</style></author><author><style face="normal" font="default" size="100%">Matesanz, F.</style></author><author><style face="normal" font="default" size="100%">Bogdanović, O.</style></author><author><style face="normal" font="default" size="100%">de la Calle-Mustienes, E.</style></author><author><style face="normal" font="default" size="100%">Domínguez, O.</style></author><author><style face="normal" font="default" size="100%">Taher, L.</style></author><author><style face="normal" font="default" size="100%">Furlan-Magaril, M.</style></author><author><style face="normal" font="default" size="100%">Alcina, A.</style></author><author><style face="normal" font="default" size="100%">Cañón, S.</style></author><author><style face="normal" font="default" size="100%">Fedetz, M.</style></author><author><style face="normal" font="default" size="100%">Blasco, MA.</style></author><author><style face="normal" font="default" size="100%">Pereira, PS.</style></author><author><style face="normal" font="default" size="100%">Ovcharenko, I.</style></author><author><style face="normal" font="default" size="100%">Recillas-Targa, F.</style></author><author><style face="normal" font="default" size="100%">Montoliu, L.</style></author><author><style face="normal" font="default" size="100%">Manzanares, M.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Serrano, M.</style></author><author><style face="normal" font="default" size="100%">Casares, F.</style></author><author><style face="normal" font="default" size="100%">Gómez-Skarmeta, JL.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide CTCF distribution in vertebrates defines equivalent sites that aid the identification of disease-associated genes</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Struct. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nsmb.2059</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">708–714</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['Many genomic alterations associated with human diseases localize in noncoding regulatory elements located far from the promoters they regulate, making it challenging to link noncoding mutations or risk-associated variants with target genes. The range of action of a given set of enhancers is thought to be defined by insulator elements bound by the 11 zinc-finger nuclear factor CCCTC-binding protein (CTCF). Here we analyzed the genomic distribution of CTCF in various human, mouse and chicken cell types, demonstrating the existence of evolutionarily conserved CTCF-bound sites beyond mammals. These sites preferentially flank transcription factor-encoding genes, often associated with human diseases, and function as enhancer blockers in vivo, suggesting that they act as evolutionarily invariant gene boundaries. We then applied this concept to predict and functionally demonstrate that the polymorphic variants associated with multiple sclerosis located within the EVI5 gene impinge on the adjacent gene GFI1.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Puente, XS.</style></author><author><style face="normal" font="default" size="100%">Pinyol, M.</style></author><author><style face="normal" font="default" size="100%">Quesada, V.</style></author><author><style face="normal" font="default" size="100%">Conde, L.</style></author><author><style face="normal" font="default" size="100%">Ordonez, GR.</style></author><author><style face="normal" font="default" size="100%">Villamor, N.</style></author><author><style face="normal" font="default" size="100%">Escaramis, G.</style></author><author><style face="normal" font="default" size="100%">Jares, P.</style></author><author><style face="normal" font="default" size="100%">Bea, S</style></author><author><style face="normal" font="default" size="100%">González-Díaz, M</style></author><author><style face="normal" font="default" size="100%">Bassaganyas, L.</style></author><author><style face="normal" font="default" size="100%">Baumann, T.</style></author><author><style face="normal" font="default" size="100%">Juan, M.</style></author><author><style face="normal" font="default" size="100%">Lopez-Guerra,  M</style></author><author><style face="normal" font="default" size="100%">Colomer, D.</style></author><author><style face="normal" font="default" size="100%">Tubio, JM</style></author><author><style face="normal" font="default" size="100%">Lopez, C</style></author><author><style face="normal" font="default" size="100%">Navarro, A.</style></author><author><style face="normal" font="default" size="100%">Tornador, C.</style></author><author><style face="normal" font="default" size="100%">Aymerich, M.</style></author><author><style face="normal" font="default" size="100%">Rozman, M.</style></author><author><style face="normal" font="default" size="100%">Hernandez, L</style></author><author><style face="normal" font="default" size="100%">Puente, DA.</style></author><author><style face="normal" font="default" size="100%">Freije, JM.</style></author><author><style face="normal" font="default" size="100%">Velasco, G.</style></author><author><style face="normal" font="default" size="100%">Gutiérrez-Fernández, A.</style></author><author><style face="normal" font="default" size="100%">Costa, D.</style></author><author><style face="normal" font="default" size="100%">Carrió, A.</style></author><author><style face="normal" font="default" size="100%">Guijarro, S.</style></author><author><style face="normal" font="default" size="100%">Enjuanes, A.</style></author><author><style face="normal" font="default" size="100%">Hernández, L.</style></author><author><style face="normal" font="default" size="100%">Yague, J</style></author><author><style face="normal" font="default" size="100%">Nicolas, P</style></author><author><style face="normal" font="default" size="100%">Romeo-Casabona, CM.</style></author><author><style face="normal" font="default" size="100%">Himmelbauer, H.</style></author><author><style face="normal" font="default" size="100%">Castillo, E.</style></author><author><style face="normal" font="default" size="100%">Dohm, JC.</style></author><author><style face="normal" font="default" size="100%">de Sanjose, S</style></author><author><style face="normal" font="default" size="100%">Piris, MA.</style></author><author><style face="normal" font="default" size="100%">de Alava, E.</style></author><author><style face="normal" font="default" size="100%">Miguel, JS.</style></author><author><style face="normal" font="default" size="100%">Royo, R.</style></author><author><style face="normal" font="default" size="100%">Gelpi, JL</style></author><author><style face="normal" font="default" size="100%">Torrents, D.</style></author><author><style face="normal" font="default" size="100%">Orozco, M.</style></author><author><style face="normal" font="default" size="100%">Pisano, DG.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Bayes, M.</style></author><author><style face="normal" font="default" size="100%">Heath, S.</style></author><author><style face="normal" font="default" size="100%">Gut, M.</style></author><author><style face="normal" font="default" size="100%">Klatt, P.</style></author><author><style face="normal" font="default" size="100%">Marshall, J.</style></author><author><style face="normal" font="default" size="100%">Raine, K.</style></author><author><style face="normal" font="default" size="100%">Stebbings, LA.</style></author><author><style face="normal" font="default" size="100%">Futreal, PA.</style></author><author><style face="normal" font="default" size="100%">Stratton, MR.</style></author><author><style face="normal" font="default" size="100%">Campbell, PJ.</style></author><author><style face="normal" font="default" size="100%">Gut, I.</style></author><author><style face="normal" font="default" size="100%">López-Guillermo, A</style></author><author><style face="normal" font="default" size="100%">Estivill, X.</style></author><author><style face="normal" font="default" size="100%">Montserrat, E.</style></author><author><style face="normal" font="default" size="100%">López-Otín, C.</style></author><author><style face="normal" font="default" size="100%">Campo, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature10113</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['Chronic lymphocytic leukaemia (CLL), the most frequent leukaemia in adults in Western countries, is a heterogeneous disease with variable clinical presentation and evolution. Two major molecular subtypes can be distinguished, characterized respectively by a high or low number of somatic hypermutations in the variable region of immunoglobulin genes. The molecular changes leading to the pathogenesis of the disease are still poorly understood. Here we performed whole-genome sequencing of four cases of CLL and identified 46 somatic mutations that potentially affect gene function. Further analysis of these mutations in 363 patients with CLL identified four genes that are recurrently mutated: notch 1 (NOTCH1), exportin 1 (XPO1), myeloid differentiation primary response gene 88 (MYD88) and kelch-like 6 (KLHL6). Mutations in MYD88 and KLHL6 are predominant in cases of CLL with mutated immunoglobulin genes, whereas NOTCH1 and XPO1 mutations are mainly detected in patients with unmutated immunoglobulins. The patterns of somatic mutation, supported by functional and clinical analyses, strongly indicate that the recurrent NOTCH1, MYD88 and XPO1 mutations are oncogenic changes that contribute to the clinical evolution of the disease. To our knowledge, this is the first comprehensive analysis of CLL combining whole-genome sequencing with clinical characteristics and clinical outcomes. It highlights the usefulness of this approach for the identification of clinically relevant mutations in cancer.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Baldwin, AJ.</style></author><author><style face="normal" font="default" size="100%">Knowles, TP.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, G.</style></author><author><style face="normal" font="default" size="100%">Fitzpatrick, A.</style></author><author><style face="normal" font="default" size="100%">Devlin, G.</style></author><author><style face="normal" font="default" size="100%">Shammas, S.</style></author><author><style face="normal" font="default" size="100%">Waudby, CA.</style></author><author><style face="normal" font="default" size="100%">Mossuto, MF.</style></author><author><style face="normal" font="default" size="100%">Gras, SL.</style></author><author><style face="normal" font="default" size="100%">Christodoulou, J.</style></author><author><style face="normal" font="default" size="100%">Anthony-Cahill, SJ.</style></author><author><style face="normal" font="default" size="100%">Barker, PD.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Metastability of Native Proteins and the Phenomenon of Amyloid Formation.</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of the American Chemical Society</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1021/ja2017703</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">An experimental determination of the thermodynamic stabilities of a series of amyloid fibrils reveals that this structural form is likely to be the most stable one that protein molecules can adopt even under physiological conditions. This result challenges the conventional assumption that functional forms of proteins correspond to the global minima in the free energy surfaces and suggests that living systems are conformationally as well as chemically metastable.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sánchez, R.</style></author><author><style face="normal" font="default" size="100%">Serra, F.</style></author><author><style face="normal" font="default" size="100%">Tárraga, J.</style></author><author><style face="normal" font="default" size="100%">Medina, I.</style></author><author><style face="normal" font="default" size="100%">Carbonell, J.</style></author><author><style face="normal" font="default" size="100%">Pulido, L.</style></author><author><style face="normal" font="default" size="100%">de María, A.</style></author><author><style face="normal" font="default" size="100%">Capella-Gutiérrez, S.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, H.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkr408</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">39 Suppl 2</style></volume><pages><style face="normal" font="default" size="100%">W470–W474</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Phylemon 2.0 is a new release of the suite of web tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing. It has been designed as a response to the increasing demand of molecular sequence analyses for experts and non-expert users. Phylemon 2.0 has several unique features that differentiates it from other similar web resources: (i) it offers an integrated environment that enables evolutionary analyses, format conversion, file storage and edition of results; (ii) it suggests further analyses, thereby guiding the users through the web server; and (iii) it allows users to design and save phylogenetic pipelines to be used over multiple genes (phylogenomics). Altogether, Phylemon 2.0 integrates a suite of 30 tools covering sequence alignment reconstruction and trimming; tree reconstruction, visualization and manipulation; and evolutionary hypotheses testing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Olzscha, H.</style></author><author><style face="normal" font="default" size="100%">Schermann, SM.</style></author><author><style face="normal" font="default" size="100%">Woerner, AC.</style></author><author><style face="normal" font="default" size="100%">Pinkert, S.</style></author><author><style face="normal" font="default" size="100%">Hecht, MH.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Hayer-Hartl, M.</style></author><author><style face="normal" font="default" size="100%">Hartl, FU.</style></author><author><style face="normal" font="default" size="100%">Vabulas, RM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Amyloid-like Aggregates Sequester Numerous Metastable Proteins with Essential Cellular Functions.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.cell.2010.11.050</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Protein aggregation is linked with neurodegeneration and numerous other diseases by mechanisms that are not well understood. Here, we have analyzed the gain-of-function toxicity of artificial β sheet proteins that were designed to form amyloid-like fibrils. Using quantitative proteomics, we found that the toxicity of these proteins in human cells correlates with the capacity of their aggregates to promote aberrant protein interactions and to deregulate the cytosolic stress response. The endogenous proteins that are sequestered by the aggregates share distinct physicochemical properties: They are relatively large in size and significantly enriched in predicted unstructured regions, features that are strongly linked with multifunctionality. Many of the interacting proteins occupy essential hub positions in cellular protein networks, with key roles in chromatin organization, transcription, translation, maintenance of cell architecture and protein quality control. We suggest that amyloidogenic aggregation targets a metastable subproteome, thereby causing multifactorial toxicity and, eventually, the collapse of essential cellular functions.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Roetzer, A.</style></author><author><style face="normal" font="default" size="100%">Klopf, E.</style></author><author><style face="normal" font="default" size="100%">Gratz, N.</style></author><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Hiller, E.</style></author><author><style face="normal" font="default" size="100%">Rupp, S.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Kovarik, P.</style></author><author><style face="normal" font="default" size="100%">Schüller, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Regulation of Candida glabrata oxidative stress resistance is adapted to host environment.</style></title><secondary-title><style face="normal" font="default" size="100%">FEBS Lett.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.febslet.2010.12.006</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">585</style></volume><pages><style face="normal" font="default" size="100%">319–327</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['The human fungal pathogen Candida glabrata is related to Saccharomyces cerevisiae but has developed high resistance against reactive oxygen species. We find that induction of conserved genes encoding antioxidant functions is dependent on the transcription factors CgYap1 and CgSkn7 which cooperate for promoter recognition. Superoxide stress resistance of C. glabrata is provided by superoxide dismutase CgSod1, which is not dependent on CgYap1/Skn7. Only double mutants lacking both CgSod1 and CgYap1 were efficiently killed by primary mouse macrophages. Our results suggest that in C. glabrata the regulation of key genes providing stress protection is adopted to meet a host-pathogen situation.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assigning duplication events to relative temporal scales in genome-wide studies.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btq609</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">38–45</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['MOTIVATION: In genome-wide analyses, the relative age of gene duplications is often estimated by measuring the rate of synonymous substitutions (dS) between paralogous sequences. On the other hand, recent studies have shown the feasibility of inferring, at genomic scales, the relative age of duplication events from the topology of gene family trees. This represents a promising alternative for large surveys requiring an automatic methodology to establish a timeline of duplication events and that are usually limited to the use of dS, which presents known limitations such as a fast saturation of the signal. However, both measures have never been compared in a common framework. RESULTS: Topology-based placement of duplications on a relative time scale corresponding to periods between speciation events were found to be highly consistent, providing the same placement for 67-84% of a reliable set of gene pairs duplicated in a single event. For recent evolutionary periods, dS and topological measures showed a strong correlation. We conclude that the topology-based approach is more appropriate for assigning duplications to temporal scales when analyses need to include ancient events, and that the study of recent duplications may benefit from a combination of dS and topology information.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Capella-Gutiérrez, S.</style></author><author><style face="normal" font="default" size="100%">Pryszcz, LP.</style></author><author><style face="normal" font="default" size="100%">Denisov, I.</style></author><author><style face="normal" font="default" size="100%">Kormes, D.</style></author><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PhylomeDB v3.0: an expanding repository of genome-wide collections of trees, alignments and phylogeny-based orthology and paralogy predictions.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkq1109</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">D556–D560</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['The growing availability of complete genomic sequences from diverse species has brought about the need to scale up phylogenomic analyses, including the reconstruction of large collections of phylogenetic trees. Here, we present the third version of PhylomeDB (http://phylomeDB.org), a public database for genome-wide collections of gene phylogenies (phylomes). Currently, PhylomeDB is the largest phylogenetic repository and hosts 17 phylomes, comprising 416,093 trees and 165,840 alignments. It is also a major source for phylogeny-based orthology and paralogy predictions, covering about 5 million proteins in 717 fully-sequenced genomes. For each protein-coding gene in a seed genome, the database provides original and processed alignments, phylogenetic trees derived from various methods and phylogeny-based predictions of orthology and paralogy relationships. The new version of phylomeDB has been extended with novel data access and visualization features, including the possibility of programmatic access. Available seed species include model organisms such as human, yeast, Escherichia coli or Arabidopsis thaliana, but also alternative model species such as the human pathogen Candida albicans, or the pea aphid Acyrtosiphon pisum. Finally, PhylomeDB is currently being used by several genome sequencing projects that couple the genome annotation process with the reconstruction of the corresponding phylome, a strategy that provides relevant evolutionary insights.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">TreeKO: a duplication-aware algorithm for the comparison of phylogenetic trees.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic acids research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkr087</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['Comparisons of tree topologies provide relevant information in evolutionary studies. Most existing methods share the drawback of requiring a complete and exact mapping of terminal nodes between the compared trees. This severely limits the scope of genome-wide analyses, since trees containing duplications are pruned arbitrarily or discarded. To overcome this, we have developed treeKO, an algorithm that enables the comparison of tree topologies, even in the presence of duplication and loss events. To do so treeKO recursively splits gene trees into pruned trees containing only orthologs to subsequently compute a distance based on the combined analyses of all pruned tree comparisons. In addition treeKO, implements the possibility of computing phylome support values, and reconciliation-based measures such as the number of inferred duplication and loss events.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kemena, C.</style></author><author><style face="normal" font="default" size="100%">Taly, JF.</style></author><author><style face="normal" font="default" size="100%">Kleinjung, J.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">STRIKE: evaluation of protein MSAs using a single 3D structure.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btr587</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">24</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">3385–3391</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Evaluating alternative multiple protein sequence alignments is an important unsolved problem in Biology. The most accurate way of doing this is to use structural information. Unfortunately, most methods require at least two structures to be embedded in the alignment, a condition rarely met when dealing with standard datasets.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">ENCODE Project Consortium</style></author><author><style face="normal" font="default" size="100%">Myers, RM.</style></author><author><style face="normal" font="default" size="100%">Stamatoyannopoulos, J.</style></author><author><style face="normal" font="default" size="100%">Snyder, M.</style></author><author><style face="normal" font="default" size="100%">Dunham, I.</style></author><author><style face="normal" font="default" size="100%">Hardison, RC.</style></author><author><style face="normal" font="default" size="100%">Bernstein, BE.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Kent, WJ.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Wold, B.</style></author><author><style face="normal" font="default" size="100%">Crawford, GE.</style></author><author><style face="normal" font="default" size="100%">Djebali, S.</style></author><author><style face="normal" font="default" size="100%">Merkel, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A user's guide to the encyclopedia of DNA elements (ENCODE).</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pbio.1001046</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">e1001046</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Derrien, T.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">[Long non-coding RNAs with enhancerlike function in human cells.]</style></title><secondary-title><style face="normal" font="default" size="100%">Medecine sciences : M/S</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1051/medsci/2011274009</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">359–361</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Orom, UA.</style></author><author><style face="normal" font="default" size="100%">Derrien, T.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Shiekhattar, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Long Noncoding RNAs as Enhancers of Gene Expression</style></title><secondary-title><style face="normal" font="default" size="100%">Cold Spring Harbor symposia on quantitative biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/sqb.2010.75.058</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">['The human genome contains thousands of long noncoding RNAs (ncRNAs) transcribed from diverse genomic locations. A large set of long ncRNAs is transcribed independent of protein-coding genes. We have used the GENCODE annotation of the human genome to identify 3019 long ncRNAs expressed in various human cell lines and tissue. This set of long ncRNAs responds to differentiation signals in primary human keratinocytes and is coexpressed with important regulators of keratinocyte development. Depletion of a number of these long ncRNAs leads to the repression of specific genes in their surrounding locus, supportive of an activating function for ncRNAs. Using reporter assays, we confirmed such activating function and show that such transcriptional enhancement is mediated through the long ncRNA transcripts. Our studies show that long ncRNAs exhibit functions similar to classically defined enhancers, through an RNA-dependent mechanism.']</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">ENCODE Project Consortium</style></author><author><style face="normal" font="default" size="100%">Myers, RM.</style></author><author><style face="normal" font="default" size="100%">Stamatoyannopoulos, J.</style></author><author><style face="normal" font="default" size="100%">Snyder, M.</style></author><author><style face="normal" font="default" size="100%">Dunham, I.</style></author><author><style face="normal" font="default" size="100%">Hardison, RC.</style></author><author><style face="normal" font="default" size="100%">Bernstein, BE.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Kent, WJ.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Wold, B.</style></author><author><style face="normal" font="default" size="100%">Crawford, GE.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A user's guide to the encyclopedia of DNA elements (ENCODE).</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pbio.1001046</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">e1001046</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evidence for short-time divergence and long-time conservation of tissue-specific expression after gene duplication.</style></title><secondary-title><style face="normal" font="default" size="100%">Briefings in bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bib/bbr022</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Gene duplication is one of the main mechanisms by which genomes can acquire novel functions. It has been proposed that the retention of gene duplicates can be associated to processes of tissue expression divergence. These models predict that acquisition of divergent expression patterns should be acquired shortly after the duplication, and that larger divergence in tissue expression would be expected for paralogs, as compared to orthologs of a similar age. Many studies have shown that gene duplicates tend to have divergent expression patterns and that gene family expansions are associated with high levels of tissue specificity. However, the timeframe in which these processes occur have rarely been investigated in detail, particularly in vertebrates, and most analyses do not include direct comparisons of orthologs as a baseline for the expected levels of tissue specificity in absence of duplications. To assess the specific contribution of duplications to expression divergence, we combine here phylogenetic analyses and expression data from human and mouse. In particular, we study differences in spatial expression among human-mouse paralogs, specifically duplicated after the radiation of mammals, and compare them to pairs of orthologs in the same species. Our results show that gene duplication leads to increased levels of tissue specificity and that this tends to occur promptly after the duplication event.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Neurohr, G.</style></author><author><style face="normal" font="default" size="100%">Naegeli, A.</style></author><author><style face="normal" font="default" size="100%">Titos, I.</style></author><author><style face="normal" font="default" size="100%">Theler, D.</style></author><author><style face="normal" font="default" size="100%">Greber, B.</style></author><author><style face="normal" font="default" size="100%">Díez, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Mendoza, M.</style></author><author><style face="normal" font="default" size="100%">Barral, Y.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A midzone-based ruler adjusts chromosome compaction to anaphase spindle length.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1126/science.1201578</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6028</style></number><volume><style face="normal" font="default" size="100%">332</style></volume><pages><style face="normal" font="default" size="100%">465–468</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Partitioning of chromatids during mitosis requires that chromosome compaction and spindle length scale appropriately with each other. However, it is not clear whether chromosome condensation and spindle elongation are linked. Here, we find that yeast cells could cope with a 45% increase in the length of their longest chromosome arm by increasing its condensation. The spindle midzone, aurora/Ipl1 activity, and Ser10 of histone H3 mediated this response. Thus, the anaphase spindle may function as a ruler to adapt the condensation of chromatids, promoting their segregation regardless of chromosome or spindle length.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Agostini, F.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, G. G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sequence-based prediction of protein solubility</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Molecular Biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lin, HN.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Chang, JM.</style></author><author><style face="normal" font="default" size="100%">Sung, TY.</style></author><author><style face="normal" font="default" size="100%">Hsu, WL.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Improving the alignment quality of consistency based aligners with an evaluation function using synonymous protein words.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pone.0027872</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e27872</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Most sequence alignment tools can successfully align protein sequences with higher levels of sequence identity. The accuracy of corresponding structure alignment, however, decreases rapidly when considering distantly related sequences (&lt;20% identity). In this range of identity, alignments optimized so as to maximize sequence similarity are often inaccurate from a structural point of view. Over the last two decades, most multiple protein aligners have been optimized for their capacity to reproduce structure-based alignments while using sequence information. Methods currently available differ essentially in the similarity measurement between aligned residues using substitution matrices, Fourier transform, sophisticated profile-profile functions, or consistency-based approaches, more recently.In this paper, we present a flexible similarity measure for residue pairs to improve the quality of protein sequence alignment. Our approach, called SymAlign, relies on the identification of conserved words found across a sizeable fraction of the considered dataset, and supported by evolutionary analysis. These words are then used to define a position specific substitution matrix that better reflects the biological significance of local similarity. The experiment results show that the SymAlign scoring scheme can be incorporated within T-Coffee to improve sequence alignment accuracy. We also demonstrate that SymAlign is less sensitive to the presence of structurally non-similar proteins. In the analysis of the relationship between sequence identity and structure similarity, SymAlign can better differentiate structurally similar proteins from non- similar proteins. We show that protein sequence alignments can be significantly improved using a similarity estimation based on weighted n-grams. In our analysis of the alignments thus produced, sequence conservation becomes a better indicator of structural similarity. SymAlign also provides alignment visualization that can display sub-optimal alignments on dot-matrices. The visualization makes it easy to identify well-supported alternative alignments that may not have been identified by dynamic programming. SymAlign is available at http://bio-cluster.iis.sinica.edu.tw/SymAlign/.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Esteve-Codina, A.</style></author><author><style face="normal" font="default" size="100%">Kofler, R.</style></author><author><style face="normal" font="default" size="100%">Palmieri, N.</style></author><author><style face="normal" font="default" size="100%">Bussotti, G.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Pérez-Enciso, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring the gonad transcriptome of two extreme male pigs with RNA-seq.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Genomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2164-12-552</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">552</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Although RNA-seq greatly advances our understanding of complex transcriptome landscapes, such as those found in mammals, complete RNA-seq studies in livestock and in particular in the pig are still lacking. Here, we used high-throughput RNA sequencing to gain insight into the characterization of the poly-A RNA fraction expressed in pig male gonads. An expression analysis comparing different mapping approaches and detection of allele specific expression is also discussed in this study.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erb, I.</style></author><author><style face="normal" font="default" size="100%">van Nimwegen, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcription Factor Binding Site Positioning in Yeast: Proximal Promoter Motifs Characterize TATA-Less Promoters</style></title><secondary-title><style face="normal" font="default" size="100%">PloS one</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><number><style face="normal" font="default" size="100%">9</style></number><publisher><style face="normal" font="default" size="100%">Public Library of Science</style></publisher><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e24279</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jahn, TR.</style></author><author><style face="normal" font="default" size="100%">Kohloff, KJ.</style></author><author><style face="normal" font="default" size="100%">Scott, M.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Lomas, DA.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Crowther, DC.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detection of Early Locomotor Abnormalities in a Drosophila Model of Alzheimer's Disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Neuroscience Methods</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Raimondi, S.</style></author><author><style face="normal" font="default" size="100%">Guglielmi, F.</style></author><author><style face="normal" font="default" size="100%">Giorgetti, S.</style></author><author><style face="normal" font="default" size="100%">Di Gaetano, S.</style></author><author><style face="normal" font="default" size="100%">Arciello, A.</style></author><author><style face="normal" font="default" size="100%">Monti, M.</style></author><author><style face="normal" font="default" size="100%">Relini, A.</style></author><author><style face="normal" font="default" size="100%">Nichino, D.</style></author><author><style face="normal" font="default" size="100%">Doglia, AM.</style></author><author><style face="normal" font="default" size="100%">Natalello, A.</style></author><author><style face="normal" font="default" size="100%">Pucci, P.</style></author><author><style face="normal" font="default" size="100%">Mangione, P.</style></author><author><style face="normal" font="default" size="100%">Obici, L.</style></author><author><style face="normal" font="default" size="100%">Merlini, G.</style></author><author><style face="normal" font="default" size="100%">Stoppini, M.</style></author><author><style face="normal" font="default" size="100%">Robustelli, P.</style></author><author><style face="normal" font="default" size="100%">Tartaglia GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Piccoli, R.</style></author><author><style face="normal" font="default" size="100%">Bellotti, V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effects of the known pathogenic mutations on the aggregation pathway of the amyloidogenic peptide of Apolipoprotein A-I</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mossuto, M. F.</style></author><author><style face="normal" font="default" size="100%">Bolognesi, B.</style></author><author><style face="normal" font="default" size="100%">Guixer, B.</style></author><author><style face="normal" font="default" size="100%">Dhulesia, A.</style></author><author><style face="normal" font="default" size="100%">Agostini, F.</style></author><author><style face="normal" font="default" size="100%">Janet, R.</style></author><author><style face="normal" font="default" size="100%">Kumita, J. R.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, G. G.</style></author><author><style face="normal" font="default" size="100%">Dumoulin, M.</style></author><author><style face="normal" font="default" size="100%">Dobson, C. M.</style></author><author><style face="normal" font="default" size="100%">Salvatella X.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Disulfide bonds reduce the toxicity of the amyloid fibrils formed by an extracellular protein</style></title><secondary-title><style face="normal" font="default" size="100%">Angew Chem Intl Ed</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vellozo, AF.</style></author><author><style face="normal" font="default" size="100%">Véron, AS.</style></author><author><style face="normal" font="default" size="100%">Baa-Puyoulet, P.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Cottret, L.</style></author><author><style face="normal" font="default" size="100%">Febvay, G.</style></author><author><style face="normal" font="default" size="100%">Calevro, F.</style></author><author><style face="normal" font="default" size="100%">Rahbé, Y.</style></author><author><style face="normal" font="default" size="100%">Douglas, AE.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Sagot, MF.</style></author><author><style face="normal" font="default" size="100%">Charles, H.</style></author><author><style face="normal" font="default" size="100%">Colella, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CycADS: an annotation database system to ease the development and update of BioCyc databases.</style></title><secondary-title><style face="normal" font="default" size="100%">Database (Oxford)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/database/bar008</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">2011</style></volume><pages><style face="normal" font="default" size="100%">bar008</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http://www.cycadsys.org.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rius, J.</style></author><author><style face="normal" font="default" size="100%">Cores, F.</style></author><author><style face="normal" font="default" size="100%">Solsona, F.</style></author><author><style face="normal" font="default" size="100%">van Hemert, JI.</style></author><author><style face="normal" font="default" size="100%">Koetsier, J.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A user-friendly web portal for T-Coffee on supercomputers.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2105-12-150</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">150</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT:</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nguyen, KD.</style></author><author><style face="normal" font="default" size="100%">Pan, Y.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiple sequence alignment based on dynamic weighted guidance tree.</style></title><secondary-title><style face="normal" font="default" size="100%">Int J Bioinform Res Appl</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/21576075</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">168–182</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Aligning multiple DNA/RNA/protein sequences to identify common functionalities, structures, or relationships between species is a fundamental task in bioinformatics. In this study, we propose a new multiple sequence strategy that extracts sequence information, sequence global and local similarities to provide different weights for each input sequence. A weighted pair-wise distance matrix is calculated from these sequences to build a dynamic alignment guiding tree. The tree can reorder its higher-level branches based on corresponding alignment results from lower tree levels to guarantee the highest alignment scores at each level of the tree. This technique improves the alignment accuracy up to 10% on many benchmarks tested against alignment tools such as CLUSTALW (Thompson et al., 1994), DIALIGN (Morgenstern, 1999), T-COFFEE (Notredame et al., 2000), MUSCLE (Edgar, 2004), and PROBCONS (Do et al., 2005) of the multiple sequence alignment.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mariotti, M.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selenoprofiles: profile-based scanning of eukaryotic genome sequences for selenoprotein genes</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics (Oxford, England)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btq516</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: Selenoproteins are a group of proteins that contain selenocysteine (Sec), a rare amino acid inserted co-translationally into the protein chain. The Sec codon is UGA, which is normally a stop codon. In selenoproteins UGA is recoded to Sec in presence of specific features on selenoprotein gene transcripts. Due to the dual role of the UGA codon, selenoprotein prediction and annotation are difficult tasks, and even known selenoproteins are often misannotated in genome databases. RESULTS: We present an homology-based in silico method to scan genomes for members of the known eukaryotic selenoprotein families: selenoprofiles. The core of the method is a set of manually curated highly reliable multiple sequence alignments of selenoprotein families, which are used as queries to scan genomic sequences. Results of the scan are processed through a number of steps, to produce highly accurate predictions of selenoprotein genes with little or no human intervention. Selenoprofiles is a valuable tool for bioinformatic characterization of eukaryotic selenoproteomes, and can complement genome annotation pipelines. Availability and Implementation: Selenoprofiles is a python-built pipeline that internally runs psitblastn, exonerate, genewise, SECISearch, and a number of custom made scripts and programs. The program is available at http://big.crg.cat/services/selenoprofiles. The predictions presented in this paper are available through DAS at http://genome.crg.cat:9000/das/Selenoprofiles_ensembl. CONTACT: marco.mariotti@crg.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Benítez-Páez, A.</style></author><author><style face="normal" font="default" size="100%">Villarroya, M.</style></author><author><style face="normal" font="default" size="100%">Douthwaite, S.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Armengod, ME.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">YibK is the 2'-O-methyltransferase TrmL that modifies the wobble nucleotide in Escherichia coli tRNALeu isoacceptors.</style></title><secondary-title><style face="normal" font="default" size="100%">RNA (New York, N.Y.)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1261/rna.2245910</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Transfer RNAs are the most densely modified nucleic acid molecules in living cells. In Escherichia coli, more than 30 nucleoside modifications have been characterized, ranging from methylations and pseudouridylations to more complex additions that require multiple enzymatic steps. Most of the modifying enzymes have been identified, although a few notable exceptions include the 2'-O-methyltransferase(s) that methylate the ribose at the nucleotide 34 wobble position in the two leucyl isoacceptors tRNA(Leu) (CmAA) and tRNA(Leu) (cmnm5UmAA). Here, we have used a comparative genomics approach to uncover candidate E. coli genes for the missing enzyme(s). Transfer RNAs from null mutants for candidate genes were analyzed by mass spectrometry and revealed that inactivation of yibK leads to loss of 2'-O-methylation at position 34 in both tRNA(Leu) (CmAA) and tRNA(Leu) (cmnm5UmAA). Loss of YibK methylation reduces the efficiency of codon-wobble base interaction, as demonstrated in an amber suppressor supP system. Inactivation of yibK had no detectable effect on steady-state growth rate, although a distinct disadvantage was noted in multiple-round, mixed-population growth experiments, suggesting that the ability to recover from the stationary phase was impaired. Methylation is restored in vivo by complementing with a recombinant copy of yibK. Despite being one of the smallest characterized α/β knot proteins, YibK independently catalyzes the methyl transfer from S-adenosyl-L-methionine to the 2'-OH of the wobble nucleotide; YibK recognition of this target requires a pyridine at position 34 and N(6) -(isopentenyl)-2-methylthioadenosine at position 37. YibK is one of the last remaining E. coli tRNA modification enzymes to be identified and is now renamed TrmL.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Orom, UA.</style></author><author><style face="normal" font="default" size="100%">Derrien, T.</style></author><author><style face="normal" font="default" size="100%">Beringer, M.</style></author><author><style face="normal" font="default" size="100%">Gumireddy, K.</style></author><author><style face="normal" font="default" size="100%">Gardini, A.</style></author><author><style face="normal" font="default" size="100%">Bussotti, G.</style></author><author><style face="normal" font="default" size="100%">Lai, F.</style></author><author><style face="normal" font="default" size="100%">Zytnicki, M.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Huang, Q.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Shiekhattar, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Long Noncoding RNAs with Enhancer-like Function in Human Cells</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.cell.2010.09.001</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">143</style></volume><pages><style face="normal" font="default" size="100%">46–58</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">While the long noncoding RNAs (ncRNAs) constitute a large portion of the mammalian transcriptome, their biological functions has remained elusive. A few long ncRNAs that have been studied in any detail silence gene expression in processes such as X-inactivation and imprinting. We used a GENCODE annotation of the human genome to characterize over a thousand long ncRNAs that are expressed in multiple cell lines. Unexpectedly, we found an enhancer-like function for a set of these long ncRNAs in human cell lines. Depletion of a number of ncRNAs led to decreased expression of their neighboring protein-coding genes, including the master regulator of hematopoiesis, SCL (also called TAL1), Snai1 and Snai2. Using heterologous transcription assays we demonstrated a requirement for the ncRNAs in activation of gene expression. These results reveal an unanticipated role for a class of long ncRNAs in activation of critical regulators of development and differentiation. PAPERCLIP:</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arensburger, P.</style></author><author><style face="normal" font="default" size="100%">Megy, K.</style></author><author><style face="normal" font="default" size="100%">Waterhouse, RM.</style></author><author><style face="normal" font="default" size="100%">Abrudan, J.</style></author><author><style face="normal" font="default" size="100%">Amedeo, P.</style></author><author><style face="normal" font="default" size="100%">Antelo, B.</style></author><author><style face="normal" font="default" size="100%">Bartholomay, L.</style></author><author><style face="normal" font="default" size="100%">Bidwell, S.</style></author><author><style face="normal" font="default" size="100%">Caler, E.</style></author><author><style face="normal" font="default" size="100%">Câmara, F.</style></author><author><style face="normal" font="default" size="100%">Campbell, CL.</style></author><author><style face="normal" font="default" size="100%">Campbell, KS.</style></author><author><style face="normal" font="default" size="100%">Casola, C.</style></author><author><style face="normal" font="default" size="100%">Castro, MT.</style></author><author><style face="normal" font="default" size="100%">Chandramouliswaran, I.</style></author><author><style face="normal" font="default" size="100%">Chapman, SB.</style></author><author><style face="normal" font="default" size="100%">Christley, S.</style></author><author><style face="normal" font="default" size="100%">Costas, J.</style></author><author><style face="normal" font="default" size="100%">Eisenstadt, E.</style></author><author><style face="normal" font="default" size="100%">Feschotte, C.</style></author><author><style face="normal" font="default" size="100%">Fraser-Liggett, C.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Haas, B.</style></author><author><style face="normal" font="default" size="100%">Hammond, M.</style></author><author><style face="normal" font="default" size="100%">Hansson, BS.</style></author><author><style face="normal" font="default" size="100%">Hemingway, J.</style></author><author><style face="normal" font="default" size="100%">Hill, SR.</style></author><author><style face="normal" font="default" size="100%">Howarth, C.</style></author><author><style face="normal" font="default" size="100%">Ignell, R.</style></author><author><style face="normal" font="default" size="100%">Kennedy, RC.</style></author><author><style face="normal" font="default" size="100%">Kodira, CD.</style></author><author><style face="normal" font="default" size="100%">Lobo, NF.</style></author><author><style face="normal" font="default" size="100%">Mao, C.</style></author><author><style face="normal" font="default" size="100%">Mayhew, G.</style></author><author><style face="normal" font="default" size="100%">Michel, K.</style></author><author><style face="normal" font="default" size="100%">Mori, A.</style></author><author><style face="normal" font="default" size="100%">Liu, N.</style></author><author><style face="normal" font="default" size="100%">Naveira, H.</style></author><author><style face="normal" font="default" size="100%">Nene, V.</style></author><author><style face="normal" font="default" size="100%">Nguyen, N.</style></author><author><style face="normal" font="default" size="100%">Pearson, MD.</style></author><author><style face="normal" font="default" size="100%">Pritham, EJ.</style></author><author><style face="normal" font="default" size="100%">Puiu, D.</style></author><author><style face="normal" font="default" size="100%">Qi, Y.</style></author><author><style face="normal" font="default" size="100%">Ranson, H.</style></author><author><style face="normal" font="default" size="100%">Ribeiro, JM.</style></author><author><style face="normal" font="default" size="100%">Roberston, HM.</style></author><author><style face="normal" font="default" size="100%">Severson, DW.</style></author><author><style face="normal" font="default" size="100%">Shumway, M.</style></author><author><style face="normal" font="default" size="100%">Stanke, M.</style></author><author><style face="normal" font="default" size="100%">Strausberg, RL.</style></author><author><style face="normal" font="default" size="100%">Sun, C.</style></author><author><style face="normal" font="default" size="100%">Sutton, G.</style></author><author><style face="normal" font="default" size="100%">Tu, ZJ.</style></author><author><style face="normal" font="default" size="100%">Tubio, JM.</style></author><author><style face="normal" font="default" size="100%">Unger, MF.</style></author><author><style face="normal" font="default" size="100%">Vanlandingham, DL.</style></author><author><style face="normal" font="default" size="100%">Vilella, AJ.</style></author><author><style face="normal" font="default" size="100%">White, O.</style></author><author><style face="normal" font="default" size="100%">White, JR.</style></author><author><style face="normal" font="default" size="100%">Wondji, CS.</style></author><author><style face="normal" font="default" size="100%">Wortman, J.</style></author><author><style face="normal" font="default" size="100%">Zdobnov, EM.</style></author><author><style face="normal" font="default" size="100%">Birren, B.</style></author><author><style face="normal" font="default" size="100%">Christensen, BM.</style></author><author><style face="normal" font="default" size="100%">Collins, FH.</style></author><author><style face="normal" font="default" size="100%">Cornel, A.</style></author><author><style face="normal" font="default" size="100%">Dimopoulos, G.</style></author><author><style face="normal" font="default" size="100%">Hannick, LI.</style></author><author><style face="normal" font="default" size="100%">Higgs, S.</style></author><author><style face="normal" font="default" size="100%">Lanzaro, GC.</style></author><author><style face="normal" font="default" size="100%">Lawson, D.</style></author><author><style face="normal" font="default" size="100%">Lee, NH.</style></author><author><style face="normal" font="default" size="100%">Muskavitch, MA.</style></author><author><style face="normal" font="default" size="100%">Raikhel, AS.</style></author><author><style face="normal" font="default" size="100%">Atkinson, PW.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sequencing of Culex quinquefasciatus establishes a platform for mosquito comparative genomics.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1126/science.1191864</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6000</style></number><volume><style face="normal" font="default" size="100%">330</style></volume><pages><style face="normal" font="default" size="100%">86–88</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Culex quinquefasciatus (the southern house mosquito) is an important mosquito vector of viruses such as West Nile virus and St. Louis encephalitis virus, as well as of nematodes that cause lymphatic filariasis. C. quinquefasciatus is one species within the Culex pipiens species complex and can be found throughout tropical and temperate climates of the world. The ability of C. quinquefasciatus to take blood meals from birds, livestock, and humans contributes to its ability to vector pathogens between species. Here, we describe the genomic sequence of C. quinquefasciatus: Its repertoire of 18,883 protein-coding genes is 22% larger than that of Aedes aegypti and 52% larger than that of Anopheles gambiae with multiple gene-family expansions, including olfactory and gustatory receptors, salivary gland genes, and genes associated with xenobiotic detoxification</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lee, Y.</style></author><author><style face="normal" font="default" size="100%">Zhou, T.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Wilke, CO.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Translationally optimal codons associate with aggregation-prone sites in proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Proteomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/pmic.201000229</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We analyze the relationship between codon usage bias and residue aggregation propensity in the genomes of four model organisms, Escherichia coli, yeast, fly, and mouse, as well as the archaeon Halobacterium species NRC-1. Using the Mantel-Haenszel procedure, we find that translationally optimal codons associate with aggregation-prone residues. Our results are qualitatively and quantitatively similar to those of an earlier study where we found an association between translationally optimal codons and buried residues. We also combine the aggregation-propensity data with solvent-accessibility data. Although the resulting data set is small, and hence statistical power low, results indicate that the association between optimal codons and aggregation-prone residues exists both at buried and at exposed sites. By comparing codon usage at different combinations of sites (exposed, aggregation-prone sites versus buried, non-aggregation-prone sites; buried, aggregation-prone sites versus exposed, non-aggregation-prone sites), we find that aggregation propensity and solvent accessibility seem to have independent effects of (on average) comparable magnitude on codon usage. Finally, in fly, we assess whether optimal codons associate with sites at which amino acid substitutions lead to an increase in aggregation propensity, and find only a very weak effect. These results suggest that optimal codons may be required to reduce the frequency of translation errors at aggregation-prone sites that coincide with certain functional sites, such as protein-protein interfaces. Alternatively, optimal codons may be required for rapid translation of aggregation-prone regions.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Proteome-level interplay between folding and aggregation propensities of proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2010.08.013</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">402</style></volume><pages><style face="normal" font="default" size="100%">919–928</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">With the advent of proteomics, there is an increasing need of tools for predicting the properties of large numbers of proteins by using the information provided by their amino acid sequences, even in the absence of the knowledge of their structures. One of the most important types of predictions concerns whether proteins will fold or aggregate. Here, we study the competition between these two processes by analyzing the relationship between the folding and aggregation propensity profiles for the human and Escherichia coli proteomes. These profiles are calculated, respectively, using the CamFold method, which we introduce in this work, and the Zyggregator method. Our results indicate that the kinetic behavior of proteins is, to a large extent, determined by the interplay between regions of low folding and high aggregation propensities.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nikolaou, C.</style></author><author><style face="normal" font="default" size="100%">Althammer, S.</style></author><author><style face="normal" font="default" size="100%">Beato, M.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Structural constraints revealed in consistent nucleosome positions in the genome of S. cerevisiae</style></title><secondary-title><style face="normal" font="default" size="100%">Epigenetics &amp; chromatin</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1756-8935-3-20</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">20</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: BACKGROUND: Recent advances in the field of high-throughput genomics have rendered possible the performance of genome-scale studies to define the nucleosomal landscapes of eukaryote genomes. Such analyses aim towards providing a better understanding of the process of nucleosome positioning, for which a number of models have been suggested. Nevertheless, questions regarding the sequence constraints of nucleosomal DNA and how they may have been shaped through evolution remain open. Here we analyze in detail different experimental nucleosome datasets with the aim of providing a hypothesis for the emergence of nucleosome-forming sequences. RESULTS: We have compared the complete sets of nucleosome positions for the budding yeast (S. cerevisiae) as defined in the output of two independent experiments with the use of two different experimental techniques. We found that less than 10% of the experimentally defined nucleosome positions were consistently positioned in both datasets. This subset of well-positioned nucleosomes, when compared to the bulk, was shown to have particular properties at both sequence and structural levels. Consistently positioned nucleosomes were also shown to occur preferentially in pairs of di-nucleosomes and to be surprisingly less conserved when compared to their adjacent nucleosome-free linkers. CONCLUSION: Our findings may be combined into a hypothesis for the emergence of a weak nucleosome-positioning code. According to this hypothesis, consistent nucleosomes may be partly guided by nearby nucleosome-free regions through statistical positioning. Once established, a set of well-positioned consistent nucleosomes may impose secondary constraints which further shape the structure of the underlying DNA. We are able to capture these constraints through the application of a recently introduced structural property that is related to the symmetry of DNA curvature. Furthermore we show that both consistently-positioned nucleosomes and their adjacent nucleosome-free regions show an increased tendency for the conservation of this structural feature.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Szczepankiewicz, O.</style></author><author><style face="normal" font="default" size="100%">Cabaleiro-Lago, C.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Hunter, T.</style></author><author><style face="normal" font="default" size="100%">Hunter, GJ.</style></author><author><style face="normal" font="default" size="100%">Nilsson, H.</style></author><author><style face="normal" font="default" size="100%">Thulin, E.</style></author><author><style face="normal" font="default" size="100%">Linse, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interactions in the native state of monellin, which play a protective role against aggregation.</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular bioSystems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1039/c0mb00155d</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A series of recent studies have provided initial evidence about the role of specific intra-molecular interactions in maintaining proteins in their soluble state and in protecting them from aggregation. Here we show that the amino acid sequence of the protein monellin contains two aggregation-prone regions that are prevented from initiating aggregation by multiple non-covalent interactions that favor their burial within the folded state of the protein. By investigating the behavior of single-chain monellin and a series of five of its mutational variants using a variety of biochemical, biophysical and computational techniques, we found that weakening of the non-covalent interaction that stabilizes the native state of the protein leads to an enhanced aggregation propensity. The lag time for fibrillation was found to correlate with the apparent midpoint of thermal denaturation for the series of mutational variants, thus showing that a reduced thermal stability is associated with an increased aggregation tendency. We rationalize these findings by showing that the increase in the aggregation propensity upon mutation can be predicted in a quantitative manner through the increase in the exposure to solvent of the amyloidogenic regions of the sequence caused by the destabilization of the native state. Our findings, which are further discussed in terms of the structure of monellin and the perturbation by the amino acid substitutions of the contact surface between the two subdomains that compose the folded state of monellin, provide a detailed description of the specific intra-molecular interactions that prevent aggregation by stabilizing the native state of a protein.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Díez, J.</style></author><author><style face="normal" font="default" size="100%">Walter, D.</style></author><author><style face="normal" font="default" size="100%">Muñoz-Pinedo, C.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DeathBase: a database on structure, evolution and function of proteins involved in apoptosis and other forms of cell death.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell Death Differ.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/cdd.2009.215</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">735–736</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computing multiple sequence/structure alignments with the T-coffee package.</style></title><secondary-title><style face="normal" font="default" size="100%">Curr Protoc Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/0471250953.bi0308s29</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">Chapter 3</style></volume><pages><style face="normal" font="default" size="100%">Unit 3.8.1–Unit 3.825</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this unit, we describe assembly of a multiple sequence alignment using the T-Coffee package. T-Coffee is much more flexible than most related methods (e.g., ClustalW) because it makes it possible to combine many alternative alignments into a single one, based on an estimate of consistency between these alignments. This strategy can be especially useful when one has to decide among the output produced by several alternative methods.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Peroxisome diversity and evolution.</style></title><secondary-title><style face="normal" font="default" size="100%">Philos. Trans. R. Soc. Lond., B, Biol. Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1098/rstb.2009.0240</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1541</style></number><volume><style face="normal" font="default" size="100%">365</style></volume><pages><style face="normal" font="default" size="100%">765–773</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Peroxisomes are organelles bounded by a single membrane that can be found in all major groups of eukaryotes. A single evolutionary origin of this cellular compartment is supported by the presence, in diverse organisms, of a common set of proteins implicated in peroxisome biogenesis and maintenance. Their enzymatic content, however, can vary substantially across species, indicating a high level of evolutionary plasticity. Proteomic analyses have greatly expanded our knowledge on peroxisomes in some model organisms, including plants, mammals and yeasts. However, we still have a limited knowledge about the distribution and functionalities of peroxisomes in the vast majority of groups of microbial eukaryotes. Here, I review recent advances in our understanding of peroxisome diversity and evolution, with a special emphasis on peroxisomes in microbial eukaryotes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Horner, DS.</style></author><author><style face="normal" font="default" size="100%">Pavesi, G.</style></author><author><style face="normal" font="default" size="100%">Castrignanò, T.</style></author><author><style face="normal" font="default" size="100%">De Meo, PD.</style></author><author><style face="normal" font="default" size="100%">Liuni, S.</style></author><author><style face="normal" font="default" size="100%">Sammeth, M.</style></author><author><style face="normal" font="default" size="100%">Picardi, E.</style></author><author><style face="normal" font="default" size="100%">Pesole, G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bioinformatics approaches for genomics and post genomics applications of next-generation sequencing</style></title><secondary-title><style face="normal" font="default" size="100%">Brief. Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bib/bbp046</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">181–197</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Technical advances such as the development of molecular cloning, Sanger sequencing, PCR and oligonucleotide microarrays are key to our current capacity to sequence, annotate and study complete organismal genomes. Recent years have seen the development of a variety of so-called 'next-generation' sequencing platforms, with several others anticipated to become available shortly. The previously unimaginable scale and economy of these methods, coupled with their enthusiastic uptake by the scientific community and the potential for further improvements in accuracy and read length, suggest that these technologies are destined to make a huge and ongoing impact upon genomic and post-genomic biology. However, like the analysis of microarray data and the assembly and annotation of complete genome sequences from conventional sequencing data, the management and analysis of next-generation sequencing data requires (and indeed has already driven) the development of informatics tools able to assemble, map, and interpret huge quantities of relatively or extremely short nucleotide sequence data. Here we provide a broad overview of bioinformatics approaches that have been introduced for several genomics and functional genomics applications of next-generation sequencing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gómez-Baldó, L.</style></author><author><style face="normal" font="default" size="100%">Schmidt, S.</style></author><author><style face="normal" font="default" size="100%">Maxwell, CA.</style></author><author><style face="normal" font="default" size="100%">Bonifaci, N.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Vidalain, PO.</style></author><author><style face="normal" font="default" size="100%">Senapedis, W.</style></author><author><style face="normal" font="default" size="100%">Kletke, A.</style></author><author><style face="normal" font="default" size="100%">Rosing, M.</style></author><author><style face="normal" font="default" size="100%">Barnekow, A.</style></author><author><style face="normal" font="default" size="100%">Rottapel, R.</style></author><author><style face="normal" font="default" size="100%">Capellá, G.</style></author><author><style face="normal" font="default" size="100%">Vidal, M.</style></author><author><style face="normal" font="default" size="100%">Astrinidis, A.</style></author><author><style face="normal" font="default" size="100%">Piekorz, RP.</style></author><author><style face="normal" font="default" size="100%">Pujana, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">TACC3-TSC2 maintains nuclear envelope structure and controls cell division.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell cycle </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/20237422</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Studies of the role of tuberous sclerosis complex (TSC) proteins (TSC1/TSC2) in pathology have focused mainly on their capacity to regulate translation and cell growth, but their relationship with alterations of cellular structures and the cell cycle is not yet fully understood. The transforming acidic coiled-coil (TACC) domain-containing proteins are central players in structures and processes connected to the centrosome. Here, TACC3 interactome mapping identified TSC2 and 15 other physical interactors, including the evolutionary conserved interactions with ch-TOG/CKAP5 and FAM161B. TACC3 and TSC2 co-localize and co-purify with components of the nuclear envelope, and their deficiency causes morphological alterations of this structure. During cell division, TACC3 is necessary for the proper localization of phospho-Ser939 TSC2 at spindle poles and cytokinetic bridges. Accordingly, abscission alterations and increased frequency of binucleated cells were observed in Tacc3- and Tsc2-deficient cells relative to controls. In regulating cell division, TSC2 acts epistatically to TACC3 and, in addition to canonical TSC/mTOR signaling and cytokinetic associations, converges to the early mitotic checkpoint mediated by CHFR, consistently with nuclear envelope associations. Our findings link TACC3 to novel structural and cell division functions of TSC2, which may provide additional explanations for the clinical and pathological manifestations of lymphangioleiomyomatosis (LAM) disease and TSC syndrome, including the greater clinical severity of TSC2 mutations compared to TSC1 mutations.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Meer, M. V.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, A. S.</style></author><author><style face="normal" font="default" size="100%">Artzy-Randrup, Y.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Compensatory evolution in mitochondrial tRNAs navigates valleys of low fitness</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">464</style></volume><pages><style face="normal" font="default" size="100%">279–282</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stajich, JE.</style></author><author><style face="normal" font="default" size="100%">Wilke, SK.</style></author><author><style face="normal" font="default" size="100%">Ahrén, D.</style></author><author><style face="normal" font="default" size="100%">Au, CH.</style></author><author><style face="normal" font="default" size="100%">Birren, BW.</style></author><author><style face="normal" font="default" size="100%">Borodovsky, M.</style></author><author><style face="normal" font="default" size="100%">Burns, C.</style></author><author><style face="normal" font="default" size="100%">Canbäck, B.</style></author><author><style face="normal" font="default" size="100%">Casselton, LA.</style></author><author><style face="normal" font="default" size="100%">Cheng, CK.</style></author><author><style face="normal" font="default" size="100%">Deng, J.</style></author><author><style face="normal" font="default" size="100%">Dietrich, FS.</style></author><author><style face="normal" font="default" size="100%">Fargo, DC.</style></author><author><style face="normal" font="default" size="100%">Farman, ML.</style></author><author><style face="normal" font="default" size="100%">Gathman, AC.</style></author><author><style face="normal" font="default" size="100%">Goldberg, J.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Hoegger, PJ.</style></author><author><style face="normal" font="default" size="100%">Hooker, JB.</style></author><author><style face="normal" font="default" size="100%">Huggins, A.</style></author><author><style face="normal" font="default" size="100%">James, TY.</style></author><author><style face="normal" font="default" size="100%">Kamada, T.</style></author><author><style face="normal" font="default" size="100%">Kilaru, S.</style></author><author><style face="normal" font="default" size="100%">Kodira, C.</style></author><author><style face="normal" font="default" size="100%">Kües, U.</style></author><author><style face="normal" font="default" size="100%">Kupfer, D.</style></author><author><style face="normal" font="default" size="100%">Kwan, HS.</style></author><author><style face="normal" font="default" size="100%">Lomsadze, A.</style></author><author><style face="normal" font="default" size="100%">Li, W.</style></author><author><style face="normal" font="default" size="100%">Lilly, WW.</style></author><author><style face="normal" font="default" size="100%">Ma, LJ.</style></author><author><style face="normal" font="default" size="100%">Mackey, AJ.</style></author><author><style face="normal" font="default" size="100%">Manning, G.</style></author><author><style face="normal" font="default" size="100%">Martin, F.</style></author><author><style face="normal" font="default" size="100%">Muraguchi, H.</style></author><author><style face="normal" font="default" size="100%">Natvig, DO.</style></author><author><style face="normal" font="default" size="100%">Palmerini, H.</style></author><author><style face="normal" font="default" size="100%">Ramesh, MA.</style></author><author><style face="normal" font="default" size="100%">Rehmeyer, CJ.</style></author><author><style face="normal" font="default" size="100%">Roe, BA.</style></author><author><style face="normal" font="default" size="100%">Shenoy, N.</style></author><author><style face="normal" font="default" size="100%">Stanke, M.</style></author><author><style face="normal" font="default" size="100%">Ter-Hovhannisyan, V.</style></author><author><style face="normal" font="default" size="100%">Tunlid, A.</style></author><author><style face="normal" font="default" size="100%">Velagapudi, R.</style></author><author><style face="normal" font="default" size="100%">Vision, TJ.</style></author><author><style face="normal" font="default" size="100%">Zeng, Q.</style></author><author><style face="normal" font="default" size="100%">Zolan, ME.</style></author><author><style face="normal" font="default" size="100%">Pukkila, PJ.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Insights into evolution of multicellular fungi from the assembled chromosomes of the mushroom Coprinopsis cinerea (Coprinus cinereus)</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the National Academy of Sciences of the United States of America</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1073/pnas.1003391107</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10.1073</style></volume><pages><style face="normal" font="default" size="100%">1003391107</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The mushroom Coprinopsis cinerea is a classic experimental model for multicellular development in fungi because it grows on defined media, completes its life cycle in 2 weeks, produces some 10(8) synchronized meiocytes, and can be manipulated at all stages in development by mutation and transformation. The 37-megabase genome of C. cinerea was sequenced and assembled into 13 chromosomes. Meiotic recombination rates vary greatly along the chromosomes, and retrotransposons are absent in large regions of the genome with low levels of meiotic recombination. Single-copy genes with identifiable orthologs in other basidiomycetes are predominant in low-recombination regions of the chromosome. In contrast, paralogous multicopy genes are found in the highly recombining regions, including a large family of protein kinases (FunK1) unique to multicellular fungi. Analyses of P450 and hydrophobin gene families confirmed that local gene duplications drive the expansions of paralogous copies and the expansions occur in independent lineages of Agaricomycotina fungi. Gene-expression patterns from microarrays were used to dissect the transcriptional program of dikaryon formation (mating). Several members of the FunK1 kinase family are differentially regulated during sexual morphogenesis, and coordinate regulation of adjacent duplications is rare. The genomes of C. cinerea and Laccaria bicolor, a symbiotic basidiomycete, share extensive regions of synteny. The largest syntenic blocks occur in regions with low meiotic recombination rates, no transposable elements, and tight gene spacing, where orthologous single-copy genes are overrepresented. The chromosome assembly of C. cinerea is an essential resource in understanding the evolution of multicellularity in the fungi.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Capella-Gutiérrez, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Lack of phylogenetic support for a supposed actinobacterial origin of peroxisomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Gene</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.gene.2010.06.004</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Peroxisomes are widespread eukaryotic organelles that show a high diversity in terms of metabolic functions. To explain their evolutionary origin, several endosymbiotic hypotheses have been put forward that suggest various possible prokaryotic ancestors. An alternative view proposes a scenario in which peroxisomes originated from the Endoplasmic Reticulum. Recently, an actinobacterial origin of peroxisomes have been proposed based on phylogenetic analysis of Pex1/6 proteins and the results of sequence comparisons of peroxisomal and bacterial proteins. Here we re-examine these data and show that the phylogenetic clustering of Pex1/6 proteins with actinobacterial proteins is likely the result of a long branch attraction artifact. Moreover, a statistical test shows that the phylogeny presented to support an actinobacterial origin is not significantly more supported than an alternative topology grouping Pex proteins with their Endoplasmic Reticulum homologs. We therefore conclude that there is a lack of phylogenetic support for a supposed actinobacterial origin of peroxisomes. Challenges for assessing the evolutionary origins of these intriguing organelles are discussed.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Povolotskaya, I. S.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sequence space and the ongoing expansion of the protein universe</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">465</style></volume><pages><style face="normal" font="default" size="100%">922–926</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Magis, C.</style></author><author><style face="normal" font="default" size="100%">Stricher, F.</style></author><author><style face="normal" font="default" size="100%">van der Sloot, AM.</style></author><author><style face="normal" font="default" size="100%">Serrano, L.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">T-RMSD: a fine-grained, structure-based classification method and its application to the functional characterization of TNF receptors.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2010.05.012</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">400</style></volume><pages><style face="normal" font="default" size="100%">605–617</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This study addresses the relation between structural and functional similarity in proteins. We introduce a novel method named tree based on root mean square deviation (T-RMSD), which uses distance RMSD (dRMSD) variations to build fine-grained structure-based classifications of proteins. The main improvement of the T-RMSD over similar methods, such as Dali, is its capacity to produce the equivalent of a bootstrap value for each cluster node. We validated our approach on two domain families studied extensively for their role in many biological and pathological pathways: the small GTPase RAS superfamily and the cysteine-rich domains (CRDs) associated with the tumor necrosis factor receptors (TNFRs) family. Our analysis showed that T-RMSD is able to automatically recover and refine existing classifications. In the case of the small GTPase ARF subfamily, T-RMSD can distinguish GTP- from GDP-bound states, while in the case of CRDs it can identify two new subgroups associated with well defined functional features (ligand binding and formation of ligand pre-assembly complex). We show how hidden Markov models (HMMs) can be built on these new groups and propose a methodology to use these models simultaneously in order to do fine-grained functional genomic annotation without known 3D structures. T-RMSD, an open source freeware incorporated in the T-Coffee package, is available online.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Hartl, FU.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Physicochemical determinants of chaperone requirements.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2010.03.066</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">400</style></volume><pages><style face="normal" font="default" size="100%">579–588</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe a series of stringent relationships between abundance, solubility and chaperone usage of proteins. Based on these relationships, we show that the need of Escherichia coli proteins for the chaperonin GroEL can be predicted with 86% accuracy. Furthermore, from the observation that the abundance and solubility of proteins depend on the physicochemical properties of their amino acid sequences, we demonstrate that the requirement for GroEL can also be predicted directly from the sequences with 90% accuracy. These results indicate that the physicochemical properties of the amino acid sequences represent an essential component of the cellular quality control system that ensures the maintenance of protein homeostasis in living systems.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Coll, O.</style></author><author><style face="normal" font="default" size="100%">Villalba, A.</style></author><author><style face="normal" font="default" size="100%">Bussotti, G.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Gebauer, F.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A novel, noncanonical mechanism of cytoplasmic polyadenylation operates in Drosophila embryogenesis.</style></title><secondary-title><style face="normal" font="default" size="100%">Genes Dev.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gad.568610</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">129–134</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Cytoplasmic polyadenylation is a widespread mechanism to regulate mRNA translation that requires two sequences in the 3' untranslated region (UTR) of vertebrate substrates: the polyadenylation hexanucleotide, and the cytoplasmic polyadenylation element (CPE). Using a cell-free Drosophila system, we show that these signals are not relevant for Toll polyadenylation but, instead, a &quot;polyadenylation region&quot; (PR) is necessary. Competition experiments indicate that PR-mediated polyadenylation is required for viability and is mechanistically distinct from the CPE/hexanucleotide-mediated process. These data indicate that Toll mRNA is polyadenylated by a noncanonical mechanism, and suggest that a novel machinery functions for cytoplasmic polyadenylation during Drosophila embryogenesis.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ETE: a python Environment for Tree Exploration.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2105-11-24</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">24</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: BACKGROUND: Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating the analysis and interpretation of results. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. RESULTS: Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and allows to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automatize the graphical rendering of trees with customized node-specific visualizations. CONCLUSIONS: ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Milinkovitch, MC.</style></author><author><style face="normal" font="default" size="100%">Helaers, R.</style></author><author><style face="normal" font="default" size="100%">Depiereux, E.</style></author><author><style face="normal" font="default" size="100%">Tzika, AC.</style></author><author><style face="normal" font="default" size="100%">Gabaldon, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">2X genomes - depth does matter.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2010-11-2-r16</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">R16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: BACKGROUND: Given the availability of full genome sequences, mapping gene gains, duplications, and losses during evolution should theoretically be straightforward. However, this endeavor suffers from overemphasis on detecting conserved genome features, which in turn has lead to sequencing multiple eutherian genomes with low coverage rather than fewer genomes with high-coverage and evener distribution in the phylogeny. Although limitations associated with analysis of low coverage genomes are recognized, they have not been quantified. RESULTS: Here, using recently-developed comparative genomic application systems, we evaluate the impact of low-coverage genomes on inferences pertaining to gene gains and losses when analyzing eukaryote genome evolution through gene duplication. We demonstrate that, when performing inference of genome content evolution, low-coverage genomes generate not only a massive number of false gene losses, but also striking artifacts in gene duplication inference, especially at the most recent common ancestor of low-coverage genomes. We show that the artifactual gains are caused by the low coverage of genome sequence per se rather than by the increased taxon sampling in a biased portion of the species tree. CONCLUSIONS: We argue that it will remain difficult to differentiate artifacts from true changes in modes and tempo of genome evolution until there is better homogeneity in both taxon sampling and high-coverage sequencing. This is important for broadening the utility of full genome data to the community of evolutionary biologists, whose interests go well beyond widely-conserved physiologies and developmental patterns as they seek to understand the generative mechanisms underlying biological diversity.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ahmadinejad, N.</style></author><author><style face="normal" font="default" size="100%">Dagan, T.</style></author><author><style face="normal" font="default" size="100%">Gruenheit, N.</style></author><author><style face="normal" font="default" size="100%">Martin, W.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of spliceosomal introns following endosymbiotic gene transfer.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC evolutionary biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2148-10-57</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">57</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: BACKGROUND: Spliceosomal introns are an ancient, widespread hallmark of eukaryotic genomes. Despite much research, many questions regarding the origin and evolution of spliceosomal introns remain unsolved, partly due to the difficulty of inferring ancestral gene structures. We circumvent this problem by using genes originated by endosymbiotic gene transfer, in which an intron-less structure at the time of the transfer can be assumed. RESULTS: By comparing the exon-intron structures of 64 mitochondrial-derived genes that were transferred to the nucleus at different evolutionary periods, we can trace the history of intron gains in different eukaryotic lineages. Our results show that the intron density of genes transferred relatively recently to the nuclear genome is similar to that of genes originated by more ancient transfers, indicating that gene structure can be rapidly shaped by intron gain after the integration of the gene into the genome and that this process is mainly determined by forces acting specifically on each lineage. We analyze 12 cases of mitochondrial-derived genes that have been transferred to the nucleus independently in more than one lineage. CONCLUSIONS: Remarkably, the proportion of shared intron positions that were gained independently in homologous genes is similar to that proportion observed in genes that were transferred prior to the speciation event and whose shared intron positions might be due to vertical inheritance. A particular case of parallel intron gain in the nad7 gene is discussed in more detail.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gerardo, NM.</style></author><author><style face="normal" font="default" size="100%">Altincicek, B.</style></author><author><style face="normal" font="default" size="100%">Anselme, C.</style></author><author><style face="normal" font="default" size="100%">Atamian, H.</style></author><author><style face="normal" font="default" size="100%">Barribeau, SM.</style></author><author><style face="normal" font="default" size="100%">de Vos, M.</style></author><author><style face="normal" font="default" size="100%">Duncan, E.</style></author><author><style face="normal" font="default" size="100%">Evans, JD.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Ghanim, M.</style></author><author><style face="normal" font="default" size="100%">Heddi, A.</style></author><author><style face="normal" font="default" size="100%">Kaloshian, I.</style></author><author><style face="normal" font="default" size="100%">Latorre, A.</style></author><author><style face="normal" font="default" size="100%">Moya, A.</style></author><author><style face="normal" font="default" size="100%">Nakabachi, A.</style></author><author><style face="normal" font="default" size="100%">Parker, BJ.</style></author><author><style face="normal" font="default" size="100%">Perez-Brocal, V.</style></author><author><style face="normal" font="default" size="100%">Pignatelli, M.</style></author><author><style face="normal" font="default" size="100%">Rhabe, Y.</style></author><author><style face="normal" font="default" size="100%">Ramsey, JS.</style></author><author><style face="normal" font="default" size="100%">Spragg, C.</style></author><author><style face="normal" font="default" size="100%">Tamames, J.</style></author><author><style face="normal" font="default" size="100%">Tamarit, D.</style></author><author><style face="normal" font="default" size="100%">Tamborindeguy, C.</style></author><author><style face="normal" font="default" size="100%">Vincent-Monegat, C.</style></author><author><style face="normal" font="default" size="100%">Vilcinskas, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Immunity and other defenses in pea aphids, Acyrthosiphon pisum.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2010-11-2-r21</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">R21</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: BACKGROUND: Recent genomic analyses of arthropod defense mechanisms suggest conservation of key elements underlying responses to pathogens, parasites and stresses. At the center of pathogen-induced immune response are signaling pathways triggered by the recognition of fungal, bacterial and viral signatures. These pathways result in the production of response molecules, such as antimicrobial peptides and lysozymes, which degrade or destroy invaders. Using the recently sequenced genome of the pea aphid (Acyrthosiphon pisum), we conducted the first extensive annotation of the immune and stress gene repertoire of a hemipterous insect, which is phylogenetically distantly-related to previously characterized insects models. RESULTS: Strikingly, pea aphids appear to be missing genes present in insect genomes characterized to date and thought critical for recognition, signaling and killing of microbes. In line with results of gene annotation, experimental analyses designed to characterize immune response through the isolation of RNA transcripts and proteins from immune-challenged pea aphids uncovered few immune-related products. Gene expression studies, however, indicated some expression of immune and stress-related genes. CONCLUSIONS: The absence of genes suspected to be essential for the insect immune response suggests that the traditional view of insect immunity may not be as broadly applicable as once thought. The limitations of the aphid immune system may be representative of a broad range of insects, or may be aphid specific. We suggest that several aspects of the aphid life style, such as their association with microbial symbionts, could facilitate survival without strong immune protection.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peña, A.</style></author><author><style face="normal" font="default" size="100%">Teeling, H.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Santos, F.</style></author><author><style face="normal" font="default" size="100%">Yarza, P.</style></author><author><style face="normal" font="default" size="100%">Brito-Echeverría, J.</style></author><author><style face="normal" font="default" size="100%">Lucio, M.</style></author><author><style face="normal" font="default" size="100%">Schmitt-Kopplin, P.</style></author><author><style face="normal" font="default" size="100%">Meseguer, I.</style></author><author><style face="normal" font="default" size="100%">Schenowitz, C.</style></author><author><style face="normal" font="default" size="100%">Dossat, C.</style></author><author><style face="normal" font="default" size="100%">Barbe, V.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Rosselló-Mora, R.</style></author><author><style face="normal" font="default" size="100%">Schüler, M.</style></author><author><style face="normal" font="default" size="100%">Glöckner, FO.</style></author><author><style face="normal" font="default" size="100%">Amann, R.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Antón, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fine-scale evolution: genomic, phenotypic and ecological differentiation in two coexisting Salinibacter ruber strains.</style></title><secondary-title><style face="normal" font="default" size="100%">The ISME journal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/ismej.2010.6</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Genomic and metagenomic data indicate a high degree of genomic variation within microbial populations, although the ecological and evolutive meaning of this microdiversity remains unknown. Microevolution analyses, including genomic and experimental approaches, are so far very scarce for non-pathogenic bacteria. In this study, we compare the genomes, metabolomes and selected ecological traits of the strains M8 and M31 of the hyperhalophilic bacterium Salinibacter ruber that contain ribosomal RNA (rRNA) gene and intergenic regions that are identical in sequence and were simultaneously isolated from a Mediterranean solar saltern. Comparative analyses indicate that S. ruber genomes present a mosaic structure with conserved and hypervariable regions (HVRs). The HVRs or genomic islands, are enriched in transposases, genes related to surface properties, strain-specific genes and highly divergent orthologous. However, the many indels outside the HVRs indicate that genome plasticity extends beyond them. Overall, 10% of the genes encoded in the M8 genome are absent from M31 and could stem from recent acquisitions. S. ruber genomes also harbor 34 genes located outside HVRs that are transcribed during standard growth and probably derive from lateral gene transfers with Archaea preceding the M8/M31 divergence. Metabolomic analyses, phage susceptibility and competition experiments indicate that these genomic differences cannot be considered neutral from an ecological perspective. The results point to the avoidance of competition by micro-niche adaptation and response to viral predation as putative major forces that drive microevolution within these Salinibacter strains. In addition, this work highlights the extent of bacterial functional diversity and environmental adaptation, beyond the resolution of the 16S rRNA and internal transcribed spacers regions.The ISME Journal advance online publication, 18 February 2010; doi:10.1038/ismej.2010.6.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Di Tommaso, P.</style></author><author><style face="normal" font="default" size="100%">Orobitg, M.</style></author><author><style face="normal" font="default" size="100%">Guirado, F.</style></author><author><style face="normal" font="default" size="100%">Cores, F.</style></author><author><style face="normal" font="default" size="100%">Espinosa, T.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cloud-Coffee: implementation of a parallel consistency-based multiple alignment algorithm in the T-Coffee package and its benchmarking on the Amazon Elastic-Cloud.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btq304</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">15</style></number><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">1903–1904</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">SUMMARY: We present the first parallel implementation of the T-Coffee consistency-based multiple aligner. We benchmark it on the Amazon Elastic Cloud (EC2) and show that the parallelization procedure is reasonably effective. We also conclude that for a web server with moderate usage (10K hits/month) the cloud provides a cost-effective alternative to in-house deployment. AVAILABILITY: T-Coffee is a freeware open source package available from http://www.tcoffee.org/homepage.html</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Manichanh, C.</style></author><author><style face="normal" font="default" size="100%">Reeder, J.</style></author><author><style face="normal" font="default" size="100%">Gibert, P.</style></author><author><style face="normal" font="default" size="100%">Varela, E.</style></author><author><style face="normal" font="default" size="100%">Llopis, M.</style></author><author><style face="normal" font="default" size="100%">Antolin, M.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Knight, R.</style></author><author><style face="normal" font="default" size="100%">Guarner, F.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reshaping the gut microbiome with bacterial transplantation and antibiotic intake.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.107987.110</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The intestinal microbiota consists of over 1000 species, which play key roles in gut physiology and homeostasis. Imbalances in the composition of this bacterial community can lead to transient intestinal dysfunctions and chronic disease states. Understanding how to manipulate this ecosystem is thus essential for treating many disorders. In this study, we took advantage of recently developed tools for deep sequencing and phylogenetic clustering to examine the long-term effects of exogenous microbiota transplantation combined with and without an antibiotic pretreatment. In our rat model, deep sequencing revealed an intestinal bacterial diversity exceeding that of the human gut by a factor of two to three. The transplantation produced a marked increase in the microbial diversity of the recipients, which stemmed from both capture of new phylotypes and increase in abundance of others. However, when transplantation was performed after antibiotic intake, the resulting state simply combined the reshaping effects of the individual treatments (including the reduced diversity from antibiotic treatment alone). Therefore, lowering the recipient bacterial load by antibiotic intake prior to transplantation did not increase establishment of the donor phylotypes, although some dominant lineages still transferred successfully. Remarkably, all of these effects were observed after 1 mo of treatment and persisted after 3 mo. Overall, our results indicate that the indigenous gut microbial composition is more plastic that previously anticipated. However, since antibiotic pretreatment counterintuitively interferes with the establishment of an exogenous community, such plasticity is likely conditioned more by the altered microbiome gut homeostasis caused by antibiotics than by the primary bacterial loss.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Roetzer, A.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Schüller, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">From Saccharomyces cerevisiae to Candida glabrata in a few easy steps: important adaptations for an opportunistic pathogen.</style></title><secondary-title><style face="normal" font="default" size="100%">FEMS microbiology letters</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1111/j.1574-6968.2010.02102.x</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The opportunistic human fungal pathogen Candida glabrata is closely related to Saccharomyces cerevisiae, yet it has evolved to survive within mammalian hosts. Which traits help C. glabrata to adapt to this different environment? Which specific responses are crucial for its survival in the host? The main differences seem to include an extended repertoire of adhesin genes, high drug resistance, an enhanced ability to sustain prolonged starvation and adaptations of the transcriptional wiring of key stress response genes. Here, we discuss the properties of C. glabrata with a focus on the differences to related fungi.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tilgner, H.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">From chromatin to splicing: RNA-processing as a total artwork</style></title><secondary-title><style face="normal" font="default" size="100%">Epigenetics : official journal of the DNA Methylation Society</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/20305391</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">5(3)</style></volume><pages><style face="normal" font="default" size="100%">180-184</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">RNA plays a central role in the determination of the phenotype of the cell. The molecular mechanisms involved in primary RNA synthesis and subsequent post-processing are not completely understood, but there is increasing evidence that they are more tightly coupled than previously expected. The analyses by a number of groups of recently published genome wide maps of chromatin structure have further uncovered a role for primary chromatin structure in RNA processing. Indeed, these analyses have revealed that nucleosomes show a characteristic occupancy pattern in exonic regions of metazoan genomes. The pattern is strongly indicative of an implication of nucleosome positioning in exon recognition during pre-mRNA splicing. Characteristic exonic patterns have also been observed for a number of histone modifications, suggesting the possibility that chromatin state plays a direct role in the regulation of splicing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">International Cancer Genome Consortium</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Martin, D.</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">International network of cancer genome projects</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature08987</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7291</style></number><volume><style face="normal" font="default" size="100%">464</style></volume><pages><style face="normal" font="default" size="100%">993–998</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Montgomery, SB.</style></author><author><style face="normal" font="default" size="100%">Sammeth, M.</style></author><author><style face="normal" font="default" size="100%">Gutierrez-Arcelus, M.</style></author><author><style face="normal" font="default" size="100%">Lach, RP.</style></author><author><style face="normal" font="default" size="100%">Ingle, C.</style></author><author><style face="normal" font="default" size="100%">Nisbett, J.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, ET.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcriptome genetics using second generation sequencing in a Caucasian population</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature08903</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7289</style></number><volume><style face="normal" font="default" size="100%">464</style></volume><pages><style face="normal" font="default" size="100%">773–777</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Gene expression is an important phenotype that informs about genetic and environmental effects on cellular state. Many studies have previously identified genetic variants for gene expression phenotypes using custom and commercially available microarrays. Second generation sequencing technologies are now providing unprecedented access to the fine structure of the transcriptome. We have sequenced the mRNA fraction of the transcriptome in 60 extended HapMap individuals of European descent and have combined these data with genetic variants from the HapMap3 project. We have quantified exon abundance based on read depth and have also developed methods to quantify whole transcript abundance. We have found that approximately 10 million reads of sequencing can provide access to the same dynamic range as arrays with better quantification of alternative and highly abundant transcripts. Correlation with SNPs (small nucleotide polymorphisms) leads to a larger discovery of eQTLs (expression quantitative trait loci) than with arrays. We also detect a substantial number of variants that influence the structure of mature transcripts indicating variants responsible for alternative splicing. Finally, measures of allele-specific expression allowed the identification of rare eQTLs and allelic differences in transcript structure. This analysis shows that high throughput sequencing technologies reveal new properties of genetic effects on the transcriptome and allow the exploration of genetic effects in cellular processes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Novoa, I.</style></author><author><style face="normal" font="default" size="100%">Gallego, J.</style></author><author><style face="normal" font="default" size="100%">Ferreira, PG.</style></author><author><style face="normal" font="default" size="100%">Mendez, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mitotic cell-cycle progression is regulated by CPEB1 and CPEB4-dependent translational control</style></title><secondary-title><style face="normal" font="default" size="100%">Nature cell biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/ncb2046</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12(5)</style></volume><pages><style face="normal" font="default" size="100%">447-456</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Meiotic and early-embryonic cell divisions in vertebrates take place in the absence of transcription and rely on the translational regulation of stored maternal messenger RNAs. Most of these mRNAs are regulated by the cytoplasmic-polyadenylation-element-binding protein (CPEB), which mediates translational activation and repression through cytoplasmic changes in their poly(A) tail length. It was unknown whether translational regulation by cytoplasmic polyadenylation and CPEB can also regulate mRNAs at specific points of mitotic cell-cycle divisions. Here we show that CPEB-mediated post-transcriptional regulation by phase-specific changes in poly(A) tail length is required for cell proliferation and specifically for entry into M phase in mitotically dividing cells. This translational control is mediated by two members of the CPEB family of proteins, CPEB1 and CPEB4. We conclude that regulation of poly(A) tail length is not only required to compensate for the lack of transcription in specialized cell divisions but also acts as a general mechanism to control mitosis.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, A. S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measurements of spontaneous rates of mutations in the recent past and the near future</style></title><secondary-title><style face="normal" font="default" size="100%">Philos. Trans. R. Soc. Lond., B, Biol. Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">365</style></volume><pages><style face="normal" font="default" size="100%">1169–1176</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brorsson, AC.</style></author><author><style face="normal" font="default" size="100%">Bolognesi, B.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Shammas, SL.</style></author><author><style face="normal" font="default" size="100%">Favrin, G.</style></author><author><style face="normal" font="default" size="100%">Watson, I.</style></author><author><style face="normal" font="default" size="100%">Lomas, DA.</style></author><author><style face="normal" font="default" size="100%">Chiti, F.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Crowther, DC.</style></author><author><style face="normal" font="default" size="100%">Luheshi, LM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Intrinsic determinants of neurotoxic aggregate formation by the amyloid beta peptide.</style></title><secondary-title><style face="normal" font="default" size="100%">Biophys. J.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.bpj.2009.12.4320</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">98</style></volume><pages><style face="normal" font="default" size="100%">1677–1684</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The extent to which proteins aggregate into distinct structures ranging from prefibrillar oligomers to amyloid fibrils is key to the pathogenesis of many age-related degenerative diseases. We describe here for the Alzheimer's disease-related amyloid beta peptide (Abeta) an investigation of the sequence-based determinants of the balance between the formation of prefibrillar aggregates and amyloid fibrils. We show that by introducing single-point mutations, it is possible to convert the normally harmless Abeta40 peptide into a pathogenic species by increasing its relative propensity to form prefibrillar but not fibrillar aggregates, and, conversely, to abolish the pathogenicity of the highly neurotoxic E22G Abeta42 peptide by reducing its relative propensity to form prefibrillar species rather than mature fibrillar ones. This observation can be rationalized by the demonstration that whereas regions of the sequence of high aggregation propensity dominate the overall tendency to aggregate, regions with low intrinsic aggregation propensities exert significant control over the balance of the prefibrillar and fibrillar species formed, and therefore play a major role in determining the neurotoxicity of the Abeta peptide.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Pignatelli, M.</style></author><author><style face="normal" font="default" size="100%">Moya, A.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The pea aphid phylome: a complete catalogue of evolutionary histories and arthropod orthology and paralogy relationships for Acyrthosiphon pisum genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Insect Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1111/j.1365-2583.2009.00947.x</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">19 Suppl 2</style></volume><pages><style face="normal" font="default" size="100%">13–21</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Phylogenetic analyses serve many purposes, including the establishment of orthology relationships, the prediction of protein function and the detection of important evolutionary events. Within the context of the sequencing of the genome of the pea aphid, Acyrthosiphon pisum, we undertook a phylogenetic analysis for every protein of this species. The resulting phylome includes the evolutionary relationships of all predicted aphid proteins and their homologues among 13 other fully-sequenced arthropods and three out-group species. Subsequent analyses have revealed multiple gene expansions that are specific to aphids and have served to transfer functional annotations to 4058 pea aphid genes that display one-to-one orthology relationships with Drosophila melanogaster annotated genes. All phylogenies and alignments are accessible through the PhylomeDB database. Here we provide a description of this dataset and provide some examples on how can it be exploited.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Innan, H.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The evolution of gene duplications: classifying and distinguishing between models</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Rev Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/nrg/journal/v11/n2/abs/nrg2689.html</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">108</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue><section><style face="normal" font="default" size="100%">97</style></section></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author><author><style face="normal" font="default" size="100%">Povolotskaya, Inna S.</style></author><author><style face="normal" font="default" size="100%">Ivankov, Dmitry N.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Rate of sequence divergence under constant selection</style></title><secondary-title><style face="normal" font="default" size="100%">Biology Direct</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2010</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Background: Divergence of two independently evolving sequences that originated from a common ancestor can be described by two parameters, the asymptotic level of divergence E and the rate r at which this level of divergence is approached. Constant negative selection impedes allele replacements and, therefore, it is routinely assumed that it must decelerate sequence divergence. However, its impact on E and on r has not been formally investigated. Results: Strong selection that favors only one allele can make E arbitrarily small and r arbitrarily large. In contrast, in the case of 4 possible alleles and equal mutation rates, the lowest value of r, attained when two alleles confer equal fitnesses and the other two are strongly deleterious, is only two times lower than its value under selective neutrality. Conclusions: Constant selection can strongly constrain the level of sequence divergence, but cannot reduce substantially the rate at which this level is approached. In particular, under any constant selection the divergence of sequences that accumulated one substitution per neutral site since their origin from the common ancestor must already constitute at least one half of the asymptotic divergence at sites under such selection.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><section><style face="normal" font="default" size="100%">5</style></section></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mihailovich, M.</style></author><author><style face="normal" font="default" size="100%">Militti, C.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Gebauer, F.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Eukaryotic cold shock domain proteins: highly versatile regulators of gene expression.</style></title><secondary-title><style face="normal" font="default" size="100%">BioEssays</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/bies.200900122</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">109–118</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Cold shock domain (CSD)-containing proteins have been found in all three domains of life and function in a variety of processes that are related, for the most part, to post-transcriptional gene regulation. The CSD is an ancient beta-barrel fold that serves to bind nucleic acids. The CSD is structurally and functionally similar to the S1 domain, a fold with otherwise unrelated primary sequence. The flexibility of the CSD/S1 domain for RNA recognition confers an enormous functional versatility to the proteins that contain them. This review summarizes the current knowledge on eukaryotic CSD/S1 domain-containing proteins with a special emphasis on UNR (upstream of N-ras), a member of this family with multiple copies of the CSD.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lingner, T.</style></author><author><style face="normal" font="default" size="100%">Mühlhausen, S.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Meinicke, P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting phenotypic traits of prokaryotes from protein domain frequencies.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2105-11-481</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">481</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Establishing the relationship between an organism's genome sequence and its phenotype is a fundamental challenge that remains largely unsolved. Accurately predicting microbial phenotypes solely based on genomic features will allow us to infer relevant phenotypic characteristics when the availability of a genome sequence precedes experimental characterization, a scenario that is favored by the advent of novel high-throughput and single cell sequencing techniques.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dalloul, RA.</style></author><author><style face="normal" font="default" size="100%">Long, JA.</style></author><author><style face="normal" font="default" size="100%">Zimin, AV.</style></author><author><style face="normal" font="default" size="100%">Aslam, L.</style></author><author><style face="normal" font="default" size="100%">Beal, K.</style></author><author><style face="normal" font="default" size="100%">Blomberg, Le Ann.</style></author><author><style face="normal" font="default" size="100%">Bouffard, P.</style></author><author><style face="normal" font="default" size="100%">Burt, DW.</style></author><author><style face="normal" font="default" size="100%">Crasta, O.</style></author><author><style face="normal" font="default" size="100%">Crooijmans, RP.</style></author><author><style face="normal" font="default" size="100%">Cooper, K.</style></author><author><style face="normal" font="default" size="100%">Coulombe, RA.</style></author><author><style face="normal" font="default" size="100%">De, S.</style></author><author><style face="normal" font="default" size="100%">Delany, ME.</style></author><author><style face="normal" font="default" size="100%">Dodgson, JB.</style></author><author><style face="normal" font="default" size="100%">Dong, JJ.</style></author><author><style face="normal" font="default" size="100%">Evans, C.</style></author><author><style face="normal" font="default" size="100%">Frederickson, KM.</style></author><author><style face="normal" font="default" size="100%">Flicek, P.</style></author><author><style face="normal" font="default" size="100%">Florea, L.</style></author><author><style face="normal" font="default" size="100%">Folkerts, O.</style></author><author><style face="normal" font="default" size="100%">Groenen, MA.</style></author><author><style face="normal" font="default" size="100%">Harkins, TT.</style></author><author><style face="normal" font="default" size="100%">Herrero, J.</style></author><author><style face="normal" font="default" size="100%">Hoffmann, S.</style></author><author><style face="normal" font="default" size="100%">Megens, HJ.</style></author><author><style face="normal" font="default" size="100%">Jiang, A.</style></author><author><style face="normal" font="default" size="100%">de Jong, P.</style></author><author><style face="normal" font="default" size="100%">Kaiser, P.</style></author><author><style face="normal" font="default" size="100%">Kim, H.</style></author><author><style face="normal" font="default" size="100%">Kim, KW.</style></author><author><style face="normal" font="default" size="100%">Kim, S.</style></author><author><style face="normal" font="default" size="100%">Langenberger, D.</style></author><author><style face="normal" font="default" size="100%">Lee, MK.</style></author><author><style face="normal" font="default" size="100%">Lee, T.</style></author><author><style face="normal" font="default" size="100%">Mane, S.</style></author><author><style face="normal" font="default" size="100%">Marcais, G.</style></author><author><style face="normal" font="default" size="100%">Marz, M.</style></author><author><style face="normal" font="default" size="100%">McElroy, AP.</style></author><author><style face="normal" font="default" size="100%">Modise, T.</style></author><author><style face="normal" font="default" size="100%">Nefedov, M.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Paton, IR.</style></author><author><style face="normal" font="default" size="100%">Payne, WS.</style></author><author><style face="normal" font="default" size="100%">Pertea, G.</style></author><author><style face="normal" font="default" size="100%">Prickett, D.</style></author><author><style face="normal" font="default" size="100%">Puiu, D.</style></author><author><style face="normal" font="default" size="100%">Qioa, D.</style></author><author><style face="normal" font="default" size="100%">Raineri, E.</style></author><author><style face="normal" font="default" size="100%">Ruffier, M.</style></author><author><style face="normal" font="default" size="100%">Salzberg, SL.</style></author><author><style face="normal" font="default" size="100%">Schatz, MC.</style></author><author><style face="normal" font="default" size="100%">Scheuring, C.</style></author><author><style face="normal" font="default" size="100%">Schmidt, CJ.</style></author><author><style face="normal" font="default" size="100%">Schroeder, S.</style></author><author><style face="normal" font="default" size="100%">Searle, SM.</style></author><author><style face="normal" font="default" size="100%">Smith, EJ.</style></author><author><style face="normal" font="default" size="100%">Smith, J.</style></author><author><style face="normal" font="default" size="100%">Sonstegard, TS.</style></author><author><style face="normal" font="default" size="100%">Stadler, PF.</style></author><author><style face="normal" font="default" size="100%">Tafer, H.</style></author><author><style face="normal" font="default" size="100%">Tu, ZJ.</style></author><author><style face="normal" font="default" size="100%">Van Tassell, CP.</style></author><author><style face="normal" font="default" size="100%">Vilella, AJ.</style></author><author><style face="normal" font="default" size="100%">Williams, KP.</style></author><author><style face="normal" font="default" size="100%">Yorke, JA.</style></author><author><style face="normal" font="default" size="100%">Zhang, L.</style></author><author><style face="normal" font="default" size="100%">Zhang, HB.</style></author><author><style face="normal" font="default" size="100%">Zhang, X.</style></author><author><style face="normal" font="default" size="100%">Zhang, Y.</style></author><author><style face="normal" font="default" size="100%">Reed, KM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multi-platform next-generation sequencing of the domestic turkey (Meleagris gallopavo): genome assembly and analysis.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pbio.1000475</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">8</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A synergistic combination of two next-generation sequencing platforms with a detailed comparative BAC physical contig map provided a cost-effective assembly of the genome sequence of the domestic turkey (Meleagris gallopavo). Heterozygosity of the sequenced source genome allowed discovery of more than 600,000 high quality single nucleotide variants. Despite this heterozygosity, the current genome assembly (∼1.1 Gb) includes 917 Mb of sequence assigned to specific turkey chromosomes. Annotation identified nearly 16,000 genes, with 15,093 recognized as protein coding and 611 as non-coding RNA genes. Comparative analysis of the turkey, chicken, and zebra finch genomes, and comparing avian to mammalian species, supports the characteristic stability of avian genomes and identifies genes unique to the avian lineage. Clear differences are seen in number and variety of genes of the avian immune system where expansions and novel genes are less frequent than examples of gene loss. The turkey genome sequence provides resources to further understand the evolution of vertebrate genomes and genetic variation underlying economically important quantitative traits in poultry. This integrated approach may be a model for providing both gene and chromosome level assemblies of other species with agricultural, ecological, and evolutionary interest.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yau, WL.</style></author><author><style face="normal" font="default" size="100%">Blisnick, T.</style></author><author><style face="normal" font="default" size="100%">Taly, JF.</style></author><author><style face="normal" font="default" size="100%">Helmer-Citterich, M.</style></author><author><style face="normal" font="default" size="100%">Schiene-Fischer, C.</style></author><author><style face="normal" font="default" size="100%">Leclercq, O.</style></author><author><style face="normal" font="default" size="100%">Li, J.</style></author><author><style face="normal" font="default" size="100%">Schmidt-Arras, D.</style></author><author><style face="normal" font="default" size="100%">Morales, MA.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Romo, D.</style></author><author><style face="normal" font="default" size="100%">Bastin, P.</style></author><author><style face="normal" font="default" size="100%">Späth, GF.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cyclosporin A treatment of Leishmania donovani reveals stage-specific functions of cyclophilins in parasite proliferation and viability.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Negl Trop Dis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pntd.0000729</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e729</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Cyclosporin A (CsA) has important anti-microbial activity against parasites of the genus Leishmania, suggesting CsA-binding cyclophilins (CyPs) as potential drug targets. However, no information is available on the genetic diversity of this important protein family, and the mechanisms underlying the cytotoxic effects of CsA on intracellular amastigotes are only poorly understood. Here, we performed a first genome-wide analysis of Leishmania CyPs and investigated the effects of CsA on host-free L. donovani amastigotes in order to elucidate the relevance of these parasite proteins for drug development.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Liberles DA</style></author><author><style face="normal" font="default" size="100%">Dittmar de la Cruz K</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Gene Dosage and Duplication</style></title><secondary-title><style face="normal" font="default" size="100%">Evolution after Gene Duplication</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><publisher><style face="normal" font="default" size="100%">Wiley </style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Detectiocases of possible functional diversification between orthologous proteins.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">The International Aphid Genomics Consortium</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Câmara, F.</style></author></secondary-authors><translated-authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome Sequence of the Pea Aphid Acyrthosiphon pisum</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pbio.1000313</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">e1000313</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Aphids are important agricultural pests and also biological models for studies of insect-plant interactions, symbiosis, virus vectoring, and the developmental causes of extreme phenotypic plasticity. Here we present the 464 Mb draft genome assembly of the pea aphid Acyrthosiphon pisum. This first published whole genome sequence of a basal hemimetabolous insect provides an outgroup to the multiple published genomes of holometabolous insects. Pea aphids are host-plant specialists, they can reproduce both sexually and asexually, and they have coevolved with an obligate bacterial symbiont. Here we highlight findings from whole genome analysis that may be related to these unusual biological features. These findings include discovery of extensive gene duplication in more than 2000 gene families as well as loss of evolutionarily conserved genes. Gene family expansions relative to other published genomes include genes involved in chromatin modification, miRNA synthesis, and sugar transport. Gene losses include genes central to the IMD immune pathway, selenoprotein utilization, purine salvage, and the entire urea cycle. The pea aphid genome reveals that only a limited number of genes have been acquired from bacteria; thus the reduced gene count of Buchnera does not reflect gene transfer to the host genome. The inventory of metabolic genes in the pea aphid genome suggests that there is extensive metabolite exchange between the aphid and Buchnera, including sharing of amino acid biosynthesis between the aphid and Buchnera. The pea aphid genome provides a foundation for post-genomic studies of fundamental biological questions and applied agricultural problems.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gil Borlado, MC.</style></author><author><style face="normal" font="default" size="100%">Moreno Lastres, D.</style></author><author><style face="normal" font="default" size="100%">Gonzalez Hoyuela, M.</style></author><author><style face="normal" font="default" size="100%">Moran, M.</style></author><author><style face="normal" font="default" size="100%">Blazquez, A.</style></author><author><style face="normal" font="default" size="100%">Pello, R.</style></author><author><style face="normal" font="default" size="100%">Marin Buera, L.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Garcia Peñas, JJ.</style></author><author><style face="normal" font="default" size="100%">Martín, MA.</style></author><author><style face="normal" font="default" size="100%">Arenas, J.</style></author><author><style face="normal" font="default" size="100%">Ugalde, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of the mitochondrial genetic background in complex III deficiency.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pone.0012801</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">5</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: In recent years clinical evidence has emphasized the importance of the mtDNA genetic background that hosts a primary pathogenic mutation in the clinical expression of mitochondrial disorders, but little experimental confirmation has been provided. We have analyzed the pathogenic role of a novel homoplasmic mutation (m.15533 A&gt;G) in the cytochrome b (MT-CYB) gene in a patient presenting with lactic acidosis, seizures, mild mental delay, and behaviour abnormalities. METHODOLOGY: Spectrophotometric analyses of the respiratory chain enzyme activities were performed in different tissues, the whole muscle mitochondrial DNA of the patient was sequenced, and the novel mutation was confirmed by PCR-RFLP. Transmitochondrial cybrids were constructed to confirm the pathogenicity of the mutation, and assembly/stability studies were carried out in fibroblasts and cybrids by means of mitochondrial translation inhibition in combination with blue native gel electrophoresis. PRINCIPAL FINDINGS: Biochemical analyses revealed a decrease in respiratory chain complex III activity in patient's skeletal muscle, and a combined enzyme defect of complexes III and IV in fibroblasts. Mutant transmitochondrial cybrids restored normal enzyme activities and steady-state protein levels, the mutation was mildly conserved along evolution, and the proband's mother and maternal aunt, both clinically unaffected, also harboured the homoplasmic mutation. These data suggested a nuclear genetic origin of the disease. However, by forcing the de novo functioning of the OXPHOS system, a severe delay in the biogenesis of the respiratory chain complexes was observed in the mutants, which demonstrated a direct functional effect of the mitochondrial genetic background. CONCLUSIONS: Our results point to possible pitfalls in the detection of pathogenic mitochondrial mutations, and highlight the role of the genetic mtDNA background in the development of mitochondrial disorders.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gauthier, Jacques-Antoine</style></author><author><style face="normal" font="default" size="100%">Widmer, Eric D.</style></author><author><style face="normal" font="default" size="100%">Bucher, Philipp</style></author><author><style face="normal" font="default" size="100%">Notredame, Cédric</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MULTICHANNEL SEQUENCE ANALYSIS APPLIED TO SOCIAL SCIENCE DATA</style></title><secondary-title><style face="normal" font="default" size="100%">Sociological Methodology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1111/j.1467-9531.2010.01227.x</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><publisher><style face="normal" font="default" size="100%">Blackwell Publishing Inc</style></publisher><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">1–38</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castellano, S.</style></author><author><style face="normal" font="default" size="100%">Andrés, AM.</style></author><author><style face="normal" font="default" size="100%">Bosch, E.</style></author><author><style face="normal" font="default" size="100%">Bayes, M.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Clark, AG.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Low exchangeability of selenocysteine, the 21st amino acid, in vertebrate proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol. Biol. Evol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/molbev/msp10</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">2031–2040</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Selenocysteine (Sec), the 21st amino acid, is incorporated into proteins through the recoding of a termination codon, an inefficient translational process mediated by a complex molecular machinery. Sec is a rare amino acid in extant proteins, chemically similar to cysteine (Cys), found in homologous position to Cys of nonselenoprotein families. Selenoproteins account for the dependence of vertebrates on environmental selenium (Se) and have an important role in several Se-deficiency diseases. Selenoproteins are poorly characterized enzymes and reports on the functional exchangeability of Sec with Cys are limited and controversial. Whether the unique role of Sec in some selenoenzymes illustrates the broader contribution of Se to protein function is unknown (Gromer S, Johansson L, Bauer H, Arscott LD, Rauch S, Ballou DP, Williams CH Jr, Schirmer RH, Arnér ES. 2003. Active sites of thioredoxin reductases: why selenoproteins? Proc Natl Acad Sci USA. 100:12618-12623). Here, we address this question from an evolutionary perspective by the simultaneous identification of the patterns of divergence in almost half a billion years of vertebrate evolution and diversity within the human lineage for the full complement of enzymatic Sec residues in these proteomes. We complete this analysis with data for the homologous Cys residues in the same genomes. Our results indicate concerted purifying selection across Sec and Cys sites in all selenoproteomes, consistent with a unique role of Sec in protein function, low exchangeability, and an unknown degree of functional divergence with Cys homologs. The distinct biochemical properties of Sec, rather than the geographical distribution of Se, global O(2) levels or Sec metabolic cost, appear to play a major role in driving adaptive changes in vertebrate selenoproteomes. A better understanding of the selenoproteomes and neutral evolutionary patterns in other taxa will be necessary to fully assess the generality of this conclusion.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gil-Borlado, MC.</style></author><author><style face="normal" font="default" size="100%">González-Hoyuela, M.</style></author><author><style face="normal" font="default" size="100%">Blázquez, A.</style></author><author><style face="normal" font="default" size="100%">García-Silva, MT.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Manzanares, J.</style></author><author><style face="normal" font="default" size="100%">Vara, J.</style></author><author><style face="normal" font="default" size="100%">Martín, MA.</style></author><author><style face="normal" font="default" size="100%">Seneca, S.</style></author><author><style face="normal" font="default" size="100%">Arenas, J.</style></author><author><style face="normal" font="default" size="100%">Ugalde, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pathogenic mutations in the 5' untranslated region of BCS1L mRNA in mitochondrial complex III deficiency.</style></title><secondary-title><style face="normal" font="default" size="100%">Mitochondrion</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.mito.2009.04.00</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">299–305</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Mutations in the assembly chaperone BCS1L constitute a major cause of mitochondrial complex III deficiency. We studied the presence of BCS1L mutations in a complex III-deficient patient with metabolic acidosis, liver failure, and tubulopathy. A previously reported mutation, p.R56X, was identified in one BCS1L allele, and two novel heterozygous mutations, g.1181A&gt;G and g.1164C&gt;G, were detected in the second allele. The g.1181A&gt;G mutation generated an alternative splicing site in the BCS1L transcript, causing a 19-nucleotides deletion in its 5'UTR region. Decreased BCS1L mRNA and protein levels, and a respiratory chain complex III assembly impairment, determine a pathogenic role for the novel BCS1L mutations.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tilgner, H.</style></author><author><style face="normal" font="default" size="100%">Nikolaou, C.</style></author><author><style face="normal" font="default" size="100%">Althammer, S.</style></author><author><style face="normal" font="default" size="100%">Sammeth, M.</style></author><author><style face="normal" font="default" size="100%">Beato, M.</style></author><author><style face="normal" font="default" size="100%">Valcárcel, J.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Nucleosome positioning as a determinant of exon recognition</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Struct. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nsmb.1658</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">996–1001</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Chromatin structure influences transcription, but its role in subsequent RNA processing is unclear. Here we present analyses of high-throughput data that imply a relationship between nucleosome positioning and exon definition. First, we have found stable nucleosome occupancy within human and Caenorhabditis elegans exons that is stronger in exons with weak splice sites. Conversely, we have found that pseudoexons–intronic sequences that are not included in mRNAs but are flanked by strong splice sites–show nucleosome depletion. Second, the ratio between nucleosome occupancy within and upstream from the exons correlates with exon-inclusion levels. Third, nucleosomes are positioned central to exons rather than proximal to splice sites. These exonic nucleosomal patterns are also observed in non-expressed genes, suggesting that nucleosome marking of exons exists in the absence of transcription. Our analysis provides a framework that contributes to the understanding of splicing on the basis of chromatin architecture.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Makrythanasis, P.</style></author><author><style face="normal" font="default" size="100%">Kapranov, P.</style></author><author><style face="normal" font="default" size="100%">Bartoloni, L.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Deutsch, S.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Drenkow, J.</style></author><author><style face="normal" font="default" size="100%">Rossier, C.</style></author><author><style face="normal" font="default" size="100%">Ariani, F.</style></author><author><style face="normal" font="default" size="100%">Capra, V.</style></author><author><style face="normal" font="default" size="100%">Excoffier, L.</style></author><author><style face="normal" font="default" size="100%">Renieri, A.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Variation in novel exons (RACEfrags) of the MECP2 gene in Rett syndrome patients and controls.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum. Mutat.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/humu.21073</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">E866–E879</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The study of transcription using genomic tiling arrays has lead to the identification of numerous additional exons. One example is the MECP2 gene on the X chromosome; using 5'RACE and RT-PCR in human tissues and cell lines, we have found more than 70 novel exons (RACEfrags) connecting to at least one annotated exon.. We sequenced all MECP2-connected exons and flanking sequences in 3 groups: 46 patients with the Rett syndrome and without mutations in the currently annotated exons of the MECP2 and CDKL5 genes; 32 patients with the Rett syndrome and identified mutations in the MECP2 gene; 100 control individuals from the same geoethnic group. Approximately 13 kb were sequenced per sample, (2.4 Mb of DNA resequencing). A total of 75 individuals had novel rare variants (mostly private variants) but no statistically significant difference was found among the 3 groups. These results suggest that variants in the newly discovered exons may not contribute to Rett syndrome. Interestingly however, there are about twice more variants in the novel exons than in the flanking sequences (44 vs. 21 for approximately 1.3 Mb sequenced for each class of sequence</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kemena, C.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Upcoming challenges for multiple sequence alignment methods in the high-throughput era.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btp452</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">2455–2465</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This review focuses on recent trends in multiple sequence alignment tools. It describes the latest algorithmic improvements including the extension of consistency-based methods to the problem of template-based multiple sequence alignments. Some results are presented suggesting that template-based methods are significantly more accurate than simpler alternative methods. The validation of existing methods is also discussed at length with the detailed description of recent results and some suggestions for future validation strategies. The last part of the review addresses future challenges for multiple sequence alignment methods in the genomic era, most notably the need to cope with very large sequences, the need to integrate large amounts of experimental data, the need to accurately align non-coding and non-transcribed sequences and finally, the need to integrate many alternative methods and approaches.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Buschbeck, M.</style></author><author><style face="normal" font="default" size="100%">Uribesalgo, I.</style></author><author><style face="normal" font="default" size="100%">Wibowo, I.</style></author><author><style face="normal" font="default" size="100%">Rué, P.</style></author><author><style face="normal" font="default" size="100%">Martin, D.</style></author><author><style face="normal" font="default" size="100%">Gutierrez, A.</style></author><author><style face="normal" font="default" size="100%">Morey, L.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">López-Schier, H.</style></author><author><style face="normal" font="default" size="100%">Di Croce, L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The histone variant macroH2A is an epigenetic regulator of key developmental genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Struct. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nsmb.1665</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">1074–1079</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The histone variants macroH2A1 and macroH2A2 are associated with X chromosome inactivation in female mammals. However, the physiological function of macroH2A proteins on autosomes is poorly understood. Microarray-based analysis in human male pluripotent cells uncovered occupancy of both macroH2A variants at many genes encoding key regulators of development and cell fate decisions. On these genes, the presence of macroH2A1+2 is a repressive mark that overlaps locally and functionally with Polycomb repressive complex 2. We demonstrate that macroH2A1+2 contribute to the fine-tuning of temporal activation of HOXA cluster genes during neuronal differentiation. Furthermore, elimination of macroH2A2 function in zebrafish embryos produced severe but specific phenotypes. Taken together, our data demonstrate that macroH2A variants constitute an important epigenetic mark involved in the concerted regulation of gene expression programs during cellular differentiation and vertebrate development.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Schlüter, A.</style></author><author><style face="normal" font="default" size="100%">Real-Chicharro, A.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Sánchez-Jiménez, F.</style></author><author><style face="normal" font="default" size="100%">Pujol, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PeroxisomeDB 2.0: an integrative view of the global peroxisomal metabolome</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Boj, SF.</style></author><author><style face="normal" font="default" size="100%">Servitja, JM.</style></author><author><style face="normal" font="default" size="100%">Martin, D.</style></author><author><style face="normal" font="default" size="100%">Rios, M.</style></author><author><style face="normal" font="default" size="100%">Talianidis, I.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Ferrer, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Functional targets of the monogenic diabetes transcription factors HNF-1alpha and HNF-4alpha are highly conserved between mice and humans.</style></title><secondary-title><style face="normal" font="default" size="100%">Diabetes</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.2337/db08-081</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">1245–1253</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">OBJECTIVE: The evolutionary conservation of transcriptional mechanisms has been widely exploited to understand human biology and disease. Recent findings, however, unexpectedly showed that the transcriptional regulators hepatocyte nuclear factor (HNF)-1alpha and -4alpha rarely bind to the same genes in mice and humans, leading to the proposal that tissue-specific transcriptional regulation has undergone extensive divergence in the two species. Such observations have major implications for the use of mouse models to understand HNF-1alpha- and HNF-4alpha-deficient diabetes. However, the significance of studies that assess binding without considering regulatory function is poorly understood. RESEARCH DESIGN AND METHODS: We compared previously reported mouse and human HNF-1alpha and HNF-4alpha binding studies with independent binding experiments. We also integrated binding studies with mouse and human loss-of-function gene expression datasets. RESULTS: First, we confirmed the existence of species-specific HNF-1alpha and -4alpha binding, yet observed incomplete detection of binding in the different datasets, causing an underestimation of binding conservation. Second, only a minor fraction of HNF-1alpha- and HNF-4alpha-bound genes were downregulated in the absence of these regulators. This subset of functional targets did not show evidence for evolutionary divergence of binding or binding sequence motifs. Finally, we observed differences between conserved and species-specific binding properties. For example, conserved binding was more frequently located near transcriptional start sites and was more likely to involve multiple binding events in the same gene. CONCLUSIONS: Despite evolutionary changes in binding, essential direct transcriptional functions of HNF-1alpha and -4alpha are largely conserved between mice and humans.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Buell, AK.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Birkett, NR.</style></author><author><style face="normal" font="default" size="100%">Waudby, CA.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Salvatella, X.</style></author><author><style face="normal" font="default" size="100%">Welland, ME.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Knowles, TP.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Position-dependent electrostatic protection against protein aggregation.</style></title><secondary-title><style face="normal" font="default" size="100%">Chembiochem</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/cbic.200900144</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">1309–1312</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Proteins with a high propensity to aggregate can be largely prevented from doing so with surprisingly small changes to their primary structure. By using a combination of rational design and quantitative measurements of aggregation rates, we show that adding a single charge in specific &quot;gatekeeper&quot; regions is sufficient to change the timescale for amyloid fibril growth from minutes to weeks, thereby dramatically reducing the efficiency of this process.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Pechmann, S.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A relationship between mRNA expression levels and protein solubility in E. coli.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2009.03.002</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">388</style></volume><pages><style face="normal" font="default" size="100%">381–389</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Each step in the process of gene expression, from the transcription of DNA into mRNA to the folding and posttranslational modification of proteins, is regulated by complex cellular mechanisms. At the same time, stringent conditions on the physicochemical properties of proteins, and hence on the nature of their amino acids, are imposed by the need to avoid aggregation at the concentrations required for optimal cellular function. A relationship is therefore expected to exist between mRNA expression levels and protein solubility in the cell. By investigating such a relationship, we formulate a method that enables the prediction of the maximal levels of mRNA expression in Escherichia coli with an accuracy of 83% and of the solubility of recombinant human proteins expressed in E. coli with an accuracy of 86%.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chapple, CE.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Krol, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SECISaln, a web-based tool for the creation of structure-based alignments of eukaryotic SECIS elements.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btp02</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">674–675</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">SUMMARY: Selenoproteins contain the 21st amino acid selenocysteine which is encoded by an inframe UGA codon, usually read as a stop. In eukaryotes, its co-translational recoding requires the presence of an RNA stem-loop structure, the SECIS element in the 3 untranslated region of (UTR) selenoprotein mRNAs. Despite little sequence conservation, SECIS elements share the same overall secondary structure. Until recently, the lack of a significantly high number of selenoprotein mRNA sequences hampered the identification of other potential sequence conservation. In this work, the web-based tool SECISaln provides for the first time an extensive structure-based sequence alignment of SECIS elements resulting from the well-defined secondary structure of the SECIS RNA and the increased size of the eukaryotic selenoproteome. We have used SECISaln to improve our knowledge of SECIS secondary structure and to discover novel, conserved nucleotide positions and we believe it will be a useful tool for the selenoprotein and RNA scientific communities. AVAILABILITY: SECISaln is freely available as a web-based tool at http://genome.crg.es/software/secisaln/.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Koscielny, G.</style></author><author><style face="normal" font="default" size="100%">Le Texier, V.</style></author><author><style face="normal" font="default" size="100%">Gopalakrishnan, C.</style></author><author><style face="normal" font="default" size="100%">Kumanduri, V.</style></author><author><style face="normal" font="default" size="100%">Riethoven, JJ.</style></author><author><style face="normal" font="default" size="100%">Nardone, F.</style></author><author><style face="normal" font="default" size="100%">Stanley, E.</style></author><author><style face="normal" font="default" size="100%">Fallsehr, C.</style></author><author><style face="normal" font="default" size="100%">Hofmann, O.</style></author><author><style face="normal" font="default" size="100%">Kull, M.</style></author><author><style face="normal" font="default" size="100%">Harrington, E.</style></author><author><style face="normal" font="default" size="100%">Boué, S.</style></author><author><style face="normal" font="default" size="100%">Eyras, E.</style></author><author><style face="normal" font="default" size="100%">Plass, M.</style></author><author><style face="normal" font="default" size="100%">Lopez, F.</style></author><author><style face="normal" font="default" size="100%">Ritchie, W.</style></author><author><style face="normal" font="default" size="100%">Moucadel, V.</style></author><author><style face="normal" font="default" size="100%">Ara, T.</style></author><author><style face="normal" font="default" size="100%">Pospisil, H.</style></author><author><style face="normal" font="default" size="100%">Herrmann, A.</style></author><author><style face="normal" font="default" size="100%">G Reich, J.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Bork, P.</style></author><author><style face="normal" font="default" size="100%">Doeberitz, MK.</style></author><author><style face="normal" font="default" size="100%">Vilo, J.</style></author><author><style face="normal" font="default" size="100%">Hide, W.</style></author><author><style face="normal" font="default" size="100%">Apweiler, R.</style></author><author><style face="normal" font="default" size="100%">Thanaraj, TA.</style></author><author><style face="normal" font="default" size="100%">Gautheret, D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ASTD: The Alternative Splicing and Transcript Diversity database.</style></title><secondary-title><style face="normal" font="default" size="100%">Genomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.ygeno.2008.11.00</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">93</style></volume><pages><style face="normal" font="default" size="100%">213–220</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The Alternative Splicing and Transcript Diversity database (ASTD) gives access to a vast collection of alternative transcripts that integrate transcription initiation, polyadenylation and splicing variant data. Alternative transcripts are derived from the mapping of transcribed sequences to the complete human, mouse and rat genomes using an extension of the computational pipeline developed for the ASD (Alternative Splicing Database) and ATD (Alternative Transcript Diversity) databases, which are now superseded by ASTD. For the human genome, ASTD identifies splicing variants, transcription initiation variants and polyadenylation variants in 68%, 68% and 62% of the gene set, respectively, consistent with current estimates for transcription variation. Users can access ASTD through a variety of browsing and query tools, including expression state-based queries for the identification of tissue-specific isoforms. Participating laboratories have experimentally validated a subset of ASTD-predicted alternative splice forms and alternative polyadenylation forms that were not previously reported. The ASTD database can be accessed at http://www.ebi.ac.uk/astd.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pignatelli, M.</style></author><author><style face="normal" font="default" size="100%">Serras, F.</style></author><author><style face="normal" font="default" size="100%">Moya, A.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Corominas, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CROC: finding chromosomal clusters in eukaryotic genomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btp24</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">1552–1553</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">SUMMARY: There is increasing evidence showing that co-expression of genes that cluster along the genome is a common characteristic of eukaryotic transcriptomes. Several algorithms have been used to date in the identification of these kinds of gene organization. Here, we present a web tool called CROC that aims to help in the identification and analysis of genomic gene clusters. This method has been successfully used before in the identification of chromosomal clusters in different eukaryotic species. AVAILABILITY: The web server is freely available to non-commercial users at the following address: http://metagenomics.uv.es/CROC/.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Servitja, JM.</style></author><author><style face="normal" font="default" size="100%">Pignatelli, M.</style></author><author><style face="normal" font="default" size="100%">Maestro, MA.</style></author><author><style face="normal" font="default" size="100%">Cardalda, C.</style></author><author><style face="normal" font="default" size="100%">Boj, SF.</style></author><author><style face="normal" font="default" size="100%">Lozano, J.</style></author><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Lafuente, A.</style></author><author><style face="normal" font="default" size="100%">McCarthy, MI.</style></author><author><style face="normal" font="default" size="100%">Sumoy, L.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Ferrer, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hnf1alpha (MODY3) controls tissue-specific transcriptional programs and exerts opposed effects on cell growth in pancreatic islets and liver.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol. Cell. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1128/MCB.01389-0</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">2945–2959</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Heterozygous HNF1A mutations cause pancreatic-islet beta-cell dysfunction and monogenic diabetes (MODY3). Hnf1alpha is known to regulate numerous hepatic genes, yet knowledge of its function in pancreatic islets is more limited. We now show that Hnf1a deficiency in mice leads to highly tissue-specific changes in the expression of genes involved in key functions of both islets and liver. To gain insights into the mechanisms of tissue-specific Hnf1alpha regulation, we integrated expression studies of Hnf1a-deficient mice with identification of direct Hnf1alpha targets. We demonstrate that Hnf1alpha can bind in a tissue-selective manner to genes that are expressed only in liver or islets. We also show that Hnf1alpha is essential only for the transcription of a minor fraction of its direct-target genes. Even among genes that were expressed in both liver and islets, the subset of targets showing functional dependence on Hnf1alpha was highly tissue specific. This was partly explained by the compensatory occupancy by the paralog Hnf1beta at selected genes in Hnf1a-deficient liver. In keeping with these findings, the biological consequences of Hnf1a deficiency were markedly different in islets and liver. Notably, Hnf1a deficiency led to impaired large-T-antigen-induced growth and oncogenesis in beta cells yet enhanced proliferation in hepatocytes. Collectively, these findings show that Hnf1alpha governs broad, highly tissue-specific genetic programs in pancreatic islets and liver and reveal key consequences of Hnf1a deficiency relevant to the pathophysiology of monogenic diabetes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Routledge, KE.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Platt, GW.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Radford, SE.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Competition between intramolecular and intermolecular interactions in an amyloid-forming protein.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2009.04.042</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">389</style></volume><pages><style face="normal" font="default" size="100%">776–786</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Despite much progress in understanding the folding and the aggregation processes of proteins, the rules defining their interplay have yet to be fully defined. This problem is of particular importance since many diseases are initiated by protein unfolding and hence the propensity to aggregate competes with intramolecular collapse and other folding events. Here, we describe the roles of intramolecular and intermolecular interactions in defining the length of the lag time and the apparent rate of elongation of the 100-residue protein human beta(2)-microglobulin at pH 2.5, commencing from an acid-denatured state that lacks persistent structure but contains significant non-random hydrophobic interactions. Using a combination of site-directed mutagenesis, quantitative kinetic analysis and computational methods, we show that only a single region of about 10 residues in length, determines the rate of fibril formation, despite the fact that other regions exhibit a significant intrinsic propensity for aggregation. We rationalise these results by analysing the effect of incorporating the conformational properties of acid-unfolded beta(2)-microglobulin and its variants at pH 2.5 as measured by NMR spectroscopy into the Zyggregator aggregation prediction algorithm. These results demonstrate that residual structure in the precursor state modulates the intrinsic propensity of the polypeptide chain to aggregate and that the algorithm developed here allows the key regions for aggregation to be more clearly identified and the rates of their self-association to be predicted. Given the common propensity of unfolded chains to form non-random intramolecular interactions as monomers and to self-assemble subsequently into amyloid fibrils, the approach developed should find widespread utility for the prediction of regions important in amyloid formation and their rates of self-assembly.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pechmann, S.</style></author><author><style face="normal" font="default" size="100%">Levy, ED.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Physicochemical principles that regulate the competition between functional and dysfunctional association of proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Natl. Acad. Sci. U.S.A.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1073/pnas.0812414106</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">25</style></number><volume><style face="normal" font="default" size="100%">106</style></volume><pages><style face="normal" font="default" size="100%">10159–10164</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">To maintain protein homeostasis, a variety of quality control mechanisms, such as the unfolded protein response and the heat shock response, enable proteins to fold and to assemble into functional complexes while avoiding the formation of aberrant and potentially harmful aggregates. We show here that a complementary contribution to the regulation of the interactions between proteins is provided by the physicochemical properties of their amino acid sequences. The results of a systematic analysis of the protein-protein complexes in the Protein Data Bank (PDB) show that interface regions are more prone to aggregate than other surface regions, indicating that many of the interactions that promote the formation of functional complexes, including hydrophobic and electrostatic forces, can potentially also cause abnormal intermolecular association. We also show, however, that aggregation-prone interfaces are prevented from triggering uncontrolled assembly by being stabilized into their functional conformations by disulfide bonds and salt bridges. These results indicate that functional and dysfunctional association of proteins are promoted by similar forces but also that they are closely regulated by the presence of specific interactions that stabilize native states.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arman, M.</style></author><author><style face="normal" font="default" size="100%">Aguilera-Montilla, N.</style></author><author><style face="normal" font="default" size="100%">Mas, V.</style></author><author><style face="normal" font="default" size="100%">Puig-Kröger, A.</style></author><author><style face="normal" font="default" size="100%">Pignatelli, M.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Corbí, AL.</style></author><author><style face="normal" font="default" size="100%">Lozano, F.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The human CD6 gene is transcriptionally regulated by RUNX and Ets transcription factors in T cells.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol. Immunol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.molimm.2009.04.01</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11-12</style></number><volume><style face="normal" font="default" size="100%">46</style></volume><pages><style face="normal" font="default" size="100%">2226–2235</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">CD6 is a lymphocyte surface receptor involved in lymphocyte activation and differentiation processes that is constitutively expressed on developing and mature T cells and on the B1a cells. To define the molecular basis for the tissue-specific expression of CD6 we have identified the transcription factors that control the activity of the proximal regulatory region of the human CD6 gene. The TATA-less CD6 promoter contains multiple transcriptional start sites, and its preferential activity in human T lymphocytes is dependent on RUNX- and Ets-binding sites located within a highly conserved region. RUNX and Ets-1 factors transactivated the CD6 promoter through recognition of the -215 and -230 binding sites, respectively. Chromatin immunoprecipitation assays revealed that RUNX1 constitutively occupies the CD6 promoter in vivo, and knockdown experiments demonstrated that the steady-state level of CD6 mRNA is dependent on the expression of RUNX1, RUNX3 and Ets-1 transcription factors. Therefore, RUNX1/3 and Ets1 control the expression of CD6 in human T lymphocytes, thus expanding the range of T-cell specific and developmentally regulated lymphocyte gene targets involved in T-cell activation and differentiation.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Varas, F.</style></author><author><style face="normal" font="default" size="100%">Stadtfeld, M.</style></author><author><style face="normal" font="default" size="100%">de Andres-Aguayo, L.</style></author><author><style face="normal" font="default" size="100%">Maherali, N.</style></author><author><style face="normal" font="default" size="100%">di Tullio, A.</style></author><author><style face="normal" font="default" size="100%">Pantano, L.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Hochedlinger, K.</style></author><author><style face="normal" font="default" size="100%">Graf, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fibroblast-derived induced pluripotent stem cells show no common retroviral vector insertions.</style></title><secondary-title><style face="normal" font="default" size="100%">Stem Cells</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1634/stemcells.2008-0696</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">300–306</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Several laboratories have reported the reprogramming of mouse and human fibroblasts into pluripotent cells, using retroviruses carrying the Oct4, Sox2, Klf4, and c-Myc transcription factor genes. In these experiments the frequency of reprogramming was lower than 0.1% of the infected cells, raising the possibility that additional events are required to induce reprogramming, such as activation of genes triggered by retroviral insertions. We have therefore determined by ligation-mediated polymerase chain reaction (LM-PCR) the retroviral insertion sites in six induced pluripotent stem (iPS) cell clones derived from mouse fibroblasts. Seventy-nine insertion sites were assigned to a single mouse genome location. Thirty-five of these mapped to gene transcription units, whereas 29 insertions landed within 10 kilobases of transcription start sites. No common insertion site was detected among the iPS clones studied. Moreover, bioinformatics analyses revealed no enrichment of a specific gene function, network, or pathway among genes targeted by retroviral insertions. We conclude that Oct4, Sox2, Klf4, and c-Myc are sufficient to promote fibroblast-to-iPS cell reprogramming and propose that the observed low reprogramming frequencies may have alternative explanations.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hamada, D.</style></author><author><style face="normal" font="default" size="100%">Tanaka, T.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Pawar, A.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Kawamura, M.</style></author><author><style face="normal" font="default" size="100%">Tamura, A.</style></author><author><style face="normal" font="default" size="100%">Tanaka, N.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Competition between folding, native-state dimerisation and amyloid aggregation in beta-lactoglobulin.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2008.12.038</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">386</style></volume><pages><style face="normal" font="default" size="100%">878–890</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We show that a series of peptides corresponding to individual beta-strands in native beta-lactoglobulin readily form amyloid aggregates and that such aggregates are capable of seeding fibril formation by a full-length form of beta-lactoglobulin in which the disulfide bonds are reduced. By contrast, preformed fibrils corresponding to only one of the beta-strands that we considered, betaA, were found to promote fibril formation by a full-length form of beta-lactoglobulin in which the disulfide bonds are intact. These results indicate that regions of high intrinsic aggregation propensity do not give rise to aggregation unless at least partial unfolding takes place. Furthermore, we found that the high aggregation propensity of one of the edge strands, betaI, promotes dimerisation of the native structure rather than misfolding and aggregation since the structure of betaI is stabilised by the presence of a disulfide bond. These findings demonstrate that the interactions that promote folding and native-state oligomerisation can also result in high intrinsic amyloidogenicity. However, we show that the presence of the remainder of the sequence dramatically reduces the net overall aggregation propensity by negative design principles that we suggest are very common in biological systems as a result of evolutionary processes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Varas, F.</style></author><author><style face="normal" font="default" size="100%">Stadtfeld, M.</style></author><author><style face="normal" font="default" size="100%">de Andres-Aguayo, L.</style></author><author><style face="normal" font="default" size="100%">Maherali, N.</style></author><author><style face="normal" font="default" size="100%">di Tullio, A.</style></author><author><style face="normal" font="default" size="100%">Pantano, L.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Hochedlinger, K.</style></author><author><style face="normal" font="default" size="100%">Graf, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fibroblast-derived induced pluripotent stem cells show no common retroviral vector insertions.</style></title><secondary-title><style face="normal" font="default" size="100%">Stem Cells</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1634/stemcells.2008-0696</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">300–306</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Several laboratories have reported the reprogramming of mouse and human fibroblasts into pluripotent cells, using retroviruses carrying the Oct4, Sox2, Klf4, and c-Myc transcription factor genes. In these experiments the frequency of reprogramming was lower than 0.1% of the infected cells, raising the possibility that additional events are required to induce reprogramming, such as activation of genes triggered by retroviral insertions. We have therefore determined by ligation-mediated polymerase chain reaction (LM-PCR) the retroviral insertion sites in six induced pluripotent stem (iPS) cell clones derived from mouse fibroblasts. Seventy-nine insertion sites were assigned to a single mouse genome location. Thirty-five of these mapped to gene transcription units, whereas 29 insertions landed within 10 kilobases of transcription start sites. No common insertion site was detected among the iPS clones studied. Moreover, bioinformatics analyses revealed no enrichment of a specific gene function, network, or pathway among genes targeted by retroviral insertions. We conclude that Oct4, Sox2, Klf4, and c-Myc are sufficient to promote fibroblast-to-iPS cell reprogramming and propose that the observed low reprogramming frequencies may have alternative explanations.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Acquisition of prokaryotic genes by fungal genomes</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Genet.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Correlation between mRNA expression levels and protein aggregation propensities in subcellular localisations.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Biosyst</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1039/b913099n</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">1873–1876</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We investigate the relationship between mRNA expression levels and protein aggregation propensities at the proteomic level, and find that these quantities exhibit a significant correlation when they are averaged across subcellular localisations. In order to investigate this phenomenon, we study the dependence of mRNA expression levels and protein aggregation propensities on the volume of the corresponding subcellular localisations, finding that proteins tend to be increasingly more abundant and more soluble with decreasing volumes of their subcellular localisations. These results indicate that the maintenance of protein solubility plays an even greater role than previously thought in sustaining protein homeostasis.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gauthier, JA</style></author><author><style face="normal" font="default" size="100%">Widmer, E</style></author><author><style face="normal" font="default" size="100%">Bucher, P</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">How much does it cost? Optimization of costs in sequence analysis of social science data</style></title><secondary-title><style face="normal" font="default" size="100%">Sociological Methods and Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">August 2009</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">Issue 1</style></number><volume><style face="normal" font="default" size="100%">Volume 38</style></volume><pages><style face="normal" font="default" size="100%">Pages 197-231</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Capella-Gutiérrez, S.</style></author><author><style face="normal" font="default" size="100%">Silla-Martínez, JM.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btp34</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">15</style></number><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">1972–1973</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">SUMMARY: Multiple sequence alignments are central to many areas of bioinformatics. It has been shown that the removal of poorly aligned regions from an alignment increases the quality of subsequent analyses. Such an alignment trimming phase is complicated in large-scale phylogenetic analyses that deal with thousands of alignments. Here, we present trimAl, a tool for automated alignment trimming, which is especially suited for large-scale phylogenetic analyses. trimAl can consider several parameters, alone or in multiple combinations, for selecting the most reliable positions in the alignment. These include the proportion of sequences with a gap, the level of amino acid similarity and, if several alignments for the same set of sequences are provided, the level of consistency across different alignments. Moreover, trimAl can automatically select the parameters to be used in each specific alignment so that the signal-to-noise ratio is optimized. AVAILABILITY: trimAl has been written in C++, it is portable to all platforms. trimAl is freely available for download (http://trimal.cgenomics.org) and can be used online through the Phylemon web server (http://phylemon2.bioinfo.cipf.es/). Supplementary Material is available at http://trimal.cgenomics.org/publications.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sammeth, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Complete alternative splicing events are bubbles in splicing graphs</style></title><secondary-title><style face="normal" font="default" size="100%">J. Comput. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1089/cmb.2009.0108</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">1117–1140</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Eukaryotic splicing structures are known to involve a high degree of alternative forms derived from a premature transcript by alternative splicing (AS). With the advent of new sequencing technologies, evidence for new splice forms becomes increasingly available-bit by bit revealing that the true splicing diversity of &quot;AS events&quot; often comprises more than two alternatives and therefore cannot be sufficiently described by pairwise comparisons as conducted in analyzes hitherto. Especially, I emphasize on &quot;complete&quot; AS events which include all hitherto known variants of a splicing variation. Challenges emerge from the richness of data (millions of transcripts) and artifacts introduced during the technical process of obtaining transcript sequences (&quot;noise&quot;)-especially when dealing with single-read sequences known as expressed sequence tags (ESTs). Herein, I describe a novel method to efficiently predict AS events in different resolutions (&quot;dimensions&quot;) from transcript annotations that allows for combination of fragmented EST data with full-length cDNAs and can cope with large datasets containing noise. At the doorstep of many new splice forms becoming available by novel high-throughput sequencing technologies, the presented method helps to dynamically update AS databases. Applying this method to estimate the real complexity of alternative splicing, I found in human and murine annotations thousands of novel AS events that either have been disregarded or mischaracterized in earlier works. The growth of evidence for such events suggests that the number still keeps climbing. When considering complete events, the majority of exons that are observed as &quot;mutually exclusive&quot; in pairwise comparisons in fact involves at least one other alternative splice form that disagrees with their mutual exclusion. Similar observations also hold for the alternative skipping of two subsequent exons. Results suggest that the systematical analysis of complete AS events on large scale provides subtle insights in the mechanisms that drive (alternative) splicing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bovine Genome Sequencing</style></author><author><style face="normal" font="default" size="100%">Analysis Consortium</style></author><author><style face="normal" font="default" size="100%">Elsik, CG.</style></author><author><style face="normal" font="default" size="100%">Tellam, RL.</style></author><author><style face="normal" font="default" size="100%">Worley, KC.</style></author><author><style face="normal" font="default" size="100%">Gibbs, RA.</style></author><author><style face="normal" font="default" size="100%">Muzny, DM.</style></author><author><style face="normal" font="default" size="100%">Weinstock, GM.</style></author><author><style face="normal" font="default" size="100%">Adelson, DL.</style></author><author><style face="normal" font="default" size="100%">Eichler, EE.</style></author><author><style face="normal" font="default" size="100%">Elnitski, L.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Hamernik, DL.</style></author><author><style face="normal" font="default" size="100%">Kappes, SM.</style></author><author><style face="normal" font="default" size="100%">Lewin, HA.</style></author><author><style face="normal" font="default" size="100%">Lynn, DJ.</style></author><author><style face="normal" font="default" size="100%">Nicholas, FW.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Rijnkels, M.</style></author><author><style face="normal" font="default" 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face="normal" font="default" size="100%">Sherman, L.</style></author><author><style face="normal" font="default" size="100%">Southey, BR.</style></author><author><style face="normal" font="default" size="100%">Lutzow, YS.</style></author><author><style face="normal" font="default" size="100%">Sweedler, JV.</style></author><author><style face="normal" font="default" size="100%">Tammen, I.</style></author><author><style face="normal" font="default" size="100%">Telugu, BP.</style></author><author><style face="normal" font="default" size="100%">Urbanski, JM.</style></author><author><style face="normal" font="default" size="100%">Utsunomiya, YT.</style></author><author><style face="normal" font="default" size="100%">Verschoor, CP.</style></author><author><style face="normal" font="default" size="100%">Waardenberg, AJ.</style></author><author><style face="normal" font="default" size="100%">Wang, Z.</style></author><author><style face="normal" font="default" size="100%">Ward, R.</style></author><author><style face="normal" font="default" size="100%">Weikard, R.</style></author><author><style face="normal" font="default" size="100%">Welsh, TH.</style></author><author><style face="normal" font="default" size="100%">White, SN.</style></author><author><style face="normal" font="default" size="100%">Wilming, LG.</style></author><author><style face="normal" font="default" size="100%">Wunderlich, KR.</style></author><author><style face="normal" font="default" size="100%">Yang, J.</style></author><author><style face="normal" font="default" size="100%">Zhao, FQ.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The genome sequence of taurine cattle: a window to ruminant biology and evolution.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1126/science.116958</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5926</style></number><volume><style face="normal" font="default" size="100%">324</style></volume><pages><style face="normal" font="default" size="100%">522–528</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Takeuchi, A.</style></author><author><style face="normal" font="default" size="100%">Schmitt, D.</style></author><author><style face="normal" font="default" size="100%">Chapple, C.</style></author><author><style face="normal" font="default" size="100%">Babaylova, E.</style></author><author><style face="normal" font="default" size="100%">Karpova, G.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Krol, A.</style></author><author><style face="normal" font="default" size="100%">Allmang, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A short motif in Drosophila SECIS Binding Protein 2 provides differential binding affinity to SECIS RNA hairpins.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkp07</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">37</style></volume><pages><style face="normal" font="default" size="100%">2126–2141</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Selenoproteins contain the amino acid selenocysteine which is encoded by a UGA Sec codon. Recoding UGA Sec requires a complex mechanism, comprising the cis-acting SECIS RNA hairpin in the 3'UTR of selenoprotein mRNAs, and trans-acting factors. Among these, the SECIS Binding Protein 2 (SBP2) is central to the mechanism. SBP2 has been so far functionally characterized only in rats and humans. In this work, we report the characterization of the Drosophila melanogaster SBP2 (dSBP2). Despite its shorter length, it retained the same selenoprotein synthesis-promoting capabilities as the mammalian counterpart. However, a major difference resides in the SECIS recognition pattern: while human SBP2 (hSBP2) binds the distinct form 1 and 2 SECIS RNAs with similar affinities, dSBP2 exhibits high affinity toward form 2 only. In addition, we report the identification of a K (lysine)-rich domain in all SBP2s, essential for SECIS and 60S ribosomal subunit binding, differing from the well-characterized L7Ae RNA-binding domain. Swapping only five amino acids between dSBP2 and hSBP2 in the K-rich domain conferred reversed SECIS-binding properties to the proteins, thus unveiling an important sequence for form 1 binding.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Calamai, M.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Chiti, F.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutational analysis of the aggregation-prone and disaggregation-prone regions of acylphosphatase.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2008.09.003</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">387</style></volume><pages><style face="normal" font="default" size="100%">965–974</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We have performed an extensive mutational analysis of aggregation and disaggregation of amyloid-like protofibrils of human muscle acylphosphatase. Our findings indicate that the regions that promote aggregation in 25% (v/v) 2,2,2 trifluoroethanol (TFE) are different from those that promote disaggregation under milder conditions (5% TFE). Significant changes in the rate of disaggregation of protofibrils in 5% TFE result not only from mutations situated in the regions of the sequence that play a key role in the mechanism of aggregation in 25% TFE, but also from mutations located in other regions. In order to rationalise these results, we have used a modified version of the Zyggregator aggregation propensity prediction algorithm to take into account structural rearrangements of the protofibrils that may be induced by changes in solution conditions. Our results suggest that a wider range of residues contributes to the stability of the aggregates in addition to those that play an important kinetic role in the aggregation process. The mutational approach described here is capable of providing residue-specific information on the structure and dynamics of amyloid protofibrils under conditions close to physiological and should be widely applicable to other systems.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alkalaeva, E.</style></author><author><style face="normal" font="default" size="100%">Eliseev, B.</style></author><author><style face="normal" font="default" size="100%">Ambrogelly, A.</style></author><author><style face="normal" font="default" size="100%">Vlasov, P.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Gundllapalli, S.</style></author><author><style face="normal" font="default" size="100%">Frolova, L.</style></author><author><style face="normal" font="default" size="100%">Söll, D.</style></author><author><style face="normal" font="default" size="100%">Kisselev, L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Translation termination in pyrrolysine-utilizing archaea.</style></title><secondary-title><style face="normal" font="default" size="100%">FEBS Lett.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.febslet.2009.09.044</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">583</style></volume><pages><style face="normal" font="default" size="100%">3460</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Although some data link archaeal and eukaryotic translation, the overall mechanism of protein synthesis in archaea remains largely obscure. Both archaeal (aRF1) and eukaryotic (eRF1) single release factors recognize all three stop codons. The archaeal genus Methanosarcinaceae contains two aRF1 homologs, and also uses the UAG stop to encode the 22nd amino acid, pyrrolysine. Here we provide an analysis of the last stage of archaeal translation in pyrrolysine-utilizing species. We demonstrated that only one of two Methanosarcina barkeri aRF1 homologs possesses activity and recognizes all three stop codons. The second aRF1 homolog may have another unknown function. The mechanism of pyrrolysine incorporation in the Methanosarcinaceae is discussed.</style></abstract><issue><style face="normal" font="default" size="100%">21</style></issue><section><style face="normal" font="default" size="100%">3455</style></section></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Taddei, A.</style></author><author><style face="normal" font="default" size="100%">Van Houwe, G.</style></author><author><style face="normal" font="default" size="100%">Nagai, S.</style></author><author><style face="normal" font="default" size="100%">Erb, I.</style></author><author><style face="normal" font="default" size="100%">van Nimwegen, E.</style></author><author><style face="normal" font="default" size="100%">Gasser, S.M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The functional importance of telomere clustering: Global changes in gene expression result from SIR factor dispersion</style></title><secondary-title><style face="normal" font="default" size="100%">Genome research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><publisher><style face="normal" font="default" size="100%">Cold Spring Harbor Lab</style></publisher><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">611–625</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The tree versus the forest: the fungal tree of life and the topological diversity within the yeast phylome.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pone.000435</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e4357</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A recurrent topic in phylogenomics is the combination of various sequence alignments to reconstruct a tree that describes the evolutionary relationships within a group of species. However, such approach has been criticized for not being able to properly represent the topological diversity found among gene trees. To evaluate the representativeness of species trees based on concatenated alignments, we reconstruct several fungal species trees and compare them with the complete collection of phylogenies of genes encoded in the Saccharomyces cerevisiae genome. We found that, despite high levels of among-gene topological variation, the species trees do represent widely supported phylogenetic relationships. Most topological discrepancies between gene and species trees are concentrated in certain conflicting nodes. We propose to map such information on the species tree so that it accounts for the levels of congruence across the genome. We identified the lack of sufficient accuracy of current alignment and phylogenetic methods as an important source for the topological diversity encountered among gene trees. Finally, we discuss the implications of the high levels of topological variation for phylogeny-based orthology prediction strategies.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Nagy, A.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Alioto, T.</style></author><author><style face="normal" font="default" size="100%">Patthy, L.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identifying protein-coding genes in genomic sequences.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2009-10-1-20</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">201</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Dessimoz, C.</style></author><author><style face="normal" font="default" size="100%">Huxley-Jones, J.</style></author><author><style face="normal" font="default" size="100%">Vilella, A. J.</style></author><author><style face="normal" font="default" size="100%">Sonnhammer, E. L.</style></author><author><style face="normal" font="default" size="100%">Lewis, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Joining forces in the quest for orthologs</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">403</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marcet-Houben, M.</style></author><author><style face="normal" font="default" size="100%">Marceddu, G.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phylogenomics of the oxidative phosphorylation in fungi reveals extensive gene duplication followed by functional divergence.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Evol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2148-9-295</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">295</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Oxidative phosphorylation is central to the energy metabolism of the cell. Due to adaptation to different life-styles and environments, fungal species have shaped their respiratory pathways in the course of evolution. To identify the main mechanisms behind the evolution of respiratory pathways, we conducted a phylogenomics survey of oxidative phosphorylation components in the genomes of sixty fungal species. RESULTS: Besides clarifying orthology and paralogy relationships among respiratory proteins, our results reveal three parallel losses of the entire complex I, two of which are coupled to duplications in alternative dehydrogenases. Duplications in respiratory proteins have been common, affecting 76% of the protein families surveyed. We detect several instances of paralogs of genes coding for subunits of respiratory complexes that have been recruited to other multi-protein complexes inside and outside the mitochondrion, emphasizing the role of evolutionary tinkering. CONCLUSIONS: Processes of gene loss and gene duplication followed by functional divergence have been rampant in the evolution of fungal respiration. Overall, the core proteins of the respiratory pathways are conserved in most lineages, with major changes affecting the lineages of microsporidia, Schizosaccharomyces and Saccharomyces/Kluyveromyces due to adaptation to anaerobic life-styles. We did not observe specific adaptations of the respiratory metabolism common to all pathogenic species.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Thornton, J.</style></author><author><style face="normal" font="default" size="100%">BioSapiens Network including R. Guigó</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Annotations for all by all - the BioSapiens network.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2009-10-2-401</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">401</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The BioSapiens network has developed a distributed infrastructure for genome and proteome annotation by laboratories anywhere in the world.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ferreira, Pedro Gabriel</style></author><author><style face="normal" font="default" size="100%">Silva, Cândida G.</style></author><author><style face="normal" font="default" size="100%">Azevedo, Paulo J.</style></author><author><style face="normal" font="default" size="100%">Brito, Rui M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatial Clustering of Molecular Dynamics Trajectories in Protein Unfolding Simulations</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin, Heidelberg</style></pub-location><pages><style face="normal" font="default" size="100%">156–166</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-02503-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yanamandra, K.</style></author><author><style face="normal" font="default" size="100%">Alexeyev, O.</style></author><author><style face="normal" font="default" size="100%">Zamotin, V.</style></author><author><style face="normal" font="default" size="100%">Srivastava, V.</style></author><author><style face="normal" font="default" size="100%">Shchukarev, A.</style></author><author><style face="normal" font="default" size="100%">Brorsson, AC.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vogl, T.</style></author><author><style face="normal" font="default" size="100%">Kayed, R.</style></author><author><style face="normal" font="default" size="100%">Wingsle, G.</style></author><author><style face="normal" font="default" size="100%">Olsson, J.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Bergh, A.</style></author><author><style face="normal" font="default" size="100%">Elgh, F.</style></author><author><style face="normal" font="default" size="100%">Morozova-Roche, LA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Amyloid formation by the pro-inflammatory S100A8/A9 proteins in the ageing prostate.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pone.0005562</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e5562</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The conversion of soluble peptides and proteins into polymeric amyloid structures is a hallmark of many age-related degenerative disorders, including Alzheimer's disease, type II diabetes and a variety of systemic amyloidoses. We report here that amyloid formation is linked to another major age-related phenomenon–prostate tissue remodelling in middle-aged and elderly men. METHODOLOGY/PRINCIPAL FINDINGS: By using multidisciplinary analysis of corpora amylacea inclusions in prostate glands of patients diagnosed with prostate cancer we have revealed that their major components are the amyloid forms of S100A8 and S100A9 proteins associated with numerous inflammatory conditions and types of cancer. In prostate protease rich environment the amyloids are stabilized by dystrophic calcification and lateral thickening. We have demonstrated that material closely resembling CA can be produced from S100A8/A9 in vitro under native and acidic conditions and shows the characters of amyloids. This process is facilitated by calcium or zinc, both of which are abundant in ex vivo inclusions. These observations were supported by computational analysis of the S100A8/A9 calcium-dependent aggregation propensity profiles. We found DNA and proteins from Escherichia coli in CA bodies, suggesting that their formation is likely to be associated with bacterial infection. CA inclusions were also accompanied by the activation of macrophages and by an increase in the concentration of S100A8/A9 in the surrounding tissues, indicating inflammatory reactions. CONCLUSIONS/SIGNIFICANCE: These findings, taken together, suggest a link between bacterial infection, inflammation and amyloid deposition of pro-inflammatory proteins S100A8/A9 in the prostate gland, such that a self-perpetuating cycle can be triggered and may increase the risk of malignancy in the ageing prostate. The results provide strong support for the prediction that the generic ability of polypeptide chains to convert into amyloids could lead to their involvement in an increasing number of otherwise apparently unrelated diseases, particularly those associated with ageing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hermoso, A.</style></author><author><style face="normal" font="default" size="100%">Espadaler, J.</style></author><author><style face="normal" font="default" size="100%">Enrique Querol, E.</style></author><author><style face="normal" font="default" size="100%">Aviles, FX.</style></author><author><style face="normal" font="default" size="100%">Sternberg, MJ.</style></author><author><style face="normal" font="default" size="100%">Oliva, B.</style></author><author><style face="normal" font="default" size="100%">Fernandez-Fuentes, N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB).</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinform Biol Insights</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/20066127</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">77–90</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Loops represent an important part of protein structures. The study of loop is critical for two main reasons: First, loops are often involved in protein function, stability and folding. Second, despite improvements in experimental and computational structure prediction methods, modeling the conformation of loops remains problematic. Here, we present a structural classification of loops, ArchDB, a mine of information with application in both mentioned fields: loop structure prediction and function prediction. ArchDB (http://sbi.imim.es/archdb) is a database of classified protein loop motifs. The current database provides four different classification sets tailored for different purposes. ArchDB-40, a loop classification derived from SCOP40, well suited for modeling common loop motifs. Since features relevant to loop structure or function can be more easily determined on well-populated clusters, we have developed ArchDB-95, a loop classification derived from SCOP95. This new classification set shows a  40% increase in the number of subclasses, and a large 7-fold increase in the number of putative structure/function-related subclasses. We also present ArchDB-EC, a classification of loop motifs from enzymes, and ArchDB-KI, a manually annotated classification of loop motifs from kinases. Information about ligand contacts and PDB sites has been included in all classification sets. Improvements in our classification scheme are described, as well as several new database features, such as the ability to query by conserved annotations, sequence similarity, or uploading 3D coordinates of a protein. The lengths of classified loops range between 0 and 36 residues long. ArchDB offers an exhaustive sampling of loop structures. Functional information about loops and links with related biological databases are also provided. All this information and the possibility to browse/query the database through a web-server outline an useful tool with application in the comparative study of loops, the analysis of loops involved in protein function and to obtain templates for loop modeling.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Orobitg, Miquel</style></author><author><style face="normal" font="default" size="100%">Guirado, Fernando</style></author><author><style face="normal" font="default" size="100%">Notredame, Cedric</style></author><author><style face="normal" font="default" size="100%">Cores, Fernando</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploiting parallelism on progressive alignment methods</style></title><secondary-title><style face="normal" font="default" size="100%">The Journal of Supercomputing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s11227-009-0359-5</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Netherlands</style></publisher><pages><style face="normal" font="default" size="100%">1-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">10.1007/s11227-009-0359-5</style></notes></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Manichanh, C.</style></author><author><style face="normal" font="default" size="100%">Chapple, CE.</style></author><author><style face="normal" font="default" size="100%">Frangeul, L.</style></author><author><style face="normal" font="default" size="100%">Gloux, K.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Dore, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A comparison of random sequence reads versus 16S rDNA sequences for estimating the biodiversity of a metagenomic library.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkn49</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">16</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">5180–5188</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The construction of metagenomic libraries has permitted the study of microorganisms resistant to isolation and the analysis of 16S rDNA sequences has been used for over two decades to examine bacterial biodiversity. Here, we show that the analysis of random sequence reads (RSRs) instead of 16S is a suitable shortcut to estimate the biodiversity of a bacterial community from metagenomic libraries. We generated 10,010 RSRs from a metagenomic library of microorganisms found in human faecal samples. Then searched them using the program BLASTN against a prokaryotic sequence database to assign a taxon to each RSR. The results were compared with those obtained by screening and analysing the clones containing 16S rDNA sequences in the whole library. We found that the biodiversity observed by RSR analysis is consistent with that obtained by 16S rDNA. We also show that RSRs are suitable to compare the biodiversity between different metagenomic libraries. RSRs can thus provide a good estimate of the biodiversity of a metagenomic library and, as an alternative to 16S, this approach is both faster and cheaper.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Assis, R.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, AS.</style></author><author><style face="normal" font="default" size="100%">Koonin, EV.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Nested genes and increasing organizational complexity of metazoan genomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Genet.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.tig.2008.08.003</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">475–478</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The most common form of protein-coding gene overlap in eukaryotes is a simple nested structure, whereby one gene is embedded in an intron of another. Analysis of nested protein-coding genes in vertebrates, fruit flies and nematodes revealed substantially higher rates of evolutionary gains than losses. The accumulation of nested gene structures could not be attributed to any obvious functional relationships between the genes involved and represents an increase of the organizational complexity of animal genomes via a neutral process.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Large-scale assignment of orthology: back to phylogenetics?</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2008-9-10-23</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">235</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: Reliable orthology prediction is central to comparative genomics. Although orthology is defined by phylogenetic criteria, most automated prediction methods are based on pairwise sequence comparisons. Recently, automated phylogeny-based orthology prediction has emerged as a feasible alternative for genome-wide studies.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Schmidt, S.</style></author><author><style face="normal" font="default" size="100%">Gerasimova, A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Adzhubei, IA.</style></author><author><style face="normal" font="default" size="100%">Adzuhbei, IA.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, AS.</style></author><author><style face="normal" font="default" size="100%">Sunyaev, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hypermutable non-synonymous sites are under stronger negative selection.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Genet.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pgen.1000281</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e1000281</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Mutation rate varies greatly between nucleotide sites of the human genome and depends both on the global genomic location and the local sequence context of a site. In particular, CpG context elevates the mutation rate by an order of magnitude. Mutations also vary widely in their effect on the molecular function, phenotype, and fitness. Independence of the probability of occurrence of a new mutation's effect has been a fundamental premise in genetics. However, highly mutable contexts may be preserved by negative selection at important sites but destroyed by mutation at sites under no selection. Thus, there may be a positive correlation between the rate of mutations at a nucleotide site and the magnitude of their effect on fitness. We studied the impact of CpG context on the rate of human-chimpanzee divergence and on intrahuman nucleotide diversity at non-synonymous coding sites. We compared nucleotides that occupy identical positions within codons of identical amino acids and only differ by being within versus outside CpG context. Nucleotides within CpG context are under a stronger negative selection, as revealed by their lower, proportionally to the mutation rate, rate of evolution and nucleotide diversity. In particular, the probability of fixation of a non-synonymous transition at a CpG site is two times lower than at a CpG site. Thus, sites with different mutation rates are not necessarily selectively equivalent. This suggests that the mutation rate may complement sequence conservation as a characteristic predictive of functional importance of nucleotide sites.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wilm, A.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">R-Coffee: a method for multiple alignment of non-coding RNA</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Nucleic Acid Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Untranslated/ chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">e52</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">R-Coffee is a multiple RNA alignment package, derived from T-Coffee, designed to align RNA sequences while exploiting secondary structure information. R-Coffee uses an alignment-scoring scheme that incorporates secondary structure information within the alignment. It works particularly well as an alignment improver and can be combined with any existing sequence alignment method. In this work, we used R-Coffee to compute multiple sequence alignments combining the pairwise output of sequence aligners and structural aligners. We show that R-Coffee can improve the accuracy of all the sequence aligners. We also show that the consistency-based component of T-Coffee can improve the accuracy of several structural aligners. R-Coffee was tested on 388 BRAliBase reference datasets and on 11 longer Cmfinder datasets. Altogether our results suggest that the best protocol for aligning short sequences (less than 200 nt) is the combination of R-Coffee with the RNA pairwise structural aligner Consan. We also show that the simultaneous combination of the four best sequence alignment programs with R-Coffee produces alignments almost as accurate as those obtained with R-Coffee/Consan. Finally, we show that R-Coffee can also be used to align longer datasets beyond the usual scope of structural aligners. R-Coffee is freely available for download, along with documentation, from the T-Coffee web site (www.tcoffee.org).</style></abstract><accession-num><style face="normal" font="default" size="100%">18420654</style></accession-num><notes><style face="normal" font="default" size="100%">Evaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Ireland.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">BioMoby Consortium</style></author><author><style face="normal" font="default" size="100%">Wilkinson, MD.</style></author><author><style face="normal" font="default" size="100%">Senger, M.</style></author><author><style face="normal" font="default" size="100%">Kawas, E.</style></author><author><style face="normal" font="default" size="100%">Bruskiewich, R.</style></author><author><style face="normal" font="default" size="100%">Gouzy, J.</style></author><author><style face="normal" font="default" size="100%">Noirot, C.</style></author><author><style face="normal" font="default" size="100%">Bardou, P.</style></author><author><style face="normal" font="default" size="100%">Ng, A.</style></author><author><style face="normal" font="default" size="100%">Haase, D.</style></author><author><style face="normal" font="default" size="100%">Saiz, Ede A.</style></author><author><style face="normal" font="default" size="100%">Wang, D.</style></author><author><style face="normal" font="default" size="100%">Gibbons, F.</style></author><author><style face="normal" font="default" size="100%">Gordon, PM.</style></author><author><style face="normal" font="default" size="100%">Sensen, CW.</style></author><author><style face="normal" font="default" size="100%">Carrasco, JM.</style></author><author><style face="normal" font="default" size="100%">Fernández, JM.</style></author><author><style face="normal" font="default" size="100%">Shen, L.</style></author><author><style face="normal" font="default" size="100%">Links, M.</style></author><author><style face="normal" font="default" size="100%">Ng, M.</style></author><author><style face="normal" font="default" size="100%">Opushneva, N.</style></author><author><style face="normal" font="default" size="100%">Neerincx, PB.</style></author><author><style face="normal" font="default" size="100%">Leunissen, JA.</style></author><author><style face="normal" font="default" size="100%">Ernst, R.</style></author><author><style face="normal" font="default" size="100%">Twigger, S.</style></author><author><style face="normal" font="default" size="100%">Usadel, B.</style></author><author><style face="normal" font="default" size="100%">Good, B.</style></author><author><style face="normal" font="default" size="100%">Wong, Y.</style></author><author><style face="normal" font="default" size="100%">Stein, L.</style></author><author><style face="normal" font="default" size="100%">Crosby, W.</style></author><author><style face="normal" font="default" size="100%">Karlsson, J.</style></author><author><style face="normal" font="default" size="100%">Royo, R.</style></author><author><style face="normal" font="default" size="100%">Párraga, I.</style></author><author><style face="normal" font="default" size="100%">Ramírez, S.</style></author><author><style face="normal" font="default" size="100%">Gelpi, JL.</style></author><author><style face="normal" font="default" size="100%">Trelles, O.</style></author><author><style face="normal" font="default" size="100%">Pisano, DG.</style></author><author><style face="normal" font="default" size="100%">Jimenez, N.</style></author><author><style face="normal" font="default" size="100%">Kerhornou, A.</style></author><author><style face="normal" font="default" size="100%">Rosset, R.</style></author><author><style face="normal" font="default" size="100%">Zamacola, L.</style></author><author><style face="normal" font="default" size="100%">Tarraga, J.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Carazo, JM.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Navarro, A.</style></author><author><style face="normal" font="default" size="100%">Orozco, M.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Claros, MG.</style></author><author><style face="normal" font="default" size="100%">Pérez, AJ.</style></author><author><style face="normal" font="default" size="100%">Aldana, J.</style></author><author><style face="normal" font="default" size="100%">Rojano, MM.</style></author><author><style face="normal" font="default" size="100%">Fernandez-Santa Cruz, R.</style></author><author><style face="normal" font="default" size="100%">Navas, I.</style></author><author><style face="normal" font="default" size="100%">Schiltz, G.</style></author><author><style face="normal" font="default" size="100%">Farmer, A.</style></author><author><style face="normal" font="default" size="100%">Gessler, D.</style></author><author><style face="normal" font="default" size="100%">Schoof, H.</style></author><author><style face="normal" font="default" size="100%">Groscurth, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interoperability with Moby 1.0–it's better than sharing your toothbrush!</style></title><secondary-title><style face="normal" font="default" size="100%">Brief. Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bib/bbn00</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">220–231</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">STAR Consortium</style></author><author><style face="normal" font="default" size="100%">Saar, K.</style></author><author><style face="normal" font="default" size="100%">Beck, A.</style></author><author><style face="normal" font="default" size="100%">Bihoreau, MT.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Brocklebank, D.</style></author><author><style face="normal" font="default" size="100%">Chen, Y.</style></author><author><style face="normal" font="default" size="100%">Cuppen, E.</style></author><author><style face="normal" font="default" size="100%">Demonchy, S.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Flicek, P.</style></author><author><style face="normal" font="default" size="100%">Foglio, M.</style></author><author><style face="normal" font="default" size="100%">Fujiyama, A.</style></author><author><style face="normal" font="default" size="100%">Gut, IG.</style></author><author><style face="normal" font="default" size="100%">Gauguier, D.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Guryev, V.</style></author><author><style face="normal" font="default" size="100%">Heinig, M.</style></author><author><style face="normal" font="default" size="100%">Hummel, O.</style></author><author><style face="normal" font="default" size="100%">Jahn, N.</style></author><author><style face="normal" font="default" size="100%">Klages, S.</style></author><author><style face="normal" font="default" size="100%">Kren, V.</style></author><author><style face="normal" font="default" size="100%">Kube, M.</style></author><author><style face="normal" font="default" size="100%">Kuhl, H.</style></author><author><style face="normal" font="default" size="100%">Kuramoto, T.</style></author><author><style face="normal" font="default" size="100%">Kuroki, Y.</style></author><author><style face="normal" font="default" size="100%">Lechner, D.</style></author><author><style face="normal" font="default" size="100%">Lee, YA.</style></author><author><style face="normal" font="default" size="100%">Lopez-Bigas, N.</style></author><author><style face="normal" font="default" size="100%">Lathrop, GM.</style></author><author><style face="normal" font="default" size="100%">Mashimo, T.</style></author><author><style face="normal" font="default" size="100%">Medina, I.</style></author><author><style face="normal" font="default" size="100%">Mott, R.</style></author><author><style face="normal" font="default" size="100%">Patone, G.</style></author><author><style face="normal" font="default" size="100%">Perrier-Cornet, JA.</style></author><author><style face="normal" font="default" size="100%">Platzer, M.</style></author><author><style face="normal" font="default" size="100%">Pravenec, M.</style></author><author><style face="normal" font="default" size="100%">Reinhardt, R.</style></author><author><style face="normal" font="default" size="100%">Sakaki, Y.</style></author><author><style face="normal" font="default" size="100%">Schilhabel, M.</style></author><author><style face="normal" font="default" size="100%">Schulz, H.</style></author><author><style face="normal" font="default" size="100%">Serikawa, T.</style></author><author><style face="normal" font="default" size="100%">Shikhagaie, M.</style></author><author><style face="normal" font="default" size="100%">Tatsumoto, S.</style></author><author><style face="normal" font="default" size="100%">Taudien, S.</style></author><author><style face="normal" font="default" size="100%">Toyoda, A.</style></author><author><style face="normal" font="default" size="100%">Voigt, B.</style></author><author><style face="normal" font="default" size="100%">Zelenika, D.</style></author><author><style face="normal" font="default" size="100%">Zimdahl, H.</style></author><author><style face="normal" font="default" size="100%">Hubner, N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SNP and haplotype mapping for genetic analysis in the rat.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Genet.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/ng.12</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">560–566</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rivers, RC.</style></author><author><style face="normal" font="default" size="100%">Kumita, JR.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Dedmon, MM.</style></author><author><style face="normal" font="default" size="100%">Pawar, A.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Christodoulou, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Molecular determinants of the aggregation behavior of alpha- and beta-synuclein.</style></title><secondary-title><style face="normal" font="default" size="100%">Protein Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1110/ps.073181508</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">887–898</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Alpha- and beta-synuclein are closely related proteins, the first of which is associated with deposits formed in neurodegenerative conditions such as Parkinson's disease while the second appears to have no relationship to any such disorders. The aggregation behavior of alpha- and beta-synuclein as well as a series of chimeric variants were compared by exploring the structural transitions that occur in the presence of a widely used lipid mimetic, sodium dodecyl sulfate (SDS). We found that the aggregation rates of all these protein variants are significantly enhanced by low concentrations of SDS. In particular, we inserted the 11-residue sequence of mainly hydrophobic residues from the non-amyloid-beta-component (NAC) region of alpha-synuclein into beta-synuclein and show that the fibril formation rate of this chimeric protein is only weakly altered from that of beta-synuclein. These intrinsic propensities to aggregate are rationalized to a very high degree of accuracy by analysis of the sequences in terms of their associated physicochemical properties. The results begin to reveal that the differences in behavior are primarily associated with a delicate balance between the positions of a range of charged and hydrophobic residues rather than the commonly assumed presence or absence of the highly aggregation-prone region of the NAC region of alpha-synuclein. This conclusion provides new insights into the role of alpha-synuclein in disease and into the factors that regulate the balance between solubility and aggregation of a natively unfolded protein.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moretti, S.</style></author><author><style face="normal" font="default" size="100%">Wilm, A.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author><author><style face="normal" font="default" size="100%">Xenarios, I.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">R-Coffee: a web server for accurately aligning noncoding RNA sequences</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Nucleic Acid Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Untranslated/ chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">W10-3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The R-Coffee web server produces highly accurate multiple alignments of noncoding RNA (ncRNA) sequences, taking into account predicted secondary structures. R-Coffee uses a novel algorithm recently incorporated in the T-Coffee package. R-Coffee works along the same lines as T-Coffee: it uses pairwise or multiple sequence alignment (MSA) methods to compute a primary library of input alignments. The program then computes an MSA highly consistent with both the alignments contained in the library and the secondary structures associated with the sequences. The secondary structures are predicted using RNAplfold. The server provides two modes. The slow/accurate mode is restricted to small datasets (less than 5 sequences less than 150 nucleotides) and combines R-Coffee with Consan, a very accurate pairwise RNA alignment method. For larger datasets a fast method can be used (RM-Coffee mode), that uses R-Coffee to combine the output of the three packages which combines the outputs from programs found to perform best on RNA (MUSCLE, MAFFT and ProbConsRNA). Our BRAliBase benchmarks indicate that the R-Coffee/Consan combination is one of the best ncRNA alignment methods for short sequences, while the RM-Coffee gives comparable results on longer sequences. The R-Coffee web server is available at http://www.tcoffee.org.</style></abstract><accession-num><style face="normal" font="default" size="100%">18483080</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Swiss Institute of Bioinformatics (SIB), Quartier Sorge - Genopode, UNIL, CH-1015 Lausanne, Switzerland.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Djebali, S.</style></author><author><style face="normal" font="default" size="100%">Kapranov, P.</style></author><author><style face="normal" font="default" size="100%">Foissac, S.</style></author><author><style face="normal" font="default" size="100%">Lagarde, J.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Wyss, C.</style></author><author><style face="normal" font="default" size="100%">Drenkow, J.</style></author><author><style face="normal" font="default" size="100%">Dumais, E.</style></author><author><style face="normal" font="default" size="100%">Murray, RR.</style></author><author><style face="normal" font="default" size="100%">Lin, C.</style></author><author><style face="normal" font="default" size="100%">Szeto, D.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Calvo, M.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Makrythanasis, P.</style></author><author><style face="normal" font="default" size="100%">Vidal, M.</style></author><author><style face="normal" font="default" size="100%">Salehi-Ashtiani, K.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Efficient targeted transcript discovery via array-based normalization of RACE libraries.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Methods</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nmeth.121</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">629–635</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Rapid amplification of cDNA ends (RACE) is a widely used approach for transcript identification. Random clone selection from the RACE mixture, however, is an ineffective sampling strategy if the dynamic range of transcript abundances is large. To improve sampling efficiency of human transcripts, we hybridized the products of the RACE reaction onto tiling arrays and used the detected exons to delineate a series of reverse-transcriptase (RT)-PCRs, through which the original RACE transcript population was segregated into simpler transcript populations. We independently cloned the products and sequenced randomly selected clones. This approach, RACEarray, is superior to direct cloning and sequencing of RACE products because it specifically targets new transcripts and often results in overall normalization of transcript abundance. We show theoretically and experimentally that this strategy leads indeed to efficient sampling of new transcripts, and we investigated multiplexing the strategy by pooling RACE reactions from multiple interrogated loci before hybridization.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Zyggregator method for predicting protein aggregation propensities.</style></title><secondary-title><style face="normal" font="default" size="100%">Chem Soc Rev</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1039/b706784b</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">37</style></volume><pages><style face="normal" font="default" size="100%">1395–1401</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Protein aggregation causes many devastating neurological and systemic diseases and represents a major problem in the preparation of recombinant proteins in biotechnology. Major advances in understanding the causes of this phenomenon have been made through the realisation that the analysis of the physico-chemical characteristics of the amino acids can provide accurate predictions about the rates of growth of the misfolded assemblies and the specific regions of the sequences that promote aggregation. More recently it has also been shown that the toxicity in vivo of protein aggregates can be predicted by estimating the propensity of polypeptide chains to form protofibrillar assemblies. In this tutorial review we describe the development of these predictions made through the Zyggregator method and the applications that have been explored so far.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Roma, G.</style></author><author><style face="normal" font="default" size="100%">Sardiello, M.</style></author><author><style face="normal" font="default" size="100%">Cobellis, G.</style></author><author><style face="normal" font="default" size="100%">Cruz, P.</style></author><author><style face="normal" font="default" size="100%">Lago, G.</style></author><author><style face="normal" font="default" size="100%">Sanges, R.</style></author><author><style face="normal" font="default" size="100%">Stupka, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The UniTrap resource: tools for the biologist enabling optimized use of gene trap clones.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkm825</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">D741–D746</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We have developed a comprehensive resource devoted to biologists wanting to optimize the use of gene trap clones in their experiments. We have processed 300 602 such clones from both public and private projects to generate 28,199 'UniTraps', i.e. distinct collections of unambiguous insertions at the same subgenic region of annotated genes. The UniTrap resource contains data relative to 9583 trapped genes, which represent 42.3% of the mouse gene content. Among the trapped genes, 7,728 have a counterpart in humans, and 677 are known to be involved in the pathogenesis of human diseases. The aim of this analysis is to provide the wet lab researchers with a comprehensive database and curated tools for (i) identifying and comparing the clones carrying a trap into the genes of interest, (ii) evaluating the severity of the mutation to the protein function in each independent trapping event and (iii) supplying complete information to perform PCR, RT-PCR and restriction experiments to verify the clone and identify the exact point of vector insertion. To share this unique resource with the scientific community, we have designed and implemented a web interface that is freely accessible at http://unitrap.cbm.fvg.it/.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Bueno, A.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PhylomeDB: a database for genome-wide collections of gene phylogenies.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkm89</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">D491–D496</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The complete collection of evolutionary histories of all genes in a genome, also known as phylome, constitutes a valuable source of information. The reconstruction of phylomes has been previously prevented by large demands of time and computer power, but is now feasible thanks to recent developments in computers and algorithms. To provide a publicly available repository of complete phylomes that allows researchers to access and store large-scale phylogenomic analyses, we have developed PhylomeDB. PhylomeDB is a database of complete phylomes derived for different genomes within a specific taxonomic range. All phylomes in the database are built using a high-quality phylogenetic pipeline that includes evolutionary model testing and alignment trimming phases. For each genome, PhylomeDB provides the alignments, phylogentic trees and tree-based orthology predictions for every single encoded protein. The current version of PhylomeDB includes the phylomes of Human, the yeast Saccharomyces cerevisiae and the bacterium Escherichia coli, comprising a total of 32 289 seed sequences with their corresponding alignments and 172 324 phylogenetic trees. PhylomeDB can be publicly accessed at http://phylomedb.bioinfo.cipf.es.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castellano, S.</style></author><author><style face="normal" font="default" size="100%">Gladyshev, VN.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Berry, MJ.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SelenoDB 1.0 : a database of selenoprotein genes, proteins and SECIS elements.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkm73</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">D332–D338</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Selenoproteins are a diverse group of proteins usually misidentified and misannotated in sequence databases. The presence of an in-frame UGA (stop) codon in the coding sequence of selenoprotein genes precludes their identification and correct annotation. The in-frame UGA codons are recoded to cotranslationally incorporate selenocysteine, a rare selenium-containing amino acid. The development of ad hoc experimental and, more recently, computational approaches have allowed the efficient identification and characterization of the selenoproteomes of a growing number of species. Today, dozens of selenoprotein families have been described and more are being discovered in recently sequenced species, but the correct genomic annotation is not available for the majority of these genes. SelenoDB is a long-term project that aims to provide, through the collaborative effort of experimental and computational researchers, automatic and manually curated annotations of selenoprotein genes, proteins and SECIS elements. Version 1.0 of the database includes an initial set of eukaryotic genomic annotations, with special emphasis on the human selenoproteome, for immediate inspection by selenium researchers or incorporation into more general databases. SelenoDB is freely available at http://www.selenodb.org.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Bueno, A.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PhylomeDB: a database for genome-wide collections of gene phylogenies.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkm899</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">D491–D496</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The complete collection of evolutionary histories of all genes in a genome, also known as phylome, constitutes a valuable source of information. The reconstruction of phylomes has been previously prevented by large demands of time and computer power, but is now feasible thanks to recent developments in computers and algorithms. To provide a publicly available repository of complete phylomes that allows researchers to access and store large-scale phylogenomic analyses, we have developed PhylomeDB. PhylomeDB is a database of complete phylomes derived for different genomes within a specific taxonomic range. All phylomes in the database are built using a high-quality phylogenetic pipeline that includes evolutionary model testing and alignment trimming phases. For each genome, PhylomeDB provides the alignments, phylogentic trees and tree-based orthology predictions for every single encoded protein. The current version of PhylomeDB includes the phylomes of Human, the yeast Saccharomyces cerevisiae and the bacterium Escherichia coli, comprising a total of 32 289 seed sequences with their corresponding alignments and 172 324 phylogenetic trees. PhylomeDB can be publicly accessed at http://phylomedb.bioinfo.cipf.es.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Piqué, M.</style></author><author><style face="normal" font="default" size="100%">López, JM.</style></author><author><style face="normal" font="default" size="100%">Foissac, S.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Méndez, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A combinatorial code for CPE-mediated translational control.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.cell.2007.12.03</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">132</style></volume><pages><style face="normal" font="default" size="100%">434–448</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Cytoplasmic polyadenylation plays a key role in the translational control of mRNAs driving biological processes such as gametogenesis, cell-cycle progression, and synaptic plasticity. What determines the distinct time of polyadenylation and extent of translational control of a given mRNA, however, is poorly understood. The polyadenylation-regulated translation is controlled by the cytoplasmic polyadenylation element (CPE) and its binding protein, CPEB, which can assemble both translational repression or activation complexes. Using a combination of mutagenesis and experimental validation of genome-wide computational predictions, we show that the number and relative position of two elements, the CPE and the Pumilio-binding element, with respect to the polyadenylation signal define a combinatorial code that determines whether an mRNA will be translationally repressed by CPEB, as well as the extent and time of cytoplasmic polyadenylation-dependent translational activation.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gómez, A.</style></author><author><style face="normal" font="default" size="100%">Cedano, J.</style></author><author><style face="normal" font="default" size="100%">Espadaler, J.</style></author><author><style face="normal" font="default" size="100%">Hermoso, A.</style></author><author><style face="normal" font="default" size="100%">Piñol, J.</style></author><author><style face="normal" font="default" size="100%">Querol, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of protein function improving sequence remote alignment search by a fuzzy logic algorithm.</style></title><secondary-title><style face="normal" font="default" size="100%">Protein J.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s10930-007-9116-x</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">130–139</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The functional annotation of the new protein sequences represents a major drawback for genomic science. The best way to suggest the function of a protein from its sequence is by finding a related one for which biological information is available. Current alignment algorithms display a list of protein sequence stretches presenting significant similarity to different protein targets, ordered by their respective mathematical scores. However, statistical and biological significance do not always coincide, therefore, the rearrangement of the program output according to more biological characteristics than the mathematical scoring would help functional annotation. A new method that predicts the putative function for the protein integrating the results from the PSI-BLAST program and a fuzzy logic algorithm is described. Several protein sequence characteristics have been checked in their ability to rearrange a PSI-BLAST profile according more to their biological functions. Four of them: amino acid content, matched segment length and hydropathic and flexibility profiles positively contributed, upon being integrated by a fuzzy logic algorithm into a program, BYPASS, to the accurate prediction of the function of a protein from its sequence.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards quantitative predictions in cell biology using chemical properties of proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Biosyst</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1039/b805710a</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">1170–1175</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">It has recently been suggested that the concentrations of proteins in the cell are tuned towards their critical values, and that the alteration of this balance often results in misfolding diseases. This concept is intriguing because the in vivo concentrations of proteins are closely regulated by complex cellular processes, while their critical concentrations are primarily determined by the chemical characters of their amino acid sequences. We discuss here how the presence of a link between the upper levels of in vivo concentrations and critical concentrations offers an opportunity to make quantitative predictions in cell biology based on the chemical properties of proteins.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rausch, T.</style></author><author><style face="normal" font="default" size="100%">Emde, A. K.</style></author><author><style face="normal" font="default" size="100%">Weese, D.</style></author><author><style face="normal" font="default" size="100%">Doring, A.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Reinert, K.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Segment-based multiple sequence alignment</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug 15</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">16</style></number><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">i187-92</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: Many multiple sequence alignment tools have been developed in the past, progressing either in speed or alignment accuracy. Given the importance and wide-spread use of alignment tools, progress in both categories is a contribution to the community and has driven research in the field so far. RESULTS: We introduce a graph-based extension to the consistency-based, progressive alignment strategy. We apply the consistency notion to segments instead of single characters. The main problem we solve in this context is to define segments of the sequences in such a way that a graph-based alignment is possible. We implemented the algorithm using the SeqAn library and report results on amino acid and DNA sequences. The benefit of our approach is threefold: (1) sequences with conserved blocks can be rapidly aligned, (2) the implementation is conceptually easy, generic and fast and (3) the consistency idea can be extended to align multiple genomic sequences. AVAILABILITY: The segment-based multiple sequence alignment tool can be downloaded from http://www.seqan.de/projects/msa.html. A novel version of T-Coffee interfaced with the tool is available from http://www.tcoffee.org. The usage of the tool is described in both documentations.</style></abstract><accession-num><style face="normal" font="default" size="100%">18689823</style></accession-num><notes><style face="normal" font="default" size="100%">Journal Article</style></notes><auth-address><style face="normal" font="default" size="100%">International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr 63-73, 14195 Berlin, Germany. rausch@inf.fu-berlin.de</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Donaldson, ZR.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Putnam, A.</style></author><author><style face="normal" font="default" size="100%">Bai, Y.</style></author><author><style face="normal" font="default" size="100%">Stoinski, TL.</style></author><author><style face="normal" font="default" size="100%">Hammock, EA.</style></author><author><style face="normal" font="default" size="100%">Young, LJ.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of a behavior-linked microsatellite-containing element in the 5' flanking region of the primate AVPR1A gene.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Evol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2148-8-180</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">180</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The arginine vasopressin V1a receptor (V1aR) modulates social cognition and behavior in a wide variety of species. Variation in a repetitive microsatellite element in the 5' flanking region of the V1aR gene (AVPR1A) in rodents has been associated with variation in brain V1aR expression and in social behavior. In humans, the 5' flanking region of AVPR1A contains a tandem duplication of two approximately 350 bp, microsatellite-containing elements located approximately 3.5 kb upstream of the transcription start site. The first block, referred to as DupA, contains a polymorphic (GT)25 microsatellite; the second block, DupB, has a complex (CT)4-(TT)-(CT)8-(GT)24 polymorphic motif, known as RS3. Polymorphisms in RS3 have been associated with variation in sociobehavioral traits in humans, including autism spectrum disorders. Thus, evolution of these regions may have contributed to variation in social behavior in primates. We examined the structure of these regions in six ape, six monkey, and one prosimian species. RESULTS: Both tandem repeat blocks are present upstream of the AVPR1A coding region in five of the ape species we investigated, while monkeys have only one copy of this region. As in humans, the microsatellites within DupA and DupB are polymorphic in many primate species. Furthermore, both single (lacking DupB) and duplicated alleles (containing both DupA and DupB) are present in chimpanzee (Pan troglodytes) populations with allele frequencies of 0.795 and 0.205 for the single and duplicated alleles, respectively, based on the analysis of 47 wild-caught individuals. Finally, a phylogenetic reconstruction suggests two alternate evolutionary histories for this locus. CONCLUSION: There is no obvious relationship between the presence of the RS3 duplication and social organization in primates. However, polymorphisms identified in some species may be useful in future genetic association studies. In particular, the presence of both single and duplicated alleles in chimpanzees provides a unique opportunity to assess the functional role of this duplication in contributing to variation in social behavior in primates. While our initial studies show no signs of directional selection on this locus in chimps, pharmacological and genetic association studies support a potential role for this region in influencing V1aR expression and social behavior.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Schlecht, U.</style></author><author><style face="normal" font="default" size="100%">Erb, I.</style></author><author><style face="normal" font="default" size="100%">Demougin, P.</style></author><author><style face="normal" font="default" size="100%">Robine, N.</style></author><author><style face="normal" font="default" size="100%">Borde, V.</style></author><author><style face="normal" font="default" size="100%">van Nimwegen, E.</style></author><author><style face="normal" font="default" size="100%">Nicolas, A.</style></author><author><style face="normal" font="default" size="100%">Primig, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide expression profiling, in vivo DNA binding analysis, and probabilistic motif prediction reveal novel Abf1 target genes during fermentation, respiration, and sporulation in yeast</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Biology of the Cell</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><number><style face="normal" font="default" size="100%">5</style></number><publisher><style face="normal" font="default" size="100%">Am Soc Cell Biol</style></publisher><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">2193–2207</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Pignatelli, M.</style></author><author><style face="normal" font="default" size="100%">Beltran, S.</style></author><author><style face="normal" font="default" size="100%">Punset, A.</style></author><author><style face="normal" font="default" size="100%">Pérez-Lluch, S.</style></author><author><style face="normal" font="default" size="100%">Serras, F.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Corominas, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Conserved chromosomal clustering of genes governed by chromatin regulators in Drosophila.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2008-9-9-r13</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">R134</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The trithorax group (trxG) and Polycomb group (PcG) proteins are responsible for the maintenance of stable transcriptional patterns of many developmental regulators. They bind to specific regions of DNA and direct the post-translational modifications of histones, playing a role in the dynamics of chromatin structure. RESULTS: We have performed genome-wide expression studies of trx and ash2 mutants in Drosophila melanogaster. Using computational analysis of our microarray data, we have identified 25 clusters of genes potentially regulated by TRX. Most of these clusters consist of genes that encode structural proteins involved in cuticle formation. This organization appears to be a distinctive feature of the regulatory networks of TRX and other chromatin regulators, since we have observed the same arrangement in clusters after experiments performed with ASH2, as well as in experiments performed by others with NURF, dMyc, and ASH1. We have also found many of these clusters to be significantly conserved in D. simulans, D. yakuba, D. pseudoobscura and partially in Anopheles gambiae. CONCLUSION: The analysis of genes governed by chromatin regulators has led to the identification of clusters of functionally related genes conserved in other insect species, suggesting this chromosomal organization is biologically important. Moreover, our results indicate that TRX and other chromatin regulators may act globally on chromatin domains that contain transcriptionally co-regulated genes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chapple, CE.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Relaxation of selective constraints causes independent selenoprotein extinction in insect genomes.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pone.000296</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">e2968</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Selenoproteins are a diverse family of proteins notable for the presence of the 21st amino acid, selenocysteine. Until very recently, all metazoan genomes investigated encoded selenoproteins, and these proteins had therefore been believed to be essential for animal life. Challenging this assumption, recent comparative analyses of insect genomes have revealed that some insect genomes appear to have lost selenoprotein genes. METHODOLOGY/PRINCIPAL FINDINGS: In this paper we investigate in detail the fate of selenoproteins, and that of selenoprotein factors, in all available arthropod genomes. We use a variety of in silico comparative genomics approaches to look for known selenoprotein genes and factors involved in selenoprotein biosynthesis. We have found that five insect species have completely lost the ability to encode selenoproteins and that selenoprotein loss in these species, although so far confined to the Endopterygota infraclass, cannot be attributed to a single evolutionary event, but rather to multiple, independent events. Loss of selenoproteins and selenoprotein factors is usually coupled to the deletion of the entire no-longer functional genomic region, rather than to sequence degradation and consequent pseudogenisation. Such dynamics of gene extinction are consistent with the high rate of genome rearrangements observed in Drosophila. We have also found that, while many selenoprotein factors are concomitantly lost with the selenoproteins, others are present and conserved in all investigated genomes, irrespective of whether they code for selenoproteins or not, suggesting that they are involved in additional, non-selenoprotein related functions. CONCLUSIONS/SIGNIFICANCE: Selenoproteins have been independently lost in several insect species, possibly as a consequence of the relaxation in insects of the selective constraints acting across metazoans to maintain selenoproteins. The dispensability of selenoproteins in insects may be related to the fundamental differences in antioxidant defense between these animals and other metazoans.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sammeth, M.</style></author><author><style face="normal" font="default" size="100%">Foissac, S.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A general definition and nomenclature for alternative splicing events.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pcbi.100014</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e1000147</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells is one of the most challenging tasks in the postgenomic era. In this regard, alternative splicing (AS) is a key phenomenon contributing to the production of different mature transcripts from the same primary RNA sequence. As a plethora of different transcript forms is available in databases, a first step to uncover the biology that drives AS is to identify the different types of reflected splicing variation. In this work, we present a general definition of the AS event along with a notation system that involves the relative positions of the splice sites. This nomenclature univocally and dynamically assigns a specific &quot;AS code&quot; to every possible pattern of splicing variation. On the basis of this definition and the corresponding codes, we have developed a computational tool (AStalavista) that automatically characterizes the complete landscape of AS events in a given transcript annotation of a genome, thus providing a platform to investigate the transcriptome diversity across genes, chromosomes, and species. Our analysis reveals that a substantial part–in human more than a quarter-of the observed splicing variations are ignored in common classification pipelines. We have used AStalavista to investigate and to compare the AS landscape of different reference annotation sets in human and in other metazoan species and found that proportions of AS events change substantially depending on the annotation protocol, species-specific attributes, and coding constraints acting on the transcripts. The AStalavista system therefore provides a general framework to conduct specific studies investigating the occurrence, impact, and regulation of AS.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Weng, Z.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">In silico meets in vivo.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2008-9-2-30</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">302</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A report of the 6th Georgia Tech-Oak Ridge National Lab International Conference on Bioinformatics 'In silico Biology: Gene Discovery and Systems Genomics', Atlanta, USA, 15-17 November, 2007.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arkhipov, Vladimir Y.</style></author><author><style face="normal" font="default" size="100%">Koblik, Evgeny A.</style></author><author><style face="normal" font="default" size="100%">Redkin, Yaroslav A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Birds of the Krasnoye Lake area (South Chukotka)</style></title><secondary-title><style face="normal" font="default" size="100%">Arch Zool Mus MGU</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">159-183</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Avifaunal research in Krasnoye Lake area, South Chukotka, Russia (N 64</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Meehan, S.</style></author><author><style face="normal" font="default" size="100%">Knowles, TP.</style></author><author><style face="normal" font="default" size="100%">Baldwin, AJ.</style></author><author><style face="normal" font="default" size="100%">Smith, JF.</style></author><author><style face="normal" font="default" size="100%">Squires, AM.</style></author><author><style face="normal" font="default" size="100%">Clements, P.</style></author><author><style face="normal" font="default" size="100%">Treweek, TM.</style></author><author><style face="normal" font="default" size="100%">Ecroyd, H.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Macphee, CE.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Carver, JA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterisation of amyloid fibril formation by small heat-shock chaperone proteins human alphaA-, alphaB- and R120G alphaB-crystallins.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2007.06.060</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">372</style></volume><pages><style face="normal" font="default" size="100%">470–484</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">AlphaB-Crystallin is a ubiquitous small heat-shock protein (sHsp) renowned for its chaperone ability to prevent target protein aggregation. It is stress-inducible and its up-regulation is associated with a number of disorders, including those linked to the deposition of misfolded proteins, such as Alzheimer's and Parkinson's diseases. We have characterised the formation of amyloid fibrils by human alphaB-crystallin in detail, and also that of alphaA-crystallin and the disease-related mutant R120G alphaB-crystallin. We find that the last 12 amino acid residues of the C-terminal region of alphaB-crystallin are predicted from their physico-chemical properties to have a very low propensity to aggregate. (1)H NMR spectroscopy reveals that this hydrophilic C-terminal region is flexible both in its solution state and in amyloid fibrils, where it protrudes from the fibrillar core. We demonstrate, in addition, that the equilibrium between different protofilament assemblies can be manipulated and controlled in vitro to select for particular alphaB-crystallin amyloid morphologies. Overall, this study suggests that there could be a fine balance in vivo between the native functional sHsp state and the formation of amyloid fibrils.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Peretó, J.</style></author><author><style face="normal" font="default" size="100%">Montero, F.</style></author><author><style face="normal" font="default" size="100%">Gil, R.</style></author><author><style face="normal" font="default" size="100%">Latorre, A.</style></author><author><style face="normal" font="default" size="100%">Moya, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Structural analyses of a hypothetical minimal metabolism.</style></title><secondary-title><style face="normal" font="default" size="100%">Philos. Trans. R. Soc. Lond., B, Biol. Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1098/rstb.2007.2067</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1486</style></number><volume><style face="normal" font="default" size="100%">362</style></volume><pages><style face="normal" font="default" size="100%">1751–1762</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">By integrating data from comparative genomics and large-scale deletion studies, we previously proposed a minimal gene set comprising 206 protein-coding genes. To evaluate the consistency of the metabolism encoded by such a minimal genome, we have carried out a series of computational analyses. Firstly, the topology of the minimal metabolism was compared with that of the reconstructed networks from natural bacterial genomes. Secondly, the robustness of the metabolic network was evaluated by simulated mutagenesis and, finally, the stoichiometric consistency was assessed by automatically deriving the steady-state solutions from the reaction set. The results indicated that the proposed minimal metabolism presents stoichiometric consistency and that it is organized as a complex power-law network with topological parameters falling within the expected range for a natural metabolism of its size. The robustness analyses revealed that most random mutations do not alter the topology of the network significantly, but do cause significant damage by preventing the synthesis of several compounds or compromising the stoichiometric consistency of the metabolism. The implications that these results have on the origins of metabolic complexity and the theoretical design of an artificial minimal cell are discussed.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luheshi, LM.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Brorsson, AC.</style></author><author><style face="normal" font="default" size="100%">Pawar, AP.</style></author><author><style face="normal" font="default" size="100%">Watson, IE.</style></author><author><style face="normal" font="default" size="100%">Chiti, F.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Lomas, DA.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Crowther, DC.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Systematic in vivo analysis of the intrinsic determinants of amyloid Beta pathogenicity.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pbio.0050290</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">e290</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Protein aggregation into amyloid fibrils and protofibrillar aggregates is associated with a number of the most common neurodegenerative diseases. We have established, using a computational approach, that knowledge of the primary sequences of proteins is sufficient to predict their in vitro aggregation propensities. Here we demonstrate, using rational mutagenesis of the Abeta42 peptide based on such computational predictions of aggregation propensity, the existence of a strong correlation between the propensity of Abeta42 to form protofibrils and its effect on neuronal dysfunction and degeneration in a Drosophila model of Alzheimer disease. Our findings provide a quantitative description of the molecular basis for the pathogenicity of Abeta and link directly and systematically the intrinsic properties of biomolecules, predicted in silico and confirmed in vitro, to pathogenic events taking place in a living organism.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Drosophila 12 Genomes Consortium</style></author><author><style face="normal" font="default" size="100%">Clark, AG.</style></author><author><style face="normal" font="default" size="100%">Eisen, MB.</style></author><author><style face="normal" font="default" size="100%">Smith, DR.</style></author><author><style face="normal" font="default" size="100%">Bergman, CM.</style></author><author><style face="normal" font="default" size="100%">Oliver, B.</style></author><author><style face="normal" font="default" size="100%">Markow, TA.</style></author><author><style face="normal" font="default" size="100%">Kaufman, TC.</style></author><author><style face="normal" font="default" size="100%">Kellis, M.</style></author><author><style face="normal" font="default" size="100%">Gelbart, W.</style></author><author><style face="normal" font="default" size="100%">Iyer, VN.</style></author><author><style face="normal" font="default" size="100%">Pollard, DA.</style></author><author><style face="normal" font="default" size="100%">Sackton, TB.</style></author><author><style face="normal" font="default" size="100%">Larracuente, AM.</style></author><author><style face="normal" font="default" size="100%">Singh, ND.</style></author><author><style face="normal" font="default" size="100%">Abad, JP.</style></author><author><style face="normal" font="default" size="100%">Abt, DN.</style></author><author><style face="normal" font="default" size="100%">Adryan, B.</style></author><author><style face="normal" font="default" size="100%">Aguade, M.</style></author><author><style face="normal" font="default" size="100%">Akashi, H.</style></author><author><style face="normal" font="default" size="100%">Anderson, WW.</style></author><author><style face="normal" font="default" size="100%">Aquadro, CF.</style></author><author><style face="normal" font="default" size="100%">Ardell, DH.</style></author><author><style face="normal" font="default" size="100%">Arguello, R.</style></author><author><style face="normal" font="default" size="100%">Artieri, CG.</style></author><author><style face="normal" font="default" size="100%">Barbash, DA.</style></author><author><style face="normal" font="default" size="100%">Barker, D.</style></author><author><style face="normal" font="default" size="100%">Barsanti, P.</style></author><author><style face="normal" font="default" size="100%">Batterham, P.</style></author><author><style face="normal" font="default" size="100%">Batzoglou, S.</style></author><author><style face="normal" font="default" size="100%">Begun, D.</style></author><author><style face="normal" font="default" size="100%">Bhutkar, A.</style></author><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Bosak, SA.</style></author><author><style face="normal" font="default" size="100%">Bradley, RK.</style></author><author><style face="normal" font="default" size="100%">Brand, AD.</style></author><author><style face="normal" font="default" size="100%">Brent, MR.</style></author><author><style face="normal" font="default" size="100%">Brooks, AN.</style></author><author><style face="normal" font="default" size="100%">Brown, RH.</style></author><author><style face="normal" font="default" size="100%">Butlin, RK.</style></author><author><style face="normal" font="default" size="100%">Caggese, C.</style></author><author><style face="normal" font="default" size="100%">Calvi, BR.</style></author><author><style face="normal" font="default" size="100%">Bernardo de Carvalho, A.</style></author><author><style face="normal" font="default" size="100%">Caspi, A.</style></author><author><style face="normal" font="default" size="100%">Castrezana, S.</style></author><author><style face="normal" font="default" size="100%">Celniker, SE.</style></author><author><style face="normal" font="default" size="100%">Chang, JL.</style></author><author><style face="normal" font="default" size="100%">Chapple, C.</style></author><author><style face="normal" font="default" size="100%">Chatterji, S.</style></author><author><style face="normal" font="default" size="100%">Chinwalla, A.</style></author><author><style face="normal" font="default" size="100%">Civetta, A.</style></author><author><style face="normal" font="default" size="100%">Clifton, SW.</style></author><author><style face="normal" font="default" size="100%">Comeron, JM.</style></author><author><style face="normal" font="default" size="100%">Costello, JC.</style></author><author><style face="normal" font="default" size="100%">Coyne, JA.</style></author><author><style face="normal" font="default" size="100%">Daub, J.</style></author><author><style face="normal" font="default" size="100%">David, RG.</style></author><author><style face="normal" font="default" size="100%">Delcher, AL.</style></author><author><style face="normal" font="default" size="100%">Delehaunty, K.</style></author><author><style face="normal" font="default" size="100%">Do, CB.</style></author><author><style face="normal" font="default" size="100%">Ebling, H.</style></author><author><style face="normal" font="default" size="100%">Edwards, K.</style></author><author><style face="normal" font="default" size="100%">Eickbush, T.</style></author><author><style face="normal" font="default" size="100%">Evans, JD.</style></author><author><style face="normal" font="default" size="100%">Filipski, A.</style></author><author><style face="normal" font="default" size="100%">Findeiss, S.</style></author><author><style face="normal" font="default" size="100%">Freyhult, E.</style></author><author><style face="normal" font="default" size="100%">Fulton, L.</style></author><author><style face="normal" font="default" size="100%">Fulton, R.</style></author><author><style face="normal" font="default" size="100%">Garcia, AC.</style></author><author><style face="normal" font="default" size="100%">Gardiner, A.</style></author><author><style face="normal" font="default" size="100%">Garfield, DA.</style></author><author><style face="normal" font="default" size="100%">Garvin, BE.</style></author><author><style face="normal" font="default" size="100%">Gibson, G.</style></author><author><style face="normal" font="default" size="100%">Gilbert, D.</style></author><author><style face="normal" font="default" size="100%">Gnerre, S.</style></author><author><style face="normal" font="default" size="100%">Godfrey, J.</style></author><author><style face="normal" font="default" size="100%">Good, R.</style></author><author><style face="normal" font="default" size="100%">Gotea, V.</style></author><author><style face="normal" font="default" size="100%">Gravely, B.</style></author><author><style face="normal" font="default" size="100%">Greenberg, AJ.</style></author><author><style face="normal" font="default" size="100%">Griffiths-Jones, S.</style></author><author><style face="normal" font="default" size="100%">Gross, S.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Gustafson, EA.</style></author><author><style face="normal" font="default" size="100%">Haerty, W.</style></author><author><style face="normal" font="default" size="100%">Hahn, MW.</style></author><author><style face="normal" font="default" size="100%">Halligan, DL.</style></author><author><style face="normal" font="default" size="100%">Halpern, AL.</style></author><author><style face="normal" font="default" size="100%">Halter, GM.</style></author><author><style face="normal" font="default" size="100%">Han, MV.</style></author><author><style face="normal" font="default" size="100%">Heger, A.</style></author><author><style face="normal" font="default" size="100%">Hillier, L.</style></author><author><style face="normal" font="default" size="100%">Hinrichs, AS.</style></author><author><style face="normal" font="default" size="100%">Holmes, I.</style></author><author><style face="normal" font="default" size="100%">Hoskins, RA.</style></author><author><style face="normal" font="default" size="100%">Hubisz, MJ.</style></author><author><style face="normal" font="default" size="100%">Hultmark, D.</style></author><author><style face="normal" font="default" size="100%">Huntley, MA.</style></author><author><style face="normal" font="default" size="100%">Jaffe, DB.</style></author><author><style face="normal" font="default" size="100%">Jagadeeshan, S.</style></author><author><style face="normal" font="default" size="100%">Jeck, WR.</style></author><author><style face="normal" font="default" size="100%">Johnson, J.</style></author><author><style face="normal" font="default" size="100%">Jones, CD.</style></author><author><style face="normal" font="default" size="100%">Jordan, WC.</style></author><author><style face="normal" font="default" size="100%">Karpen, GH.</style></author><author><style face="normal" font="default" size="100%">Kataoka, E.</style></author><author><style face="normal" font="default" size="100%">Keightley, PD.</style></author><author><style face="normal" font="default" size="100%">Kheradpour, P.</style></author><author><style face="normal" font="default" size="100%">Kirkness, EF.</style></author><author><style face="normal" font="default" size="100%">Koerich, LB.</style></author><author><style face="normal" font="default" size="100%">Kristiansen, K.</style></author><author><style face="normal" font="default" size="100%">Kudrna, D.</style></author><author><style face="normal" font="default" size="100%">Kulathinal, RJ.</style></author><author><style face="normal" font="default" size="100%">Kumar, S.</style></author><author><style face="normal" font="default" size="100%">Kwok, R.</style></author><author><style face="normal" font="default" size="100%">Lander, E.</style></author><author><style face="normal" font="default" size="100%">Langley, CH.</style></author><author><style face="normal" font="default" size="100%">Lapoint, R.</style></author><author><style face="normal" font="default" size="100%">Lazzaro, BP.</style></author><author><style face="normal" font="default" size="100%">Lee, SJ.</style></author><author><style face="normal" font="default" size="100%">Levesque, L.</style></author><author><style face="normal" font="default" size="100%">Li, R.</style></author><author><style face="normal" font="default" size="100%">Lin, CF.</style></author><author><style face="normal" font="default" size="100%">Lin, MF.</style></author><author><style face="normal" font="default" size="100%">Lindblad-Toh, K.</style></author><author><style face="normal" font="default" size="100%">Llopart, A.</style></author><author><style face="normal" font="default" size="100%">Long, M.</style></author><author><style face="normal" font="default" size="100%">Low, L.</style></author><author><style face="normal" font="default" size="100%">Lozovsky, E.</style></author><author><style face="normal" font="default" size="100%">Lu, J.</style></author><author><style face="normal" font="default" size="100%">Luo, M.</style></author><author><style face="normal" font="default" size="100%">Machado, CA.</style></author><author><style face="normal" font="default" size="100%">Makalowski, W.</style></author><author><style face="normal" font="default" size="100%">Marzo, M.</style></author><author><style face="normal" font="default" size="100%">Matsuda, M.</style></author><author><style face="normal" font="default" size="100%">Matzkin, L.</style></author><author><style face="normal" font="default" size="100%">McAllister, B.</style></author><author><style face="normal" font="default" size="100%">McBride, CS.</style></author><author><style face="normal" font="default" size="100%">McKernan, B.</style></author><author><style face="normal" font="default" size="100%">McKernan, K.</style></author><author><style face="normal" font="default" size="100%">Mendez-Lago, M.</style></author><author><style face="normal" font="default" size="100%">Minx, P.</style></author><author><style face="normal" font="default" size="100%">Mollenhauer, MU.</style></author><author><style face="normal" font="default" size="100%">Montooth, K.</style></author><author><style face="normal" font="default" size="100%">Mount, SM.</style></author><author><style face="normal" font="default" size="100%">Mu, X.</style></author><author><style face="normal" font="default" size="100%">Myers, E.</style></author><author><style face="normal" font="default" size="100%">Negre, B.</style></author><author><style face="normal" font="default" size="100%">Newfeld, S.</style></author><author><style face="normal" font="default" size="100%">Nielsen, R.</style></author><author><style face="normal" font="default" size="100%">Noor, MA.</style></author><author><style face="normal" font="default" size="100%">O'Grady, P.</style></author><author><style face="normal" font="default" size="100%">Pachter, L.</style></author><author><style face="normal" font="default" size="100%">Papaceit, M.</style></author><author><style face="normal" font="default" size="100%">Parisi, MJ.</style></author><author><style face="normal" font="default" size="100%">Parisi, M.</style></author><author><style face="normal" font="default" size="100%">Parts, L.</style></author><author><style face="normal" font="default" size="100%">Pedersen, JS.</style></author><author><style face="normal" font="default" size="100%">Pesole, G.</style></author><author><style face="normal" font="default" size="100%">Phillippy, AM.</style></author><author><style face="normal" font="default" size="100%">Ponting, CP.</style></author><author><style face="normal" font="default" size="100%">Pop, M.</style></author><author><style face="normal" font="default" size="100%">Porcelli, D.</style></author><author><style face="normal" font="default" size="100%">Powell, JR.</style></author><author><style face="normal" font="default" size="100%">Prohaska, S.</style></author><author><style face="normal" font="default" size="100%">Pruitt, K.</style></author><author><style face="normal" font="default" size="100%">Puig, M.</style></author><author><style face="normal" font="default" size="100%">Quesneville, H.</style></author><author><style face="normal" font="default" size="100%">Ram, KR.</style></author><author><style face="normal" font="default" size="100%">Rand, D.</style></author><author><style 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face="normal" font="default" size="100%">Jaffe, DB.</style></author><author><style face="normal" font="default" size="100%">Alvarez, P.</style></author><author><style face="normal" font="default" size="100%">Brockman, W.</style></author><author><style face="normal" font="default" size="100%">Butler, J.</style></author><author><style face="normal" font="default" size="100%">Chin, C.</style></author><author><style face="normal" font="default" size="100%">Gnerre, S.</style></author><author><style face="normal" font="default" size="100%">Grabherr, M.</style></author><author><style face="normal" font="default" size="100%">Kleber, M.</style></author><author><style face="normal" font="default" size="100%">Mauceli, E.</style></author><author><style face="normal" font="default" size="100%">MacCallum, I.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of genes and genomes on the Drosophila phylogeny.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0634</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7167</style></number><volume><style face="normal" font="default" size="100%">450</style></volume><pages><style face="normal" font="default" size="100%">203–218</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lyle, R.</style></author><author><style face="normal" font="default" size="100%">Prandini, P.</style></author><author><style face="normal" font="default" size="100%">Osoegawa, K.</style></author><author><style face="normal" font="default" size="100%">ten Hallers, B.</style></author><author><style face="normal" font="default" size="100%">Humphray, S.</style></author><author><style face="normal" font="default" size="100%">Zhu, B.</style></author><author><style face="normal" font="default" size="100%">Eyras, E.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Bird, CP.</style></author><author><style face="normal" font="default" size="100%">Gagos, S.</style></author><author><style face="normal" font="default" size="100%">Scott, C.</style></author><author><style face="normal" font="default" size="100%">Cox, A.</style></author><author><style face="normal" font="default" size="100%">Deutsch, S.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Cruts, M.</style></author><author><style face="normal" font="default" size="100%">Dahoun, S.</style></author><author><style face="normal" font="default" size="100%">She, X.</style></author><author><style face="normal" font="default" size="100%">Bena, F.</style></author><author><style face="normal" font="default" size="100%">Wang, SY.</style></author><author><style face="normal" font="default" size="100%">Van Broeckhoven, C.</style></author><author><style face="normal" font="default" size="100%">Eichler, EE.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Rogers, J.</style></author><author><style face="normal" font="default" size="100%">de Jong, PJ.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Islands of euchromatin-like sequence and expressed polymorphic sequences within the short arm of human chromosome 21.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.667530</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">1690–1696</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The goals of the human genome project did not include sequencing of the heterochromatic regions. We describe here an initial sequence of 1.1 Mb of the short arm of human chromosome 21 (HSA21p), estimated to be 10% of 21p. This region contains extensive euchromatic-like sequence and includes on average one transcript every 100 kb. These transcripts show multiple inter- and intrachromosomal copies, and extensive copy number and sequence variability. The sequencing of the &quot;heterochromatic&quot; regions of the human genome is likely to reveal many additional functional elements and provide important evolutionary information.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">From endosymbiont to host-controlled organelle: the hijacking of mitochondrial protein synthesis and metabolism.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pcbi.0030219</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">e219</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Mitochondria are eukaryotic organelles that originated from the endosymbiosis of an alpha-proteobacterium. To gain insight into the evolution of the mitochondrial proteome as it proceeded through the transition from a free-living cell to a specialized organelle, we compared a reconstructed ancestral proteome of the mitochondrion with the proteomes of alpha-proteobacteria as well as with the mitochondrial proteomes in yeast and man. Overall, there has been a large turnover of the mitochondrial proteome during the evolution of mitochondria. Early in the evolution of the mitochondrion, proteins involved in cell envelope synthesis have virtually disappeared, whereas proteins involved in replication, transcription, cell division, transport, regulation, and signal transduction have been replaced by eukaryotic proteins. More than half of what remains from the mitochondrial ancestor in modern mitochondria corresponds to translation, including post-translational modifications, and to metabolic pathways that are directly, or indirectly, involved in energy conversion. Altogether, the results indicate that the eukaryotic host has hijacked the proto-mitochondrion, taking control of its protein synthesis and metabolism.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Pechmann, S.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Life on the edge: a link between gene expression levels and aggregation rates of human proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Biochem. Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.tibs.2007.03.005</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">204–206</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tress, ML.</style></author><author><style face="normal" font="default" size="100%">Martelli, PL.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Reeves, GA.</style></author><author><style face="normal" font="default" size="100%">Wesselink, JJ.</style></author><author><style face="normal" font="default" size="100%">Yeats, C.</style></author><author><style face="normal" font="default" size="100%">Olason, PI.</style></author><author><style face="normal" font="default" size="100%">Albrecht, M.</style></author><author><style face="normal" font="default" size="100%">Hegyi, H.</style></author><author><style face="normal" font="default" size="100%">Giorgetti, A.</style></author><author><style face="normal" font="default" size="100%">Raimondo, D.</style></author><author><style face="normal" font="default" size="100%">Lagarde, J.</style></author><author><style face="normal" font="default" size="100%">Laskowski, RA.</style></author><author><style face="normal" font="default" size="100%">López, G.</style></author><author><style face="normal" font="default" size="100%">Sadowski, MI.</style></author><author><style face="normal" font="default" size="100%">Watson, JD.</style></author><author><style face="normal" font="default" size="100%">Fariselli, P.</style></author><author><style face="normal" font="default" size="100%">Rossi, I.</style></author><author><style face="normal" font="default" size="100%">Nagy, A.</style></author><author><style face="normal" font="default" size="100%">Kai, W.</style></author><author><style face="normal" font="default" size="100%">Størling, Z.</style></author><author><style face="normal" font="default" size="100%">Orsini, M.</style></author><author><style face="normal" font="default" size="100%">Assenov, Y.</style></author><author><style face="normal" font="default" size="100%">Blankenburg, H.</style></author><author><style face="normal" font="default" size="100%">Huthmacher, C.</style></author><author><style face="normal" font="default" size="100%">Ramírez, F.</style></author><author><style face="normal" font="default" size="100%">Schlicker, A.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Jones, P.</style></author><author><style face="normal" font="default" size="100%">Kerrien, S.</style></author><author><style face="normal" font="default" size="100%">Orchard, S.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Brunak, S.</style></author><author><style face="normal" font="default" size="100%">Casadio, R.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Hermjakob, H.</style></author><author><style face="normal" font="default" size="100%">Jones, DT.</style></author><author><style face="normal" font="default" size="100%">Lengauer, T.</style></author><author><style face="normal" font="default" size="100%">Orengo, CA.</style></author><author><style face="normal" font="default" size="100%">Patthy, L.</style></author><author><style face="normal" font="default" size="100%">Thornton, JM.</style></author><author><style face="normal" font="default" size="100%">Tramontano, A.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The implications of alternative splicing in the ENCODE protein complement.</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Natl. Acad. Sci. U.S.A.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1073/pnas.070080010</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">13</style></number><volume><style face="normal" font="default" size="100%">104</style></volume><pages><style face="normal" font="default" size="100%">5495–5500</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Alternative premessenger RNA splicing enables genes to generate more than one gene product. Splicing events that occur within protein coding regions have the potential to alter the biological function of the expressed protein and even to create new protein functions. Alternative splicing has been suggested as one explanation for the discrepancy between the number of human genes and functional complexity. Here, we carry out a detailed study of the alternatively spliced gene products annotated in the ENCODE pilot project. We find that alternative splicing in human genes is more frequent than has commonly been suggested, and we demonstrate that many of the potential alternative gene products will have markedly different structure and function from their constitutively spliced counterparts. For the vast majority of these alternative isoforms, little evidence exists to suggest they have a role as functional proteins, and it seems unlikely that the spectrum of conventional enzymatic or structural functions can be substantially extended through alternative splicing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kalinina, E.</style></author><author><style face="normal" font="default" size="100%">Biswas, R.</style></author><author><style face="normal" font="default" size="100%">Berezniuk, I.</style></author><author><style face="normal" font="default" size="100%">Hermoso, A.</style></author><author><style face="normal" font="default" size="100%">Aviles, FX.</style></author><author><style face="normal" font="default" size="100%">Fricker, LD.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A novel subfamily of mouse cytosolic carboxypeptidases.</style></title><secondary-title><style face="normal" font="default" size="100%">FASEB J.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1096/fj.06-7329com</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">836–850</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Nna1 is a recently described gene product that has sequence similarity with metallocarboxypeptidases. In the present study, five additional Nna1-like genes were identified in the mouse genome and named cytosolic carboxypeptidase (CCP) 2 through 6. Modeling suggests that the carboxypeptidase domain folds into a structure that resembles metallocarboxypeptidases of the M14 family, with all necessary residues for catalytic activity and broad substrate specificity. All CCPs are abundant in testis and also expressed in brain, pituitary, eye, and other mouse tissues. In brain, Nna1/CCP1, CCP5, and CCP6 are broadly distributed, whereas CCP2 and 3 exhibit restricted patterns of expression. Nna1/CCP1, CCP2, CCP5, and CCP6 were found to exhibit a cytosolic distribution, with a slight accumulation of CCP5 in the nucleus. Based on the above results, we hypothesized that Nna1/CCP1 and CCP2-6 function in the processing of cytosolic proteins such as alpha-tubulin, which is known to be modified by the removal of a C-terminal tyrosine. Analysis of the forms of alpha tubulin in the olfactory bulb of mice lacking Nna1/CCP1 showed the absence of the detyrosinylated form in the mitral cells. Taken together, these results are consistent with a role for Nna1/CCP1 and the related CCPs in the processing of tubulin.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rodriguez de la Vega, M.</style></author><author><style face="normal" font="default" size="100%">Sevilla, RG.</style></author><author><style face="normal" font="default" size="100%">Hermoso, A.</style></author><author><style face="normal" font="default" size="100%">Lorenzo, J.</style></author><author><style face="normal" font="default" size="100%">Tanco, S.</style></author><author><style face="normal" font="default" size="100%">Diez, A.</style></author><author><style face="normal" font="default" size="100%">Fricker, LD.</style></author><author><style face="normal" font="default" size="100%">Bautista, JM.</style></author><author><style face="normal" font="default" size="100%">Avilés, FX.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Nna1-like proteins are active metallocarboxypeptidases of a new and diverse M14 subfamily.</style></title><secondary-title><style face="normal" font="default" size="100%">FASEB J.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1096/fj.06-7330com</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">851–865</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Nna1 has some sequence similarity to metallocarboxypeptidases, but the biochemical characterization of Nna1 has not previously been reported. In this work we performed a detailed genomic scan and found &gt;100 Nna1 homologues in bacteria, Protista, and Animalia, including several paralogs in most eukaryotic species. Phylogenetic analysis of the Nna1-like sequences demonstrates a major divergence between Nna1-like peptidases and the previously known metallocarboxypeptidases subfamilies: M14A, M14B, and M14C. Conformational modeling of representative Nna1-like proteins from a variety of species indicates an unusually open active site, a property that might facilitate its action on a wide variety of peptide and protein substrates. To test this, we expressed a recombinant form of one of the Nna1-like peptidases from Caenorhabditis elegans and demonstrated that this protein is a fully functional metallocarboxypeptidase that cleaves a range of C-terminal amino acids from synthetic peptides. The enzymatic activity is activated by ATP/ADP and salt-inactivated, and is preferentially inhibited by Z-Glu-Tyr dipeptide, which is without precedent in metallocarboxypeptidases and resembles tubulin carboxypeptidase functioning; this hypothesis is strongly reinforced by the results depicted in Kalinina et al. published as accompanying paper in this journal. Our findings demonstrate that the M14 family of metallocarboxypeptidases is more complex and diverse than expected, and that Nna1-like peptidases are functional variants of such enzymes, representing a novel subfamily (we propose the name M14D) that contributes substantially to such diversity.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">ENCODE Project Consortium</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Stamatoyannopoulos, JA.</style></author><author><style face="normal" font="default" size="100%">Dutta, A.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Margulies, EH.</style></author><author><style face="normal" font="default" size="100%">Weng, Z.</style></author><author><style face="normal" font="default" size="100%">Snyder, M.</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, ET.</style></author><author><style face="normal" font="default" size="100%">Thurman, RE.</style></author><author><style face="normal" font="default" size="100%">Kuehn, MS.</style></author><author><style face="normal" font="default" size="100%">Taylor, CM.</style></author><author><style face="normal" font="default" size="100%">Neph, S.</style></author><author><style face="normal" font="default" size="100%">Koch, CM.</style></author><author><style face="normal" font="default" size="100%">Asthana, S.</style></author><author><style face="normal" font="default" size="100%">Malhotra, A.</style></author><author><style face="normal" font="default" size="100%">Adzhubei, I.</style></author><author><style face="normal" font="default" size="100%">Greenbaum, JA.</style></author><author><style face="normal" font="default" size="100%">Andrews, RM.</style></author><author><style face="normal" font="default" size="100%">Flicek, P.</style></author><author><style face="normal" font="default" size="100%">Boyle, PJ.</style></author><author><style face="normal" font="default" size="100%">Cao, H.</style></author><author><style face="normal" font="default" size="100%">Carter, NP.</style></author><author><style face="normal" font="default" size="100%">Clelland, GK.</style></author><author><style face="normal" font="default" size="100%">Davis, S.</style></author><author><style face="normal" font="default" size="100%">Day, N.</style></author><author><style face="normal" font="default" size="100%">Dhami, P.</style></author><author><style face="normal" font="default" size="100%">Dillon, SC.</style></author><author><style face="normal" font="default" size="100%">Dorschner, MO.</style></author><author><style face="normal" font="default" size="100%">Fiegler, H.</style></author><author><style face="normal" font="default" size="100%">Giresi, PG.</style></author><author><style face="normal" font="default" size="100%">Goldy, J.</style></author><author><style face="normal" font="default" size="100%">Hawrylycz, M.</style></author><author><style face="normal" font="default" size="100%">Haydock, A.</style></author><author><style face="normal" font="default" size="100%">Humbert, R.</style></author><author><style face="normal" font="default" size="100%">James, KD.</style></author><author><style face="normal" font="default" size="100%">Johnson, BE.</style></author><author><style face="normal" font="default" size="100%">Johnson, EM.</style></author><author><style face="normal" font="default" size="100%">Frum, TT.</style></author><author><style face="normal" font="default" size="100%">Rosenzweig, ER.</style></author><author><style face="normal" font="default" size="100%">Karnani, N.</style></author><author><style face="normal" font="default" size="100%">Lee, K.</style></author><author><style face="normal" font="default" size="100%">Lefebvre, GC.</style></author><author><style face="normal" font="default" size="100%">Navas, PA.</style></author><author><style face="normal" font="default" size="100%">Neri, F.</style></author><author><style face="normal" font="default" size="100%">Parker, SC.</style></author><author><style face="normal" font="default" size="100%">Sabo, PJ.</style></author><author><style face="normal" font="default" size="100%">Sandstrom, R.</style></author><author><style face="normal" font="default" size="100%">Shafer, A.</style></author><author><style face="normal" font="default" size="100%">Vetrie, D.</style></author><author><style face="normal" font="default" size="100%">Weaver, M.</style></author><author><style face="normal" font="default" size="100%">Wilcox, S.</style></author><author><style face="normal" font="default" size="100%">Yu, M.</style></author><author><style face="normal" font="default" size="100%">Collins, FS.</style></author><author><style face="normal" font="default" size="100%">Dekker, J.</style></author><author><style face="normal" font="default" size="100%">Lieb, JD.</style></author><author><style face="normal" font="default" size="100%">Tullius, TD.</style></author><author><style face="normal" font="default" size="100%">Crawford, GE.</style></author><author><style face="normal" font="default" size="100%">Sunyaev, S.</style></author><author><style face="normal" font="default" size="100%">Noble, WS.</style></author><author><style face="normal" font="default" size="100%">Dunham, I.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Kapranov, P.</style></author><author><style face="normal" font="default" size="100%">Rozowsky, J.</style></author><author><style face="normal" font="default" size="100%">Zheng, D.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Ghosh, S.</style></author><author><style face="normal" font="default" size="100%">Sandelin, A.</style></author><author><style face="normal" font="default" size="100%">Hofacker, IL.</style></author><author><style face="normal" font="default" size="100%">Baertsch, R.</style></author><author><style face="normal" font="default" size="100%">Keefe, D.</style></author><author><style face="normal" font="default" size="100%">Dike, S.</style></author><author><style face="normal" font="default" size="100%">Cheng, J.</style></author><author><style 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font="default" size="100%">Maduro, VV.</style></author><author><style face="normal" font="default" size="100%">Maskeri, B.</style></author><author><style face="normal" font="default" size="100%">McDowell, JC.</style></author><author><style face="normal" font="default" size="100%">Park, M.</style></author><author><style face="normal" font="default" size="100%">Thomas, PJ.</style></author><author><style face="normal" font="default" size="100%">Young, AC.</style></author><author><style face="normal" font="default" size="100%">Blakesley, RW.</style></author><author><style face="normal" font="default" size="100%">Muzny, DM.</style></author><author><style face="normal" font="default" size="100%">Sodergren, E.</style></author><author><style face="normal" font="default" size="100%">Wheeler, DA.</style></author><author><style face="normal" font="default" size="100%">Worley, KC.</style></author><author><style face="normal" font="default" size="100%">Jiang, H.</style></author><author><style face="normal" font="default" size="100%">Weinstock, GM.</style></author><author><style face="normal" font="default" size="100%">Gibbs, RA.</style></author><author><style face="normal" font="default" size="100%">Graves, T.</style></author><author><style face="normal" font="default" size="100%">Fulton, R.</style></author><author><style face="normal" font="default" size="100%">Mardis, ER.</style></author><author><style face="normal" font="default" size="100%">Wilson, RK.</style></author><author><style face="normal" font="default" size="100%">Clamp, M.</style></author><author><style face="normal" font="default" size="100%">Cuff, J.</style></author><author><style face="normal" font="default" size="100%">Gnerre, S.</style></author><author><style face="normal" font="default" size="100%">Jaffe, DB.</style></author><author><style face="normal" font="default" size="100%">Chang, JL.</style></author><author><style face="normal" font="default" size="100%">Lindblad-Toh, K.</style></author><author><style face="normal" font="default" size="100%">Lander, ES.</style></author><author><style face="normal" font="default" size="100%">Koriabine, M.</style></author><author><style face="normal" font="default" size="100%">Nefedov, M.</style></author><author><style face="normal" font="default" size="100%">Osoegawa, K.</style></author><author><style face="normal" font="default" size="100%">Yoshinaga, Y.</style></author><author><style face="normal" font="default" size="100%">Zhu, B.</style></author><author><style face="normal" font="default" size="100%">de Jong, PJ.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0587</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7146</style></number><volume><style face="normal" font="default" size="100%">447</style></volume><pages><style face="normal" font="default" size="100%">799–816</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rozowsky, JS.</style></author><author><style face="normal" font="default" size="100%">Newburger, D.</style></author><author><style face="normal" font="default" size="100%">Sayward, F.</style></author><author><style face="normal" font="default" size="100%">Wu, J.</style></author><author><style face="normal" font="default" size="100%">Jordan, G.</style></author><author><style face="normal" font="default" size="100%">Korbel, JO.</style></author><author><style face="normal" font="default" size="100%">Nagalakshmi, U.</style></author><author><style face="normal" font="default" size="100%">Yang, J.</style></author><author><style face="normal" font="default" size="100%">Zheng, D.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Weissman, S.</style></author><author><style face="normal" font="default" size="100%">Miller, P.</style></author><author><style face="normal" font="default" size="100%">Snyder, M.</style></author><author><style face="normal" font="default" size="100%">Gerstein, MB.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The DART classification of unannotated transcription within the ENCODE regions: associating transcription with known and novel loci.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.569600</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">732–745</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For the approximately 1% of the human genome in the ENCODE regions, only about half of the transcriptionally active regions (TARs) identified with tiling microarrays correspond to annotated exons. Here we categorize this large amount of &quot;unannotated transcription.&quot; We use a number of disparate features to classify the 6988 novel TARs-array expression profiles across cell lines and conditions, sequence composition, phylogenetic profiles (presence/absence of syntenic conservation across 17 species), and locations relative to genes. In the classification, we first filter out TARs with unusual sequence composition and those likely resulting from cross-hybridization. We then associate some of those remaining with proximal exons having correlated expression profiles. Finally, we cluster unclassified TARs into putative novel loci, based on similar expression and phylogenetic profiles. To encapsulate our classification, we construct a Database of Active Regions and Tools (DART.gersteinlab.org). DART has special facilities for rapidly handling and comparing many sets of TARs and their heterogeneous features, synchronizing across builds, and interfacing with other resources. Overall, we find that approximately 14% of the novel TARs can be associated with known genes, while approximately 21% can be clustered into approximately 200 novel loci. We observe that TARs associated with genes are enriched in the potential to form structural RNAs and many novel TAR clusters are associated with nearby promoters. To benchmark our classification, we design a set of experiments for testing the connectivity of novel TARs. Overall, we find that 18 of the 46 connections tested validate by RT-PCR and four of five sequenced PCR products confirm connectivity unambiguously.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Kapranov, P.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Drenkow, J.</style></author><author><style face="normal" font="default" size="100%">Lagarde, J.</style></author><author><style face="normal" font="default" size="100%">Alioto, T.</style></author><author><style face="normal" font="default" size="100%">Manzano, C.</style></author><author><style face="normal" font="default" size="100%">Chrast, J.</style></author><author><style face="normal" font="default" size="100%">Dike, S.</style></author><author><style face="normal" font="default" size="100%">Wyss, C.</style></author><author><style face="normal" font="default" size="100%">Henrichsen, CN.</style></author><author><style face="normal" font="default" size="100%">Holroyd, N.</style></author><author><style face="normal" font="default" size="100%">Dickson, MC.</style></author><author><style face="normal" font="default" size="100%">Taylor, R.</style></author><author><style face="normal" font="default" size="100%">Hance, Z.</style></author><author><style face="normal" font="default" size="100%">Foissac, S.</style></author><author><style face="normal" font="default" size="100%">Myers, RM.</style></author><author><style face="normal" font="default" size="100%">Rogers, J.</style></author><author><style face="normal" font="default" size="100%">Hubbard, T.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prominent use of distal 5' transcription start sites and discovery of a large number of additional exons in ENCODE regions.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.566060</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">746–759</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This report presents systematic empirical annotation of transcript products from 399 annotated protein-coding loci across the 1% of the human genome targeted by the Encyclopedia of DNA elements (ENCODE) pilot project using a combination of 5' rapid amplification of cDNA ends (RACE) and high-density resolution tiling arrays. We identified previously unannotated and often tissue- or cell-line-specific transcribed fragments (RACEfrags), both 5' distal to the annotated 5' terminus and internal to the annotated gene bounds for the vast majority (81.5%) of the tested genes. Half of the distal RACEfrags span large segments of genomic sequences away from the main portion of the coding transcript and often overlap with the upstream-annotated gene(s). Notably, at least 20% of the resultant novel transcripts have changes in their open reading frames (ORFs), most of them fusing ORFs of adjacent transcripts. A significant fraction of distal RACEfrags show expression levels comparable to those of known exons of the same locus, suggesting that they are not part of very minority splice forms. These results have significant implications concerning (1) our current understanding of the architecture of protein-coding genes; (2) our views on locations of regulatory regions in the genome; and (3) the interpretation of sequence polymorphisms mapping to regions hitherto considered to be &quot;noncoding,&quot; ultimately relating to the identification of disease-related sequence alterations.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Washietl, S.</style></author><author><style face="normal" font="default" size="100%">Pedersen, JS.</style></author><author><style face="normal" font="default" size="100%">Korbel, JO.</style></author><author><style face="normal" font="default" size="100%">Stocsits, C.</style></author><author><style face="normal" font="default" size="100%">Gruber, AR.</style></author><author><style face="normal" font="default" size="100%">Hackermüller, J.</style></author><author><style face="normal" font="default" size="100%">Hertel, J.</style></author><author><style face="normal" font="default" size="100%">Lindemeyer, M.</style></author><author><style face="normal" font="default" size="100%">Reiche, K.</style></author><author><style face="normal" font="default" size="100%">Tanzer, A.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Wyss, C.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Lagarde, J.</style></author><author><style face="normal" font="default" size="100%">Drenkow, J.</style></author><author><style face="normal" font="default" size="100%">Kapranov, P.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Snyder, M.</style></author><author><style face="normal" font="default" size="100%">Gerstein, MB.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Hofacker, IL.</style></author><author><style face="normal" font="default" size="100%">Stadler, PF.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Structured RNAs in the ENCODE selected regions of the human genome.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.565070</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">852–864</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zheng, D.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Baertsch, R.</style></author><author><style face="normal" font="default" size="100%">Kapranov, P.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Choo, SW.</style></author><author><style face="normal" font="default" size="100%">Lu, Y.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Snyder, M.</style></author><author><style face="normal" font="default" size="100%">Ruan, Y.</style></author><author><style face="normal" font="default" size="100%">Wei, CL.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Gerstein, MB.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pseudogenes in the ENCODE regions: consensus annotation, analysis of transcription, and evolution.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.558630</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">839–851</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Arising from either retrotransposition or genomic duplication of functional genes, pseudogenes are &quot;genomic fossils&quot; valuable for exploring the dynamics and evolution of genes and genomes. Pseudogene identification is an important problem in computational genomics, and is also critical for obtaining an accurate picture of a genome's structure and function. However, no consensus computational scheme for defining and detecting pseudogenes has been developed thus far. As part of the ENCyclopedia Of DNA Elements (ENCODE) project, we have compared several distinct pseudogene annotation strategies and found that different approaches and parameters often resulted in rather distinct sets of pseudogenes. We subsequently developed a consensus approach for annotating pseudogenes (derived from protein coding genes) in the ENCODE regions, resulting in 201 pseudogenes, two-thirds of which originated from retrotransposition. A survey of orthologs for these pseudogenes in 28 vertebrate genomes showed that a significant fraction ( approximately 80%) of the processed pseudogenes are primate-specific sequences, highlighting the increasing retrotransposition activity in primates. Analysis of sequence conservation and variation also demonstrated that most pseudogenes evolve neutrally, and processed pseudogenes appear to have lost their coding potential immediately or soon after their emergence. In order to explore the functional implication of pseudogene prevalence, we have extensively examined the transcriptional activity of the ENCODE pseudogenes. We performed systematic series of pseudogene-specific RACE analyses. These, together with complementary evidence derived from tiling microarrays and high throughput sequencing, demonstrated that at least a fifth of the 201 pseudogenes are transcribed in one or more cell lines or tissues.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using geneid to identify genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Current protocols in bioinformatics / editoral board, Andreas D. Baxevanis ... [et al.]</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/0471250953.bi0403s1</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">Chapter 4</style></volume><pages><style face="normal" font="default" size="100%">Unit 4.3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This unit describes the usage of geneid, an efficient gene-finding program that allows for the analysis of large genomic sequences, including whole mammalian chromosomes. These sequences can be partially annotated, and geneid can be used to refine this initial annotation. Training geneid is relatively easy, and parameter configurations exist for a number of eukaryotic species. Geneid produces output in a variety of standard formats. The results, thus, can be processed by a variety of software tools, including visualization programs. Geneid software is in the public domain, and it is undergoing constant development. It is easy to install and use. Exhaustive benchmark evaluations show that geneid compares favorably with other existing gene finding tools.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Meinhardt, J.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Pawar, A.</style></author><author><style face="normal" font="default" size="100%">Christopeit, T.</style></author><author><style face="normal" font="default" size="100%">Hortschansky, P.</style></author><author><style face="normal" font="default" size="100%">Schroeckh, V.</style></author><author><style face="normal" font="default" size="100%">Dobson, CM.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">F√§ndrich, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Similarities in the thermodynamics and kinetics of aggregation of disease-related Abeta(1-40) peptides.</style></title><secondary-title><style face="normal" font="default" size="100%">Protein Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1110/ps.062734207</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">1214–1222</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Increasing evidence indicates that polypeptide aggregation often involves a nucleation and a growth phase, although the relationship between the factors that determine these two phases has not yet been fully clarified. We present here an analysis of several mutations at different sites of the Abeta(1-40) peptide, including those associated with early onset forms of the Alzheimer's disease, which reveals that the effects of specific amino acid substitutions in the sequence of this peptide are strongly modulated by their structural context. Nevertheless, mutations at different positions perturb in a correlated manner the free energies of aggregation as well as the lag times and growth rates. We show that these observations can be rationalized in terms of the intrinsic propensities for aggregation of the Abeta(1-40) sequence, thus suggesting that, in the case of this peptide, the determinants of the thermodynamics and of the nucleation and growth of the aggregates have a similar physicochemical basis.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Roma, G.</style></author><author><style face="normal" font="default" size="100%">Cobellis, G.</style></author><author><style face="normal" font="default" size="100%">Claudiani, P.</style></author><author><style face="normal" font="default" size="100%">Maione, F.</style></author><author><style face="normal" font="default" size="100%">Cruz, P.</style></author><author><style face="normal" font="default" size="100%">Tripoli, G.</style></author><author><style face="normal" font="default" size="100%">Sardiello, M.</style></author><author><style face="normal" font="default" size="100%">Peluso, I.</style></author><author><style face="normal" font="default" size="100%">Stupka, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A novel view of the transcriptome revealed from gene trapping in mouse embryonic stem cells.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.5720807</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">1051–1060</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Embryonic stem (ES) cells are pluripotent cell lines with the capacity of self-renewal and the ability to differentiate into specific cell types. We performed the first genome-wide analysis of the mouse ES cell transcriptome using approximately 250,000 gene trap sequence tags deposited in public databases. We unveiled &gt;8000 novel transcripts, mostly non-coding, and &gt;1000 novel alternative and often tissue-specific exons of known genes. Experimental verification of the expression of these genes and exons by RT-PCR yielded a 70% validation rate. A novel non-coding transcript within the set studied showed a highly specific pattern of expression by in situ hybridization. Our analysis also shows that the genome presents gene trapping hotspots, which correspond to 383 known and 87 novel genes. These &quot;hypertrapped&quot; genes show minimal overlap with previously published expression profiles of ES cells; however, we prove by real-time PCR that they are highly expressed in this cell type, thus potentially contributing to the phenotype of ES cells. Although gene trapping was initially devised as an insertional mutagenesis technique, our study demonstrates its impact on the discovery of a substantial and unprecedented portion of the transcriptome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tárraga, J.</style></author><author><style face="normal" font="default" size="100%">Medina, I.</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, H.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phylemon: a suite of web tools for molecular evolution, phylogenetics and phylogenomics</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">38–42</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moretti, S.</style></author><author><style face="normal" font="default" size="100%">Armougom, F.</style></author><author><style face="normal" font="default" size="100%">Wallace, I. M.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author><author><style face="normal" font="default" size="100%">Jongeneel, C. V.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Information Storage and Retrieval</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology, Amino Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">W645-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.</style></abstract><accession-num><style face="normal" font="default" size="100%">17526519</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Swiss Institute of Bioinformatics, Batiment Genopode, UNIL, CH-101 Lausanne.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kerhornou, A.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BioMoby web services to support clustering of co-regulated genes based on similarity of promoter configurations.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/btm25</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">14</style></number><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">1831–1833</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Here we present a computational protocol to analyze the promoter regions of a given set of co-expressed genes, and its implementation through the use of Web services technologies. This protocol aims to cluster a set of co-regulated genes in subsets of genes showing similar configurations of transcription factor binding sites. All the steps of this protocol have been developed as web services that are compliant with BioMoby specifications. AVAILABILITY: {http://genome.imim.es/cgi-bin/moby/GeneClustering_DataSubmission.cgi}. SUPPLEMENTARY INFORMATION: Supplementary data are available at {http://genome.imim.es/webservices/}</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Caflisch, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computational analysis of the S. cerevisiae proteome reveals the function and cellular localization of the least and most amyloidogenic proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Proteins</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/prot.21427</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">68</style></volume><pages><style face="normal" font="default" size="100%">273–278</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Protein sequences have evolved to optimize biological function that usually requires a well-defined three-dimensional structure and a monomeric (or oligomeric) state. These two requirements may be in conflict as the propensity for beta-sheet structure, which is one of the two most common regular conformations of the polypeptide chain in folded proteins, favors also the formation of ordered aggregates of multiple copies of the same protein (fibril, i.e., polymeric state). Such beta-aggregation is typical of amyloid diseases that include Alzheimer's, Parkinson's, and type II diabetes as well as the spongiform encephalopathies. Here, an analytical model previously developed for evaluating the amyloidogenic potential of polypeptides is applied to the proteome of the budding yeast (Saccharomyces cerevisiae). The model is based on the physicochemical properties that are relevant for beta-aggregation and requires only the protein sequence as input. It is shown that beta-aggregation prone proteins in yeast are accrued in molecular transport, protein biosynthesis, and cell wall organization processes while they are underrepresented in ribosome biogenesis, RNA metabolism, and vitamin metabolism. Furthermore, beta-aggregation prone proteins are much more abundant in the cell wall, endoplasmic reticulum, and plasma membrane than in the nucleolus, ribosome, and nucleus. Thus, this study indicates that evolution has not only prevented the selection of amyloidogenic sequences in cellular compartments characterized by a high concentration of unfolded proteins but also tried to exploit the beta-aggregated state for certain functions (e.g. molecular transport) and in well-confined cellular environments or organelles to protect the rest of the cell from toxic (pre-)fibrillar species.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Schlüter, A.</style></author><author><style face="normal" font="default" size="100%">Fourcade, S.</style></author><author><style face="normal" font="default" size="100%">Domènech-Estévez, E.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Berthommier, G.</style></author><author><style face="normal" font="default" size="100%">Ripp, R.</style></author><author><style face="normal" font="default" size="100%">Wanders, RJ.</style></author><author><style face="normal" font="default" size="100%">Poch, O.</style></author><author><style face="normal" font="default" size="100%">Pujol, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkl935</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">D815–D822</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Peroxisomes are essential organelles of eukaryotic origin, ubiquitously distributed in cells and organisms, playing key roles in lipid and antioxidant metabolism. Loss or malfunction of peroxisomes causes more than 20 fatal inherited conditions. We have created a peroxisomal database (http://www.peroxisomeDB.org) that includes the complete peroxisomal proteome of Homo sapiens and Saccharomyces cerevisiae, by gathering, updating and integrating the available genetic and functional information on peroxisomal genes. PeroxisomeDB is structured in interrelated sections 'Genes', 'Functions', 'Metabolic pathways' and 'Diseases', that include hyperlinks to selected features of NCBI, ENSEMBL and UCSC databases. We have designed graphical depictions of the main peroxisomal metabolic routes and have included updated flow charts for diagnosis. Precomputed BLAST, PSI-BLAST, multiple sequence alignment (MUSCLE) and phylogenetic trees are provided to assist in direct multispecies comparison to study evolutionary conserved functions and pathways. Highlights of the PeroxisomeDB include new tools developed for facilitating (i) identification of novel peroxisomal proteins, by means of identifying proteins carrying peroxisome targeting signal (PTS) motifs, (ii) detection of peroxisomes in silico, particularly useful for screening the deluge of newly sequenced genomes. PeroxisomeDB should contribute to the systematic characterization of the peroxisomal proteome and facilitate system biology approaches on the organelle.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tanner, S.</style></author><author><style face="normal" font="default" size="100%">Shen, Z.</style></author><author><style face="normal" font="default" size="100%">Ng, J.</style></author><author><style face="normal" font="default" size="100%">Florea, L.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Briggs, SP.</style></author><author><style face="normal" font="default" size="100%">Bafna, V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Improving gene annotation using peptide mass spectrometry.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.564650</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">231–239</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Annotation of protein-coding genes is a key goal of genome sequencing projects. In spite of tremendous recent advances in computational gene finding, comprehensive annotation remains a challenge. Peptide mass spectrometry is a powerful tool for researching the dynamic proteome and suggests an attractive approach to discover and validate protein-coding genes. We present algorithms to construct and efficiently search spectra against a genomic database, with no prior knowledge of encoded proteins. By searching a corpus of 18.5 million tandem mass spectra (MS/MS) from human proteomic samples, we validate 39,000 exons and 11,000 introns at the level of translation. We present translation-level evidence for novel or extended exons in 16 genes, confirm translation of 224 hypothetical proteins, and discover or confirm over 40 alternative splicing events. Polymorphisms are efficiently encoded in our database, allowing us to observe variant alleles for 308 coding SNPs. Finally, we demonstrate the use of mass spectrometry to improve automated gene prediction, adding 800 correct exons to our predictions using a simple rescoring strategy. Our results demonstrate that proteomic profiling should play a role in any genome sequencing project.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Cavalli, A.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of local structural stabilities of proteins from their amino acid sequences.</style></title><secondary-title><style face="normal" font="default" size="100%">Structure</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.str.2006.12.007</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">139–143</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Hydrogen exchange experiments provide detailed information about the local stability and the solvent accessibility of different regions of the structures of folded proteins, protein complexes, and amyloid fibrils. We introduce an approach to predict protection factors from hydrogen exchange in proteins based on the knowledge of their amino acid sequences without the inclusion of any additional structural information. These results suggest that the propensity of different regions of the structures of globular proteins to undergo local unfolding events can be predicted from their amino acid sequences with an accuracy of 80% or better.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Monsellier, E.</style></author><author><style face="normal" font="default" size="100%">Ramazzotti, M.</style></author><author><style face="normal" font="default" size="100%">de Laureto, PP.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Taddei, N.</style></author><author><style face="normal" font="default" size="100%">Fontana, A.</style></author><author><style face="normal" font="default" size="100%">Vendruscolo, M.</style></author><author><style face="normal" font="default" size="100%">Chiti, F.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The distribution of residues in a polypeptide sequence is a determinant of aggregation optimized by evolution.</style></title><secondary-title><style face="normal" font="default" size="100%">Biophys. J.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1529/biophysj.107.111336</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">93</style></volume><pages><style face="normal" font="default" size="100%">4382–4391</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">It has been shown that the propensity of a protein to form amyloid-like fibrils can be predicted with high accuracy from the knowledge of its amino acid sequence. It has also been suggested, however, that some regions of the sequences are more important than others in determining the aggregation process. Here, we have addressed this issue by constructing a set of &quot;sequence scrambled&quot; variants of the first 29 residues of horse heart apomyoglobin (apoMb(1-29)), in which the sequence was modified while maintaining the same amino acid composition. The clustering of the most amyloidogenic residues in one region of the sequence was found to cause a marked increase of the elongation rate (k(agg)) and a remarkable shortening of the lag phase (t(lag)) of the fibril growth, as determined by far-UV circular dichroism and thioflavin T fluorescence. We also show that taking explicitly into consideration the presence of aggregation-promoting regions in the predictive methods results in a quantitative agreement between the theoretical and observed k(agg) and t(lag) values of the apoMb(1-29) variants. These results, together with a comparison between homologous segments from the family of globins, indicate the existence of a negative selection against the clustering of highly amyloidogenic residues in one or few regions of polypeptide sequences.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Recent evolutions of multiple sequence alignment algorithms</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping/methods/ trends</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/methods/ trends</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA/methods/ trends</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">e123</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><accession-num><style face="normal" font="default" size="100%">17784778</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov'tReview</style></notes><auth-address><style face="normal" font="default" size="100%">Information Genomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology, Parc Scientifique de Luminy, Marseille, France. cedric.notredame@europe.com</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Gurbich, Tatiana A.</style></author><author><style face="normal" font="default" size="100%">Vlasov, Peter K.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selection for Functional Uniformity of tuf Duplicates in Gamma-proteobacteria</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">215-218</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Having an extra copy of a gene is thought to provide some functional redundancy, which results in a higher rate of evolution in duplicated genes. In this article, we estimate the impact of gene duplication on the selection of tuf paralogs, and we find that in the absence of gene conversion, tuf paralogs have evolved significantly slower than when gene conversion has been a factor in their evolution. Thus, tuf gene copies evolve under a selective pressure that ensures their functional uniformity, and gene conversion reduces selection against amino acid substitutions that affect the function of the encoded protein, EF-Tu.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bazykin, Georgii A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Brudno, Michael</style></author><author><style face="normal" font="default" size="100%">Poliakov, Alexander</style></author><author><style face="normal" font="default" size="100%">Dubchak, Inna</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extensive Parallelism in Protein Evolution</style></title><secondary-title><style face="normal" font="default" size="100%">Biol Direct</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">20-20</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Independently evolving lineages mostly accumulate different changes, which leads to their gradual divergence. However, parallel accumulation of identical changes is also common, especially in traits with only a small number of possible states. RESULTS: We characterize parallelism in evolution of coding sequences in three four-species sets of genomes of mammals, Drosophila, and yeasts. Each such set contains two independent evolutionary paths, which we call paths I and II. An amino acid replacement which occurred along path I also occurs along path II with the probability 50-80% of that expected under selective neutrality. Thus, the per site rate of parallel evolution of proteins is several times higher than their average rate of evolution, but still lower than the rate of evolution of neutral sequences. This deficit may be caused by changes in the fitness landscape, leading to a replacement being possible along path I but not along path II. However, constant, weak selection assumed by the nearly neutral model of evolution appears to be a more likely explanation. Then, the average coefficient of selection associated with an amino acid replacement, in the units of the effective population size, must exceed approximately 0.4, and the fraction of effectively neutral replacements must be below approximately 30%. At a majority of evolvable amino acid sites, only a relatively small number of different amino acids is permitted. CONCLUSION: High, but below-neutral, rates of parallel amino acid replacements suggest that a majority of amino acid replacements that occur in evolution are subject to weak, but non-trivial, selection, as predicted by Ohta's nearly-neutral theory.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Plotnikova, Olga V.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Vlasov, Peter K.</style></author><author><style face="normal" font="default" size="100%">Grigorenko, Anastasia P.</style></author><author><style face="normal" font="default" size="100%">Ginter, Evgeny K.</style></author><author><style face="normal" font="default" size="100%">Rogaev, Evgeny I.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Conversion and Compensatory Evolution of the Gamma-crystallin Genes and Identification of a Cataractogenic Mutation that Reverses the Sequence of the Human CRYGD gene to an Ancestral State</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><volume><style face="normal" font="default" size="100%">81</style></volume><pages><style face="normal" font="default" size="100%">32-43</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We identified a mutation in the CRYGD gene (P23S) of the gamma-crystallin gene cluster that is associated with a polymorphic congenital cataract that occurs with frequency of approximately 0.3% in a human population. To gain insight into the molecular mechanism of the pathogenesis of gamma-crystallin isoforms, we undertook an evolutionary analysis of the available mammalian and newly obtained primate sequences of the gamma-crystallin genes. The cataract-associated serine at site 23 corresponds to the ancestral state, since it was found in CRYGD of a lower primate and all the surveyed nonprimate mammals. Crystallin proteins include two structurally similar domains, and substitutions in mammalian CRYGD protein at site 23 of the first domain were always associated with substitutions in the structurally reciprocal sites 109 and 136 of the second domain. These data suggest that the cataractogenic effect of serine at site 23 in the N-terminal domain of CRYGD may be compensated indirectly by amino acid changes in a distal domain. We also found that gene conversion was a factor in the evolution of the gamma-crystallin gene cluster throughout different mammalian clades. The high rate of gene conversion observed between the functional CRYGD gene and two primate gamma-crystallin pseudogenes (CRYGEP1 and CRYGFP1) coupled with a surprising finding of apparent negative selection in primate pseudogenes suggest a deleterious impact of recently derived pseudogenes involved in gene conversion in the gamma-crystallin gene cluster.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Popadin, Konstantin Yu</style></author><author><style face="normal" font="default" size="100%">Mamirova, Leila A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Manually Curated Database of Tetrapod Mitochondrially Encoded tRNA Sequences and Secondary Structures</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www-personal.umich.edu/~kondrash/Database/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">441-441</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Mitochondrial tRNAs have been the subject of study for structural biologists interested in their secondary structure characteristics, evolutionary biologists have researched patterns of compensatory and structural evolution and medical studies have been directed towards understanding the basis of human disease. However, an up to date, manually curated database of mitochondrially encoded tRNAs from higher animals is currently not available. DESCRIPTION: We obtained the complete mitochondrial sequence for 277 tetrapod species from GenBank and re-annotated all of the tRNAs based on a multiple alignment of each tRNA gene and secondary structure prediction made independently for each tRNA. The mitochondrial (mt) tRNA sequences and the secondary structure based multiple alignments are freely available as Supplemental Information online. CONCLUSION: We compiled a manually curated database of mitochondrially encoded tRNAs from tetrapods with completely sequenced genomes. In the course of our work, we reannotated more than 10% of all tetrapod mt-tRNAs and subsequently predicted the secondary structures of 6060 mitochondrial tRNAs. This carefully constructed database can be utilized to enhance our knowledge in several different fields including the evolution of mt-tRNA secondary structure and prediction of pathogenic mt-tRNA mutations. In addition, researchers reporting novel mitochondrial genome sequences should check their tRNA gene annotations against our database to ensure a higher level of fidelity of their annotation.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Retelska, D.</style></author><author><style face="normal" font="default" size="100%">Beaudoing, E.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Jongeneel, C. V.</style></author><author><style face="normal" font="default" size="100%">Bucher, P</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Vertebrate conserved non coding DNA regions have a high persistence length and a short persistence time</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Genomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Conserved Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Intergenic/ genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Drosophila/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Insect/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome/ genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Time Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Vertebrates/ genetics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">398</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The comparison of complete genomes has revealed surprisingly large numbers of conserved non-protein-coding (CNC) DNA regions. However, the biological function of CNC remains elusive. CNC differ in two aspects from conserved protein-coding regions. They are not conserved across phylum boundaries, and they do not contain readily detectable sub-domains. Here we characterize the persistence length and time of CNC and conserved protein-coding regions in the vertebrate and insect lineages. RESULTS: The persistence length is the length of a genome region over which a certain level of sequence identity is consistently maintained. The persistence time is the evolutionary period during which a conserved region evolves under the same selective constraints. Our main findings are: (i) Insect genomes contain 1.60 times less conserved information than vertebrates; (ii) Vertebrate CNC have a higher persistence length than conserved coding regions or insect CNC; (iii) CNC have shorter persistence times as compared to conserved coding regions in both lineages. CONCLUSION: Higher persistence length of vertebrate CNC indicates that the conserved information in vertebrates and insects is organized in functional elements of different lengths. These findings might be related to the higher morphological complexity of vertebrates and give clues about the structure of active CNC elements. Shorter persistence time might explain the previously puzzling observations of highly conserved CNC within each phylum, and of a lack of conservation between phyla. It suggests that CNC divergence might be a key factor in vertebrate evolution. Further evolutionary studies will help to relate individual CNC to specific developmental processes.</style></abstract><accession-num><style face="normal" font="default" size="100%">17973996</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Computational Cancer Genomics Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland. Dorota.Retelska@isrec.ch</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, H.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The human phylome.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2007-8-6-r10</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">R109</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Phylogenomics analyses serve to establish evolutionary relationships among organisms and their genes. A phylome, the complete collection of all gene phylogenies in a genome, constitutes a valuable source of information, but its use in large genomes still constitutes a technical challenge. The use of phylomes also requires the development of new methods that help us to interpret them. RESULTS: We reconstruct here the human phylome, which includes the evolutionary relationships of all human proteins and their homologs among 39 fully sequenced eukaryotes. Phylogenetic techniques used include alignment trimming, branch length optimization, evolutionary model testing and maximum likelihood and Bayesian methods. Although differences with alternative topologies are minor, most of the trees support the Coelomata and Unikont hypotheses as well as the grouping of primates with laurasatheria to the exclusion of rodents. We assess the extent of gene duplication events and their relationship with the functional roles of the protein families involved. We find support for at least one, and probably two, rounds of whole genome duplications before vertebrate radiation. Using a novel algorithm that is independent from a species phylogeny, we derive orthology and paralogy relationships of human proteins among eukaryotic genomes. CONCLUSION: Topological variations among phylogenies for different genes are to be expected, highlighting the danger of gene-sampling effects in phylogenomic analyses. Several links can be established between the functions of gene families duplicated at certain phylogenetic splits and major evolutionary transitions in those lineages. The pipeline implemented here can be easily adapted for use in other organisms.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Messeguer, X.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiple non-collinear TF-map alignments of promoter regions.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2105-8-13</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">138</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The analysis of the promoter sequence of genes with similar expression patterns is a basic tool to annotate common regulatory elements. Multiple sequence alignments are on the basis of most comparative approaches. The characterization of regulatory regions from co-expressed genes at the sequence level, however, does not yield satisfactory results in many occasions as promoter regions of genes sharing similar expression programs often do not show nucleotide sequence conservation. RESULTS: In a recent approach to circumvent this limitation, we proposed to align the maps of predicted transcription factors (referred as TF-maps) instead of the nucleotide sequence of two related promoters, taking into account the label of the corresponding factor and the position in the primary sequence. We have now extended the basic algorithm to permit multiple promoter comparisons using the progressive alignment paradigm. In addition, non-collinear conservation blocks might now be identified in the resulting alignments. We have optimized the parameters of the algorithm in a small, but well-characterized collection of human-mouse-chicken-zebrafish orthologous gene promoters. CONCLUSION: Results in this dataset indicate that TF-map alignments are able to detect high-level regulatory conservation at the promoter and the 3'UTR gene regions, which cannot be detected by the typical sequence alignments. Three particular examples are introduced here to illustrate the power of the multiple TF-map alignments to characterize conserved regulatory elements in absence of sequence similarity. We consider this kind of approach can be extremely useful in the future to annotate potential transcription factor binding sites on sets of co-regulated genes from high-throughput expression experiments.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gauthier, Jacques-Antoine</style></author><author><style face="normal" font="default" size="100%">Widmer, Eric D.</style></author><author><style face="normal" font="default" size="100%">Bucher, Philipp</style></author><author><style face="normal" font="default" size="100%">Notredame, Cédric</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">{How Much Does it Cost? Optimization of Costs in Sequence Analysis of Social Science Data}</style></title><secondary-title><style face="normal" font="default" size="100%">Sociological Methods and Research, Forthcoming</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">empirical cost optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">optimal matching</style></keyword><keyword><style  face="normal" font="default" size="100%">sequence analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">trajectories</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><publisher><style face="normal" font="default" size="100%">SSRN</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Accepted Paper Series</style></work-type></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Armougom, F.</style></author><author><style face="normal" font="default" size="100%">Poirot, O.</style></author><author><style face="normal" font="default" size="100%">Moretti, S.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author><author><style face="normal" font="default" size="100%">Bucher, P</style></author><author><style face="normal" font="default" size="100%">Keduas, V.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">APDB: a web server to evaluate the accuracy of sequence alignments using structural information</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Conserved Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins/ chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology, Amino Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">2439-40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The APDB webserver uses structural information to evaluate the alignment of sequences with known structures. It returns a score correlated to the overall alignment accuracy as well as a local evaluation. Any sequence alignment can be analyzed with APDB provided it includes at least two proteins with known structures. Sequences without a known structure are simply ignored and do not contribute to the scoring procedure. AVAILABILITY: APDB is part of the T-Coffee suite of tools for alignment analysis, it is available on www.tcoffee.org. A stand-alone version of the package is also available as a freeware open source from the same address.</style></abstract><accession-num><style face="normal" font="default" size="100%">17032685</style></accession-num><notes><style face="normal" font="default" size="100%">Evaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR-13288, Marseille cedex 09, France.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aury, JM.</style></author><author><style face="normal" font="default" size="100%">Jaillon, O.</style></author><author><style face="normal" font="default" size="100%">Duret, L.</style></author><author><style face="normal" font="default" size="100%">Noel, B.</style></author><author><style face="normal" font="default" size="100%">Jubin, C.</style></author><author><style face="normal" font="default" size="100%">Porcel, BM.</style></author><author><style face="normal" font="default" size="100%">Ségurens, B.</style></author><author><style face="normal" font="default" size="100%">Daubin, V.</style></author><author><style face="normal" font="default" size="100%">Anthouard, V.</style></author><author><style face="normal" font="default" size="100%">Aiach, N.</style></author><author><style face="normal" font="default" size="100%">Arnaiz, O.</style></author><author><style face="normal" font="default" size="100%">Billaut, A.</style></author><author><style face="normal" font="default" size="100%">Beisson, J.</style></author><author><style face="normal" font="default" size="100%">Blanc, I.</style></author><author><style face="normal" font="default" size="100%">Bouhouche, K.</style></author><author><style face="normal" font="default" size="100%">Câmara, F.</style></author><author><style face="normal" font="default" size="100%">Duharcourt, S.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Gogendeau, D.</style></author><author><style face="normal" font="default" size="100%">Katinka, M.</style></author><author><style face="normal" font="default" size="100%">Keller, AM.</style></author><author><style face="normal" font="default" size="100%">Kissmehl, R.</style></author><author><style face="normal" font="default" size="100%">Klotz, C.</style></author><author><style face="normal" font="default" size="100%">Koll, F.</style></author><author><style face="normal" font="default" size="100%">Le Mouël, A.</style></author><author><style face="normal" font="default" size="100%">Lepère, G.</style></author><author><style face="normal" font="default" size="100%">Malinsky, S.</style></author><author><style face="normal" font="default" size="100%">Nowacki, M.</style></author><author><style face="normal" font="default" size="100%">Nowak, JK.</style></author><author><style face="normal" font="default" size="100%">Plattner, H.</style></author><author><style face="normal" font="default" size="100%">Poulain, J.</style></author><author><style face="normal" font="default" size="100%">Ruiz, F.</style></author><author><style face="normal" font="default" size="100%">Serrano, V.</style></author><author><style face="normal" font="default" size="100%">Zagulski, M.</style></author><author><style face="normal" font="default" size="100%">Dessen, P.</style></author><author><style face="normal" font="default" size="100%">Bétermier, M.</style></author><author><style face="normal" font="default" size="100%">Weissenbach, J.</style></author><author><style face="normal" font="default" size="100%">Scarpelli, C.</style></author><author><style face="normal" font="default" size="100%">Schächter, V.</style></author><author><style face="normal" font="default" size="100%">Sperling, L.</style></author><author><style face="normal" font="default" size="100%">Meyer, E.</style></author><author><style face="normal" font="default" size="100%">Cohen, J.</style></author><author><style face="normal" font="default" size="100%">Wincker, P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Global trends of whole-genome duplications revealed by the ciliate Paramecium tetraurelia.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0523</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7116</style></number><volume><style face="normal" font="default" size="100%">444</style></volume><pages><style face="normal" font="default" size="100%">171–178</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The duplication of entire genomes has long been recognized as having great potential for evolutionary novelties, but the mechanisms underlying their resolution through gene loss are poorly understood. Here we show that in the unicellular eukaryote Paramecium tetraurelia, a ciliate, most of the nearly 40,000 genes arose through at least three successive whole-genome duplications. Phylogenetic analysis indicates that the most recent duplication coincides with an explosion of speciation events that gave rise to the P. aurelia complex of 15 sibling species. We observed that gene loss occurs over a long timescale, not as an initial massive event. Genes from the same metabolic pathway or protein complex have common patterns of gene loss, and highly expressed genes are over-retained after all duplications. The conclusion of this analysis is that many genes are maintained after whole-genome duplication not because of functional innovation but because of gene dosage constraints.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Messeguer, X.</style></author><author><style face="normal" font="default" size="100%">Smith, TF.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcription factor map alignment of promoter regions.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371/journal.pcbi.002004</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">e49</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels–to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human-mouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Armougom, F.</style></author><author><style face="normal" font="default" size="100%">Moretti, S.</style></author><author><style face="normal" font="default" size="100%">Keduas, V.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The iRMSD: a local measure of sequence alignment accuracy using structural information</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Conserved Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Sensitivity and Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 15</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">14</style></number><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">e35-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: We introduce the iRMSD, a new type of RMSD, independent from any structure superposition and suitable for evaluating sequence alignments of proteins with known structures. RESULTS: We demonstrate that the iRMSD is equivalent to the standard RMSD although much simpler to compute and we also show that it is suitable for comparing sequence alignments and benchmarking multiple sequence alignment methods. We tested the iRMSD score on 6 established multiple sequence alignment packages and found the results to be consistent with those obtained using an established reference alignment collection like Prefab. AVAILABILITY: The iRMSD is part of the T-Coffee package and is distributed as an open source freeware (http://www.tcoffee.org/).</style></abstract><accession-num><style face="normal" font="default" size="100%">16873492</style></accession-num><notes><style face="normal" font="default" size="100%">Evaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov'tValidation Studies</style></notes><auth-address><style face="normal" font="default" size="100%">Laboratoire Information Genomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM) Parc Scientifique de Luminy, case 934, 163 Avenue de Luminy, FR-13288, Marseille cedex 09.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moretti, S.</style></author><author><style face="normal" font="default" size="100%">Reinier, F.</style></author><author><style face="normal" font="default" size="100%">Poirot, O.</style></author><author><style face="normal" font="default" size="100%">Armougom, F.</style></author><author><style face="normal" font="default" size="100%">Audic, S.</style></author><author><style face="normal" font="default" size="100%">Keduas, V.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PROTOGENE: turning amino acid alignments into bona fide CDS nucleotide alignments</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">W600-3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe Protogene, a server that can turn a protein multiple sequence alignment into the equivalent alignment of the original gene coding DNA. Protogene relies on a pipeline where every initial protein sequence is BLASTed against RefSeq or NR. The annotation associated with potential matches is used to identify the gene sequence. This gene sequence is then aligned with the query protein using Exonerate in order to extract a coding nucleotide sequence matching the original protein. Protogene can handle protein fragments and will return every CDS coding for a given protein, even if they occur in different genomes. Protogene is available from http://www.tcoffee.org/.</style></abstract><accession-num><style face="normal" font="default" size="100%">16845080</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Information Genomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR 13288, Marseille cedex 09, France.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Armougom, F.</style></author><author><style face="normal" font="default" size="100%">Moretti, S.</style></author><author><style face="normal" font="default" size="100%">Poirot, O.</style></author><author><style face="normal" font="default" size="100%">Audic, S.</style></author><author><style face="normal" font="default" size="100%">Dumas, P.</style></author><author><style face="normal" font="default" size="100%">Schaeli, B.</style></author><author><style face="normal" font="default" size="100%">Keduas, V.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expresso: automatic incorporation of structural information in multiple sequence alignments using 3D-Coffee</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Databases, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">W604-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Expresso is a multiple sequence alignment server that aligns sequences using structural information. The user only needs to provide sequences. The server runs BLAST to identify close homologues of the sequences within the PDB database. These PDB structures are used as templates to guide the alignment of the original sequences using structure-based sequence alignment methods like SAP or Fugue. The final result is a multiple sequence alignment of the original sequences based on the structural information of the templates. An advanced mode makes it possible to either upload private structures or specify which PDB templates should be used to model each sequence. Providing the suitable structural information is available, Expresso delivers sequence alignments with accuracy comparable with structure-based alignments. The server is available on http://www.tcoffee.org/.</style></abstract><accession-num><style face="normal" font="default" size="100%">16845081</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Laboratoire Information Genomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Valcárcel, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Unweaving the meanings of messenger RNA sequences.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol. Cell</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.molcel.2006.07.00</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">150–151</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In addition to protein-coding information, mRNAs harbor regulatory sequences necessary for appropriate processing of their precursors. Goren et al. (2006) and Wang et al. (2006) explore the diversity of these signals and the rules by which they function.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Farré, D.</style></author><author><style face="normal" font="default" size="100%">Albà, MM.</style></author><author><style face="normal" font="default" size="100%">Messeguer, X.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ABS: a database of Annotated regulatory Binding Sites from orthologous promoters.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkj11</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">D63–D67</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Information about the genomic coordinates and the sequence of experimentally identified transcription factor binding sites is found scattered under a variety of diverse formats. The availability of standard collections of such high-quality data is important to design, evaluate and improve novel computational approaches to identify binding motifs on promoter sequences from related genes. ABS (http://genome.imim.es/datasets/abs2005/index.html) is a public database of known binding sites identified in promoters of orthologous vertebrate genes that have been manually curated from bibliography. We have annotated 650 experimental binding sites from 68 transcription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. A simple and easy-to-use web interface facilitates data retrieval allowing different views of the information. In addition, the release 1.0 of ABS includes a customizable generator of artificial datasets based on the known sites contained in the collection and an evaluation tool to aid during the training and the assessment of motif-finding programs.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Dabbouseh, N.</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, ET.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Thomson, TM.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tandem chimerism as a means to increase protein complexity in the human genome.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.414590</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">37–44</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The &quot;one-gene, one-protein&quot; rule, coined by Beadle and Tatum, has been fundamental to molecular biology. The rule implies that the genetic complexity of an organism depends essentially on its gene number. The discovery, however, that alternative gene splicing and transcription are widespread phenomena dramatically altered our understanding of the genetic complexity of higher eukaryotic organisms; in these, a limited number of genes may potentially encode a much larger number of proteins. Here we investigate yet another phenomenon that may contribute to generate additional protein diversity. Indeed, by relying on both computational and experimental analysis, we estimate that at least 4%-5% of the tandem gene pairs in the human genome can be eventually transcribed into a single RNA sequence encoding a putative chimeric protein. While the functional significance of most of these chimeric transcripts remains to be determined, we provide strong evidence that this phenomenon does not correspond to mere technical artifacts and that it is a common mechanism with the potential of generating hundreds of additional proteins in the human genome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computational approaches for the prediction of protein function in the mitochondrion.</style></title><secondary-title><style face="normal" font="default" size="100%">Am. J. Physiol., Cell Physiol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1152/ajpcell.00225.2006</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">291</style></volume><pages><style face="normal" font="default" size="100%">C1121–C1128</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Understanding a complex biological system, such as the mitochondrion, requires the identification of the complete repertoire of proteins targeted to the organelle, the characterization of these, and finally, the elucidation of the functional and physical interactions that occur within the mitochondrion. In the last decade, significant developments have contributed to increase our understanding of the mitochondrion, and among these, computational research has played a significant role. Not only general bioinformatics tools have been applied in the context of the mitochondrion, but also some computational techniques have been specifically developed to address problems that arose from within the mitochondrial research field. In this review the contribution of bioinformatics to mitochondrial biology is addressed through a survey of current computational methods that can be applied to predict which proteins will be localized to the mitochondrion and to unravel their functional interactions.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Ogurtsov, Aleksey Y.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selection in Favor of Nucleotides G and C Diversifies Evolution Rates and Levels of Polymorphism at Mammalian Synonymous Sites</style></title><secondary-title><style face="normal" font="default" size="100%">J Theor Biol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">240</style></volume><pages><style face="normal" font="default" size="100%">616-626</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The impact of synonymous nucleotide substitutions on fitness in mammals remains controversial. Despite some indications of selective constraint, synonymous sites are often assumed to be neutral, and the rate of their evolution is used as a proxy for mutation rate. We subdivide all sites into four classes in terms of the mutable CpG context, nonCpG, postC, preG, and postCpreG, and compare four-fold synonymous sites and intron sites residing outside transposable elements. The distribution of the rate of evolution across all synonymous sites is trimodal. Rate of evolution at nonCpG synonymous sites, not preceded by C and not followed by G, is approximately 10% below that at such intron sites. In contrast, rate of evolution at postCpreG synonymous sites is approximately 30% above that at such intron sites. Finally, synonymous and intron postC and preG sites evolve at similar rates. The relationship between the levels of polymorphism at the corresponding synonymous and intron sites is very similar to that between their rates of evolution. Within every class, synonymous sites are occupied by G or C much more often than intron sites, whose nucleotide composition is consistent with neutral mutation-drift equilibrium. These patterns suggest that synonymous sites are under weak selection in favor of G and C, with the average coefficient s approximately 0.25/Ne approximately 10(-5), where Ne is the effective population size. Such selection decelerates evolution and reduces variability at sites with symmetric mutation, but has the opposite effects at sites where the favored nucleotides are more mutable. The amino-acid composition of proteins dictates that many synonymous sites are CpGprone, which causes them, on average, to evolve faster and to be more polymorphic than intron sites. An average genotype carries approximately 10(7) suboptimal nucleotides at synonymous sites, implying synergistic epistasis in selection against them.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rogaev, Evgeny I.</style></author><author><style face="normal" font="default" size="100%">Moliaka, Yuri K.</style></author><author><style face="normal" font="default" size="100%">Malyarchuk, Boris A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Derenko, Miroslava V.</style></author><author><style face="normal" font="default" size="100%">Chumakov, Ilya</style></author><author><style face="normal" font="default" size="100%">Grigorenko, Anastasia P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Complete Mitochondrial Genome and Phylogeny of Pleistocene Mammoth Mammuthus Primigenius</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Biol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e73-e73</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Phylogenetic relationships between the extinct woolly mammoth (Mammuthus primigenius), and the Asian (Elephas maximus) and African savanna (Loxodonta africana) elephants remain unresolved. Here, we report the sequence of the complete mitochondrial genome (16,842 base pairs) of a woolly mammoth extracted from permafrost-preserved remains from the Pleistocene epoch–the oldest mitochondrial genome sequence determined to date. We demonstrate that well-preserved mitochondrial genome fragments, as long as approximately 1,600-1700 base pairs, can be retrieved from pre-Holocene remains of an extinct species. Phylogenetic reconstruction of the Elephantinae clade suggests that M. primigenius and E. maximus are sister species that diverged soon after their common ancestor split from the L. africana lineage. Low nucleotide diversity found between independently determined mitochondrial genomic sequences of woolly mammoths separated geographically and in time suggests that north-eastern Siberia was occupied by a relatively homogeneous population of M. primigenius throughout the late Pleistocene.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Role of Selection in Fixation of gene Duplications</style></title><secondary-title><style face="normal" font="default" size="100%">J Theor Biol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">239</style></volume><pages><style face="normal" font="default" size="100%">141-151</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">New genes commonly appear through complete or partial duplications of pre-existing genes. Duplications of long DNA segments are constantly produced by rare mutations, may become fixed in a population by selection or random drift, and are subject to divergent evolution of the paralogous sequences after fixation, although gene conversion can impede this process. New data shed some light on each of these processes. Mutations which involve duplications can occur through at least two different mechanisms, backward strand slippage during DNA replication and unequal crossing-over. The background rate of duplication of a complete gene in humans is 10(-9)-10(-10) per generation, although many genes located within hot-spots of large-scale mutation are duplicated much more often. Many gene duplications affect fitness strongly, and are responsible, through gene dosage effects, for a number of genetic diseases. However, high levels of intrapopulation polymorphism caused by presence or absence of long, gene-containing DNA segments imply that some duplications are not under strong selection. The polymorphism to fixation ratios appear to be approximately the same for gene duplications and for presumably selectively neutral nucleotide substitutions, which, according to the McDonald-Kreitman test, is consistent with selective neutrality of duplications. However, this pattern can also be due to negative selection against most of segregating duplications and positive selection for at least some duplications which become fixed. Patterns in post-fixation evolution of duplicated genes do not easily reveal the causes of fixations. Many gene duplications which became fixed recently in a variety of organisms were positively selected because the increased expression of the corresponding genes was beneficial. The effects of gene dosage provide a unified framework for studying all phases of the life history of a gene duplication. Application of well-known methods of evolutionary genetics to accumulating data on new, polymorphic, and fixed duplication will enhance our understanding of the role of natural selection in the evolution by gene duplication.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Babenko, Vladimir N.</style></author><author><style face="normal" font="default" size="100%">Basu, Malay K.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Rogozin, Igor B.</style></author><author><style face="normal" font="default" size="100%">Koonin, Eugene V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Signs of Positive Selection of Somatic Mutations in Human Cancers Detected by EST Sequence Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Cancer</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">36-36</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Carcinogenesis typically involves multiple somatic mutations in caretaker (DNA repair) and gatekeeper (tumor suppressors and oncogenes) genes. Analysis of mutation spectra of the tumor suppressor that is most commonly mutated in human cancers, p53, unexpectedly suggested that somatic evolution of the p53 gene during tumorigenesis is dominated by positive selection for gain of function. This conclusion is supported by accumulating experimental evidence of evolution of new functions of p53 in tumors. These findings prompted a genome-wide analysis of possible positive selection during tumor evolution. METHODS: A comprehensive analysis of probable somatic mutations in the sequences of Expressed Sequence Tags (ESTs) from malignant tumors and normal tissues was performed in order to access the prevalence of positive selection in cancer evolution. For each EST, the numbers of synonymous and non-synonymous substitutions were calculated. In order to identify genes with a signature of positive selection in cancers, these numbers were compared to: i) expected numbers and ii) the numbers for the respective genes in the ESTs from normal tissues. RESULTS: We identified 112 genes with a signature of positive selection in cancers, i.e., a significantly elevated ratio of non-synonymous to synonymous substitutions, in tumors as compared to 37 such genes in an approximately equal-sized EST collection from normal tissues. A substantial fraction of the tumor-specific positive-selection candidates have experimentally demonstrated or strongly predicted links to cancer. CONCLUSION: The results of EST analysis should be interpreted with extreme caution given the noise introduced by sequencing errors and undetected polymorphisms. Furthermore, an inherent limitation of EST analysis is that multiple mutations amenable to statistical analysis can be detected only in relatively highly expressed genes. Nevertheless, the present results suggest that positive selection might affect a substantial number of genes during tumorigenic somatic evolution.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Koonin, Eugene V.</style></author><author><style face="normal" font="default" size="100%">Morgunov, Igor G.</style></author><author><style face="normal" font="default" size="100%">Finogenova, Tatiana V.</style></author><author><style face="normal" font="default" size="100%">Kondrashova, Marie N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of Glyoxylate Cycle Enzymes in Metazoa: Evidence of Multiple Horizontal Transfer Events and Pseudogene Formation</style></title><secondary-title><style face="normal" font="default" size="100%">Biol Direct</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">31-31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The glyoxylate cycle is thought to be present in bacteria, protists, plants, fungi, and nematodes, but not in other Metazoa. However, activity of the glyoxylate cycle enzymes, malate synthase (MS) and isocitrate lyase (ICL), in animal tissues has been reported. In order to clarify the status of the MS and ICL genes in animals and get an insight into their evolution, we undertook a comparative-genomic study. RESULTS: Using sequence similarity searches, we identified MS genes in arthropods, echinoderms, and vertebrates, including platypus and opossum, but not in the numerous sequenced genomes of placental mammals. The regions of the placental mammals' genomes expected to code for malate synthase, as determined by comparison of the gene orders in vertebrate genomes, show clear similarity to the opossum MS sequence but contain stop codons, indicating that the MS gene became a pseudogene in placental mammals. By contrast, the ICL gene is undetectable in animals other than the nematodes that possess a bifunctional, fused ICL-MS gene. Examination of phylogenetic trees of MS and ICL suggests multiple horizontal gene transfer events that probably went in both directions between several bacterial and eukaryotic lineages. The strongest evidence was obtained for the acquisition of the bifunctional ICL-MS gene from an as yet unknown bacterial source with the corresponding operonic organization by the common ancestor of the nematodes. CONCLUSION: The distribution of the MS and ICL genes in animals suggests that either they encode alternative enzymes of the glyoxylate cycle that are not orthologous to the known MS and ICL or the animal MS acquired a new function that remains to be characterized. Regardless of the ultimate solution to this conundrum, the genes for the glyoxylate cycle enzymes present a remarkable variety of evolutionary events including unusual horizontal gene transfer from bacteria to animals.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wallace, I. M.</style></author><author><style face="normal" font="default" size="100%">O'Sullivan, O.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">M-Coffee: combining multiple sequence alignment methods with T-Coffee</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">1692-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We introduce M-Coffee, a meta-method for assembling multiple sequence alignments (MSA) by combining the output of several individual methods into one single MSA. M-Coffee is an extension of T-Coffee and uses consistency to estimate a consensus alignment. We show that the procedure is robust to variations in the choice of constituent methods and reasonably tolerant to duplicate MSAs. We also show that performances can be improved by carefully selecting the constituent methods. M-Coffee outperforms all the individual methods on three major reference datasets: HOMSTRAD, Prefab and Balibase. We also show that on a case-by-case basis, M-Coffee is twice as likely to deliver the best alignment than any individual method. Given a collection of pre-computed MSAs, M-Coffee has similar CPU requirements to the original T-Coffee. M-Coffee is a freeware open-source package available from http://www.tcoffee.org/.</style></abstract><accession-num><style face="normal" font="default" size="100%">16556910</style></accession-num><notes><style face="normal" font="default" size="100%">Evaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Ireland.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Frankish, A.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Chen, CK.</style></author><author><style face="normal" font="default" size="100%">Chrast, J.</style></author><author><style face="normal" font="default" size="100%">Lagarde, J.</style></author><author><style face="normal" font="default" size="100%">Gilbert, JG.</style></author><author><style face="normal" font="default" size="100%">Storey, R.</style></author><author><style face="normal" font="default" size="100%">Swarbreck, D.</style></author><author><style face="normal" font="default" size="100%">Rossier, C.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Hubbard, T.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">GENCODE: producing a reference annotation for ENCODE.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2006-7-s1-s</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7 Suppl 1</style></volume><pages><style face="normal" font="default" size="100%">S4.1–S4.9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The GENCODE consortium was formed to identify and map all protein-coding genes within the ENCODE regions. This was achieved by a combination of initial manual annotation by the HAVANA team, experimental validation by the GENCODE consortium and a refinement of the annotation based on these experimental results. RESULTS: The GENCODE gene features are divided into eight different categories of which only the first two (known and novel coding sequence) are confidently predicted to be protein-coding genes. 5' rapid amplification of cDNA ends (RACE) and RT-PCR were used to experimentally verify the initial annotation. Of the 420 coding loci tested, 229 RACE products have been sequenced. They supported 5' extensions of 30 loci and new splice variants in 50 loci. In addition, 46 loci without evidence for a coding sequence were validated, consisting of 31 novel and 15 putative transcripts. We assessed the comprehensiveness of the GENCODE annotation by attempting to validate all the predicted exon boundaries outside the GENCODE annotation. Out of 1,215 tested in a subset of the ENCODE regions, 14 novel exon pairs were validated, only two of them in intergenic regions. CONCLUSION: In total, 487 loci, of which 434 are coding, have been annotated as part of the GENCODE reference set available from the UCSC browser. Comparison of GENCODE annotation with RefSeq and ENSEMBL show only 40% of GENCODE exons are contained within the two sets, which is a reflection of the high number of alternative splice forms with unique exons annotated. Over 50% of coding loci have been experimentally verified by 5' RACE for EGASP and the GENCODE collaboration is continuing to refine its annotation of 1% human genome with the aid of experimental validation.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Flicek, P.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Lagarde, J.</style></author><author><style face="normal" font="default" size="100%">Denoeud, F.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, S.</style></author><author><style face="normal" font="default" size="100%">Ashburner, M.</style></author><author><style face="normal" font="default" size="100%">Bajic, VB.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Eyras, E.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Gingeras, TR.</style></author><author><style face="normal" font="default" size="100%">Harrow, J.</style></author><author><style face="normal" font="default" size="100%">Hubbard, T.</style></author><author><style face="normal" font="default" size="100%">Lewis, SE.</style></author><author><style face="normal" font="default" size="100%">Reese, MG.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EGASP: the human ENCODE Genome Annotation Assessment Project.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2006-7-s1-s</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7 Suppl 1</style></volume><pages><style face="normal" font="default" size="100%">S2.1–S231</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. RESULTS: The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could be verified. CONCLUSION: This is the first such experiment in human DNA, and we have followed the standards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe the results presented here contribute to the value of ongoing large-scale annotation projects and should guide further experimental methods when being scaled up to the entire human genome sequence.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Reese, MG.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EGASP: Introduction.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2006-7-s1-s</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7 Suppl 1</style></volume><pages><style face="normal" font="default" size="100%">S1.1–S1.3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mularoni, L.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Albà, MM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutation patterns of amino acid tandem repeats in the human proteome.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2006-7-4-r3</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">R33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Amino acid tandem repeats are found in nearly one-fifth of human proteins. Abnormal expansion of these regions is associated with several human disorders. To gain further insight into the mutational mechanisms that operate in this type of sequence, we have analyzed a large number of mutation variants derived from human expressed sequence tags (ESTs). RESULTS: We identified 137 polymorphic variants in 115 different amino acid tandem repeats. Of these, 77 contained amino acid substitutions and 60 contained gaps (expansions or contractions of the repeat unit). The analysis showed that at least about 21% of the repeats might be polymorphic in humans. We compared the mutations found in different types of amino acid repeats and in adjacent regions. Overall, repeats showed a five-fold increase in the number of gap mutations compared to adjacent regions, reflecting the action of slippage within the repetitive structures. Gap and substitution mutations were very differently distributed between different amino acid repeat types. Among repeats containing gap variants we identified several disease and candidate disease genes. CONCLUSION: This is the first report at a genome-wide scale of the types of mutations occurring in the amino acid repeat component of the human proteome. We show that the mutational dynamics of different amino acid repeat types are very diverse. We provide a list of loci with highly variable repeat structures, some of which may be potentially involved in disease.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Snel, B.</style></author><author><style face="normal" font="default" size="100%">van Zimmeren, F.</style></author><author><style face="normal" font="default" size="100%">Hemrika, W.</style></author><author><style face="normal" font="default" size="100%">Tabak, H.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Origin and evolution of the peroxisomal proteome.</style></title><secondary-title><style face="normal" font="default" size="100%">Biol. Direct</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1745-6150-1-8</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Peroxisomes are ubiquitous eukaryotic organelles involved in various oxidative reactions. Their enzymatic content varies between species, but the presence of common protein import and organelle biogenesis systems support a single evolutionary origin. The precise scenario for this origin remains however to be established. The ability of peroxisomes to divide and import proteins post-translationally, just like mitochondria and chloroplasts, supports an endosymbiotic origin. However, this view has been challenged by recent discoveries that mutant, peroxisome-less cells restore peroxisomes upon introduction of the wild-type gene, and that peroxisomes are formed from the Endoplasmic Reticulum. The lack of a peroxisomal genome precludes the use of classical analyses, as those performed with mitochondria or chloroplasts, to settle the debate. We therefore conducted large-scale phylogenetic analyses of the yeast and rat peroxisomal proteomes. RESULTS : Our results show that most peroxisomal proteins (39-58%) are of eukaryotic origin, comprising all proteins involved in organelle biogenesis or maintenance. A significant fraction (13-18%), consisting mainly of enzymes, has an alpha-proteobacterial origin and appears to be the result of the recruitment of proteins originally targeted to mitochondria. Consistent with the findings that peroxisomes are formed in the Endoplasmic Reticulum, we find that the most universally conserved Peroxisome biogenesis and maintenance proteins are homologous to proteins from the Endoplasmic Reticulum Assisted Decay pathway. CONCLUSION: Altogether our results indicate that the peroxisome does not have an endosymbiotic origin and that its proteins were recruited from pools existing within the primitive eukaryote. Moreover the reconstruction of primitive peroxisomal proteomes suggests that ontogenetically as well as phylogenetically, peroxisomes stem from the Endoplasmic Reticulum. REVIEWERS: This article was reviewed by Arcady Mushegian, Gáspár Jékely and John Logsdon. OPEN PEER REVIEW: Reviewed by Arcady Mushegian, Gáspar Jékely and John Logsdon. For the full reviews, please go to the Reviewers' comments section.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Djebali, S.</style></author><author><style face="normal" font="default" size="100%">Delaplace, F.</style></author><author><style face="normal" font="default" size="100%">Roest Crollius, H.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exogean: a framework for annotating protein-coding genes in eukaryotic genomic DNA.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/gb-2006-7-s1-s7</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7 Suppl 1</style></volume><pages><style face="normal" font="default" size="100%">S7.1–S710</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Accurate and automatic gene identification in eukaryotic genomic DNA is more than ever of crucial importance to efficiently exploit the large volume of assembled genome sequences available to the community. Automatic methods have always been considered less reliable than human expertise. This is illustrated in the EGASP project, where reference annotations against which all automatic methods are measured are generated by human annotators and experimentally verified. We hypothesized that replicating the accuracy of human annotators in an automatic method could be achieved by formalizing the rules and decisions that they use, in a mathematical formalism.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Lineage-specific gene loss following mitochondrial endosymbiosis and its potential for function prediction in eukaryotes.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/bioinformatics/bti1124</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">21 Suppl 2</style></volume><pages><style face="normal" font="default" size="100%">ii144–ii150</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: The endosymbiotic origin of mitochondria has resulted in a massive horizontal transfer of genetic material from an alpha-proteobacterium to the early eukaryotes. Using large-scale phylogenetic analysis we have previously identified 630 orthologous groups of proteins derived from this event. Here we show that this proto-mitochondrial protein set has undergone extensive lineage-specific gene loss in the eukaryotes, with an average of three losses per orthologous group in a phylogeny of nine species. This gene loss has resulted in a high variability of the alphaproteobacterial-derived gene content of present-day eukaryotic genomes that might reflect functional adaptation to different environments. Proteins functioning in the same biochemical pathway tend to have a similar history of gene loss events, and we use this property to predict functional interactions among proteins in our set.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Cavalli, A.</style></author><author><style face="normal" font="default" size="100%">Pellarin, R.</style></author><author><style face="normal" font="default" size="100%">Caflisch, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of aggregation rate and aggregation-prone segments in polypeptide sequences.</style></title><secondary-title><style face="normal" font="default" size="100%">Protein Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1110/ps.051471205</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">2723–2734</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The reliable identification of beta-aggregating stretches in protein sequences is essential for the development of therapeutic agents for Alzheimer's and Parkinson's diseases, as well as other pathological conditions associated with protein deposition. Here, a model based on physicochemical properties and computational design of beta-aggregating peptide sequences is shown to be able to predict the aggregation rate over a large set of natural polypeptide sequences. Furthermore, the model identifies aggregation-prone fragments within proteins and predicts the parallel or anti-parallel beta-sheet organization in fibrils. The model recognizes different beta-aggregating segments in mammalian and nonmammalian prion proteins, providing insights into the species barrier for the transmission of the prion disease.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Pellarin, R.</style></author><author><style face="normal" font="default" size="100%">Cavalli, A.</style></author><author><style face="normal" font="default" size="100%">Caflisch, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Organism complexity anti-correlates with proteomic beta-aggregation propensity.</style></title><secondary-title><style face="normal" font="default" size="100%">Protein Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1110/ps.051473805</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">2735–2740</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We introduce a novel approach to estimate differences in the beta-aggregation potential of eukaryotic proteomes. The approach is based on a statistical analysis of the beta-aggregation propensity of polypeptide segments, which is calculated by an equation derived from first principles using the physicochemical properties of the natural amino acids. Our analysis reveals a significant decreasing trend of the overall beta-aggregation tendency with increasing organism complexity and longevity. A comparison with randomized proteomes shows that natural proteomes have a higher degree of polarization in both low and high beta-aggregation prone sequences. The former originates from the requirement of intrinsically disordered proteins, whereas the latter originates from the necessity of proteins with a stable folded structure.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sardiello, M.</style></author><author><style face="normal" font="default" size="100%">Annunziata, I.</style></author><author><style face="normal" font="default" size="100%">Roma, G.</style></author><author><style face="normal" font="default" size="100%">Ballabio, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sulfatases and sulfatase modifying factors: an exclusive and promiscuous relationship.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum. Mol. Genet.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/hmg/ddi351</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">21</style></number><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">3203–3217</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Sulfatases catalyze the hydrolysis of sulfate ester bonds from a wide variety of substrates. Several human inherited diseases are caused by the deficiency of individual sulfatases, while in patients with multiple sulfatase deficiency mutations in the Sulfatase Modifying Factor 1 (SUMF1) gene cause a defect in the post-translational modification of a cysteine residue into C(alpha)-formylglycine (FGly) at the active site of all sulfatases. This unique modification mechanism, which is required for catalytic activity, has been highly conserved during evolution. Here, we used a genomic approach to investigate the relationship between sulfatases and their modifying factors in humans and several model systems. First, we determined the complete catalog of human sulfatases, which comprises 17 members (versus 14 in rodents) including four novel ones (ARSH, ARSI, ARSJ and ARSK). Secondly, we showed that the active site, which is the target of the post-translational modification, is the most evolutionarily constrained region of sulfatases and shows intraspecies sequence convergence. Exhaustive sequence analyses of available proteomes indicate that sulfatases are the only likely targets of their modifying factors. Thirdly, we showed that sulfatases and ectonucleotide pyrophosphatases share significant homology at their active sites, suggesting a common evolutionary origin as well as similar catalytic mechanisms. Most importantly, gene association studies performed on prokaryotes suggested the presence of at least two additional mechanisms of cysteine-to-FGly conversion, which do not require SUMF1. These results may have important implications in the study of diseases caused by sulfatase deficiencies and in the development of therapeutic strategies.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castellano, S.</style></author><author><style face="normal" font="default" size="100%">Lobanov, AV.</style></author><author><style face="normal" font="default" size="100%">Chapple, C.</style></author><author><style face="normal" font="default" size="100%">Novoselov, SV.</style></author><author><style face="normal" font="default" size="100%">Albrecht, M.</style></author><author><style face="normal" font="default" size="100%">Hua, D.</style></author><author><style face="normal" font="default" size="100%">Lescure, A.</style></author><author><style face="normal" font="default" size="100%">Lengauer, T.</style></author><author><style face="normal" font="default" size="100%">Krol, A.</style></author><author><style face="normal" font="default" size="100%">Gladyshev, VN.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Diversity and functional plasticity of eukaryotic selenoproteins: identification and characterization of the SelJ family.</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Natl. Acad. Sci. U.S.A.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1073/pnas.050514610</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">45</style></number><volume><style face="normal" font="default" size="100%">102</style></volume><pages><style face="normal" font="default" size="100%">16188–16193</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Selenoproteins are a diverse group of proteins that contain selenocysteine (Sec), the 21st amino acid. In the genetic code, UGA serves as a termination signal and a Sec codon. This dual role has precluded the automatic annotation of selenoproteins. Recent advances in the computational identification of selenoprotein genes have provided a first glimpse of the size, functions, and phylogenetic diversity of eukaryotic selenoproteomes. Here, we describe the identification of a selenoprotein family named SelJ. In contrast to known selenoproteins, SelJ appears to be restricted to actinopterygian fishes and sea urchin, with Cys homologues only found in cnidarians. SelJ shows significant similarity to the jellyfish J1-crystallins and with them constitutes a distinct subfamily within the large family of ADP-ribosylation enzymes. Consistent with its potential role as a structural crystallin, SelJ has preferential and homogeneous expression in the eye lens in early stages of zebrafish development. A structural role for SelJ would be in contrast to the majority of known selenoenzymes. The unusually highly restricted phylogenetic distribution of SelJ, its specialization, and the comparative analysis of eukaryotic selenoproteomes reveal the diversity and functional plasticity of selenoproteins and point to a mosaic evolution of the use of Sec in proteins.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Rainey, D.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tracing the evolution of a large protein complex in the eukaryotes, NADH:ubiquinone oxidoreductase (Complex I).</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.jmb.2005.02.067</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">348</style></volume><pages><style face="normal" font="default" size="100%">857–870</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The increasing availability of sequenced genomes enables the reconstruction of the evolutionary history of large protein complexes. Here, we trace the evolution of NADH:ubiquinone oxidoreductase (Complex I), which has increased in size, by so-called supernumary subunits, from 14 subunits in the bacteria to 30 in the plants and algae, 37 in the fungi and 46 in the mammals. Using a combination of pair-wise and profile-based sequence comparisons at the levels of proteins and the DNA of the sequenced eukaryotic genomes, combined with phylogenetic analyses to establish orthology relationships, we were able to (1) trace the origin of six of the supernumerary subunits to the alpha-proteobacterial ancestor of the mitochondria, (2) detect previously unidentified homology relations between subunits from fungi and mammals, (3) detect previously unidentified subunits in the genomes of several species and (4) document several cases of gene duplications among supernumerary subunits in the eukaryotes. One of these, a duplication of N7BM (B17.2), is particularly interesting as it has been lost from genomes that have also lost Complex I proteins, making it a candidate for a Complex I interacting protein. A parsimonious reconstruction of eukaryotic Complex I evolution shows an initial increase in size that predates the separation of plants, fungi and metazoa, followed by a gradual adding and incidental losses of subunits in the various evolutionary lineages. This evolutionary scenario is in contrast to that for Complex I in the prokaryotes, for which the combination of several separate, and previously independently functioning modules into a single complex has been proposed.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Boxma, B.</style></author><author><style face="normal" font="default" size="100%">de Graaf, RM.</style></author><author><style face="normal" font="default" size="100%">van der Staay, GW.</style></author><author><style face="normal" font="default" size="100%">van Alen, TA.</style></author><author><style face="normal" font="default" size="100%">Ricard, G.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">van Hoek, AH.</style></author><author><style face="normal" font="default" size="100%">Moon-van der Staay, SY.</style></author><author><style face="normal" font="default" size="100%">Koopman, WJ.</style></author><author><style face="normal" font="default" size="100%">van Hellemond, JJ.</style></author><author><style face="normal" font="default" size="100%">Tielens, AG.</style></author><author><style face="normal" font="default" size="100%">Friedrich, T.</style></author><author><style face="normal" font="default" size="100%">Veenhuis, M.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author><author><style face="normal" font="default" size="100%">Hackstein, JH.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An anaerobic mitochondrion that produces hydrogen.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0334</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7029</style></number><volume><style face="normal" font="default" size="100%">434</style></volume><pages><style face="normal" font="default" size="100%">74–79</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Hydrogenosomes are organelles that produce ATP and hydrogen, and are found in various unrelated eukaryotes, such as anaerobic flagellates, chytridiomycete fungi and ciliates. Although all of these organelles generate hydrogen, the hydrogenosomes from these organisms are structurally and metabolically quite different, just like mitochondria where large differences also exist. These differences have led to a continuing debate about the evolutionary origin of hydrogenosomes. Here we show that the hydrogenosomes of the anaerobic ciliate Nyctotherus ovalis, which thrives in the hindgut of cockroaches, have retained a rudimentary genome encoding components of a mitochondrial electron transport chain. Phylogenetic analyses reveal that those proteins cluster with their homologues from aerobic ciliates. In addition, several nucleus-encoded components of the mitochondrial proteome, such as pyruvate dehydrogenase and complex II, were identified. The N. ovalis hydrogenosome is sensitive to inhibitors of mitochondrial complex I and produces succinate as a major metabolic end product–biochemical traits typical of anaerobic mitochondria. The production of hydrogen, together with the presence of a genome encoding respiratory chain components, and biochemical features characteristic of anaerobic mitochondria, identify the N. ovalis organelle as a missing link between mitochondria and hydrogenosomes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">López-Bigas, N.</style></author><author><style face="normal" font="default" size="100%">Audit, B.</style></author><author><style face="normal" font="default" size="100%">Ouzounis, C.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Are splicing mutations the most frequent cause of hereditary disease?</style></title><secondary-title><style face="normal" font="default" size="100%">FEBS Lett.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.febslet.2005.02.04</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">579</style></volume><pages><style face="normal" font="default" size="100%">1900–1903</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Disease-causing point mutations are assumed to act predominantly through subsequent individual changes in the amino acid sequence that impair the normal function of proteins. However, point mutations can have a more dramatic effect by altering the splicing pattern of the gene. Here, we describe an approach to estimate the overall importance of splicing mutations. This approach takes into account the complete set of genes known to be involved in disease and suggest that, contrary to current assumptions, many mutations causing disease may actually be affecting the splicing pattern of the genes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Snel, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Variation and evolution of biomolecular systems: searching for functional relevance.</style></title><secondary-title><style face="normal" font="default" size="100%">FEBS Lett.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.febslet.2005.02.004</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">579</style></volume><pages><style face="normal" font="default" size="100%">1839–1845</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The availability of genome sequences and functional genomics data from multiple species enables us to compare the composition of biomolecular systems like biochemical pathways and protein complexes between species. Here, we review small- and large-scale, &quot;genomics-based&quot; approaches to biomolecular systems variation. In general, caution is required when comparing the results of bioinformatics analyses of genomes or of functional genomics data between species. Limitations to the sensitivity of sequence analysis tools and the noisy nature of genomics data tend to lead to systematic overestimates of the amount of variation. Nevertheless, the results from detailed manual analyses, and of large-scale analyses that filter out systematic biases, point to a large amount of variation in the composition of biomolecular systems. Such observations challenge our understanding of the function of the systems and their individual components and can potentially facilitate the identification and functional characterization of sub-systems within a system. Mapping the inter-species variation of complex biomolecular systems on a phylogenetic species tree allows one to reconstruct their evolution.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Szafranski, K.</style></author><author><style face="normal" font="default" size="100%">Lehmann, R.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Glöckner, G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gene organization features in A/T-rich organisms.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Evol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s00239-004-0201-</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">60</style></volume><pages><style face="normal" font="default" size="100%">90–98</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Several species have genomes in which the four nucleotides are not equally represented (Glöckner 2000). Interestingly, shifts to very high A/T or G/C levels can occur in several distinct branches of the tree of life. The underlying reasons for these shifts therefore may be of different origin. Now entire chromosome sequences from two different A/T-rich genomes, Dictyostelium discoideum and Plasmodium falciparum, are available (Bowman et al. 1999; Gardner et al. 2002; Glöckner et al. 2002). This gives us the opportunity to investigate how a high A/T content may influence the signals that are the landmarks for gene specification. We found that, in contrast with most known metazoan and plant genomes, splice signals contain, little information other than the canonical GT-AG dinucleotides. Intron lengths in A/T rich organisms, on the other hand, are comparable to those of other lower eukaryotes. Intergenic regions show, dependent on the orientation of adjacent genes, a size pattern with a ratio of 1 (3'-3') to 2 (3'-5') to 3 (5'-5'). Overall, gene organization patterns seem not to be influenced by the A/T bias. Surprisingly, the slightly higher A/T content of the P. falciparum genome compared to that of D. discoideum (80.1 versus 77.4%) is not achieved by increased A/T richness in intergenic regions. Instead both the shift of the nucleotide usage in coding regions to A/T-rich codons and the longer intergenic regions make an equal contribution to the higher A/T content in this organism.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of splice sites in mammals and chicken.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.310880</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">111–119</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We have carried out an initial analysis of the dynamics of the recent evolution of the splice-sites sequences on a large collection of human, rodent (mouse and rat), and chicken introns. Our results indicate that the sequences of splice sites are largely homogeneous within tetrapoda. We have also found that orthologous splice signals between human and rodents and within rodents are more conserved than unrelated splice sites, but the additional conservation can be explained mostly by background intron conservation. In contrast, additional conservation over background is detectable in orthologous mammalian and chicken splice sites. Our results also indicate that the U2 and U12 intron classes seem to have evolved independently since the split of mammals and birds; we have not been able to find a convincing case of interconversion between these two classes in our collections of orthologous introns. Similarly, we have not found a single case of switching between AT-AC and GT-AG subtypes within U12 introns, suggesting that this event has been a rare occurrence in recent evolutionary times. Switching between GT-AG and the noncanonical GC-AG U2 subtypes, on the contrary, does not appear to be unusual; in particular, T to C mutations appear to be relatively well tolerated in GT-AG introns with very strong donor sites.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author><author><style face="normal" font="default" size="100%">Spronk, CA.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Snel, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Combining data from genomes, Y2H and 3D structure indicates that BolA is a reductase interacting with a glutaredoxin.</style></title><secondary-title><style face="normal" font="default" size="100%">FEBS Lett.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.febslet.2004.11.111</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">579</style></volume><pages><style face="normal" font="default" size="100%">591–596</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Genomes, functional genomics data and 3D structure reflect different aspects of protein function. Here, we combine these data to predict that BolA, a widely distributed protein family with unknown function, is a reductase that interacts with a glutaredoxin. Comparisons at the 3D structure level as well as at the sequence profile level indicate homology between BolA and OsmC, an enzyme that reduces organic peroxides. Complementary to this, comparative analyses of genomes and genomics data provide strong evidence of an interaction between BolA and the mono-thiol glutaredoxin family. The interaction between BolA and a mono-thiol glutaredoxin is of particular interest because BolA does not, in contrast to its homolog OsmC, have evolutionarily conserved cysteines to provide it with reducing equivalents. We propose that BolA uses the mono-thiol glutaredoxin as the source for these.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Izquierdo, JM.</style></author><author><style face="normal" font="default" size="100%">Majós, N.</style></author><author><style face="normal" font="default" size="100%">Bonnal, S.</style></author><author><style face="normal" font="default" size="100%">Martínez, C.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Bilbao, D.</style></author><author><style face="normal" font="default" size="100%">Valcárcel, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Regulation of Fas alternative splicing by antagonistic effects of TIA-1 and PTB on exon definition.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol. Cell</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.molcel.2005.06.01</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">475–484</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Fas exon 6 can be included or skipped to generate mRNAs encoding, respectively, a membrane bound form of the receptor that promotes apoptosis or a soluble isoform that prevents programmed cell death. We report that the apoptosis-inducing protein TIA-1 promotes U1 snRNP binding to the 5' splice site of intron 6, which in turn facilitates exon definition by enhancing U2AF binding to the 3' splice site of intron 5. The polypyrimidine tract binding protein (PTB) promotes exon skipping by binding to an exonic splicing silencer and inhibiting the association of U2AF and U2 snRNP with the upstream 3' splice site, without affecting recognition of the downstream 5' splice site by U1. Remarkably, U1 snRNP-mediated recognition of the 5' splice site is required both for efficient U2AF binding and for U2AF inhibition by PTB. We propose that TIA-1 and PTB regulate Fas splicing and possibly Fas-mediated apoptosis by targeting molecular events that lead to exon definition.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Reese, MG.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EGASP: collaboration through competition to find human genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat. Methods</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nmeth0805-57</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">575–577</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">According to the most recent estimates, the number of human genes is possibly–but not certainly–between 20,000 and 25,000. To contribute strategies to reduce this uncertainty, several groups working on computational gene prediction met recently at the Welcome Trust Sanger Institute with the goal to test and compare predictive methods of genome annotation.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of Pathogenic Mutations in Mitochondrially Encoded Human tRNAs</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">2415-2419</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Some mutations in human mitochondrial tRNAs are severely pathogenic. The available computational methods have a poor record of predicting the impact of a tRNA mutation on the phenotype and fitness. Here patterns of evolution at tRNA sites that harbor pathogenic mutations and at sites that harbor phenotypically cryptic polymorphisms were compared. Mutations that are pathogenic to humans occupy more conservative sites, are only rarely fixed in closely related species, and, when located in stem structures, often disrupt Watson-Crick pairing and display signs of compensatory evolution. These observations make it possible to classify approximately 90% of all known pathogenic mutations as deleterious together with only approximately 30% of polymorphisms. These polymorphisms segregate at frequencies that are more than two times lower than frequencies of polymorphisms classified as benign, indicating that at least approximately 30% of known polymorphisms in mitochondrial tRNAs affect fitness negatively.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">[The Analysis of Monomer Sequences in Protein and tRNA and the Manifestation of the Compensation of Pathogenic Deviations in Their Evolution]</style></title><secondary-title><style face="normal" font="default" size="100%">Biofizika</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">389-395</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The sequence analysis of proteins and mitochondrial tRNA indicated that substitutions inducing the pathogenesis in humans often occur in normal individuals of other species having no signs of pathology. The analysis of the structural stability of the protein and tRNA molecules showed that the harmful effect of pathogenic substitutions is often neutralized by other compensatory substitutions, which restore the required normal stability of the structure. A further study of this phenomenon will probably lead to new methods of treatment of genetic pathology, which would be based not on the correction of one substitution but on the correction of the stability of the molecule as an entire functional unit.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">[The Convergent Evolution of the Secondary Structure of Mitochondrial Cysteine tRNA in the Nine-banded Armadillo Dasypus Novemcinctus]</style></title><secondary-title><style face="normal" font="default" size="100%">Biofizika</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">396-403</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The case of the convergent loss of the D-hairpin in mitochondrial cysteine tRNA of the nine-banded armadillo Dasypus novemcinctus is described. This evolutionary event sheds light on the molecular structure-function relationship and on the effect of this relationship on the processes of evolution of biopolymers and macromolecules.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Taskov, K.</style></author><author><style face="normal" font="default" size="100%">Chapple, C.</style></author><author><style face="normal" font="default" size="100%">Kryukov, GV.</style></author><author><style face="normal" font="default" size="100%">Castellano, S.</style></author><author><style face="normal" font="default" size="100%">Lobanov, AV.</style></author><author><style face="normal" font="default" size="100%">Korotkov, KV.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Gladyshev, VN.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Nematode selenoproteome: the use of the selenocysteine insertion system to decode one codon in an animal genome?</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gki50</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">33</style></volume><pages><style face="normal" font="default" size="100%">2227–2238</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Selenocysteine (Sec) is co-translationally inserted into selenoproteins in response to codon UGA with the help of the selenocysteine insertion sequence (SECIS) element. The number of selenoproteins in animals varies, with humans having 25 and mice having 24 selenoproteins. To date, however, only one selenoprotein, thioredoxin reductase, has been detected in Caenorhabditis elegans, and this enzyme contains only one Sec. Here, we characterize the selenoproteomes of C.elegans and Caenorhabditis briggsae with three independent algorithms, one searching for pairs of homologous nematode SECIS elements, another searching for Cys- or Sec-containing homologs of potential nematode selenoprotein genes and the third identifying Sec-containing homologs of annotated nematode proteins. These methods suggest that thioredoxin reductase is the only Sec-containing protein in the C.elegans and C.briggsae genomes. In contrast, we identified additional selenoproteins in other nematodes. Assuming that Sec insertion mechanisms are conserved between nematodes and other eukaryotes, the data suggest that nematode selenoproteomes were reduced during evolution, and that in an extreme reduction case Sec insertion systems probably decode only a single UGA codon in C.elegans and C.briggsae genomes. In addition, all detected genes had a rare form of SECIS element containing a guanosine in place of a conserved adenosine present in most other SECIS structures, suggesting that in organisms with small selenoproteomes SECIS elements may change rapidly.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Wyss, C.</style></author><author><style face="normal" font="default" size="100%">Câmara, F.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Eyras, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparative gene finding in chicken indicates that we are closing in on the set of multi-exonic widely expressed human genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gki32</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">33</style></volume><pages><style face="normal" font="default" size="100%">1935–1939</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The recent availability of the chicken genome sequence poses the question of whether there are human protein-coding genes conserved in chicken that are currently not included in the human gene catalog. Here, we show, using comparative gene finding followed by experimental verification of exon pairs by RT-PCR, that the addition to the multi-exonic subset of this catalog could be as little as 0.2%, suggesting that we may be closing in on the human gene set. Our protocol, however, has two shortcomings: (i) the bioinformatic screening of the predicted genes, applied to filter out false positives, cannot handle intronless genes; and (ii) the experimental verification could fail to identify expression at a specific developmental time. This highlights the importance of developing methods that could provide a reliable estimate of the number of these two types of genes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Eyras, E.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Bye, JM.</style></author><author><style face="normal" font="default" size="100%">Câmara, F.</style></author><author><style face="normal" font="default" size="100%">Flicek, P.</style></author><author><style face="normal" font="default" size="100%">Huckle, EJ.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Shteynberg, DD.</style></author><author><style face="normal" font="default" size="100%">Wyss, C.</style></author><author><style face="normal" font="default" size="100%">Rogers, J.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Brent, MR.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gene finding in the chicken genome.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1186/1471-2105-6-13</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">131</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method. RESULTS: We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end. CONCLUSIONS: De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">In Search of the Limits of Evolution</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">37</style></volume><pages><style face="normal" font="default" size="100%">9-10</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jordan, I. King</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Adzhubei, Ivan A.</style></author><author><style face="normal" font="default" size="100%">Wolf, Yuri I.</style></author><author><style face="normal" font="default" size="100%">Koonin, Eugene V.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author><author><style face="normal" font="default" size="100%">Sunyaev, Shamil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Universal Trend of Amino acid gain and loss in Protein Evolution</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">433</style></volume><pages><style face="normal" font="default" size="100%">633-638</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Amino acid composition of proteins varies substantially between taxa and, thus, can evolve. For example, proteins from organisms with (G + C)-rich (or (A + T)-rich) genomes contain more (or fewer) amino acids encoded by (G + C)-rich codons. However, no universal trends in ongoing changes of amino acid frequencies have been reported. We compared sets of orthologous proteins encoded by triplets of closely related genomes from 15 taxa representing all three domains of life (Bacteria, Archaea and Eukaryota), and used phylogenies to polarize amino acid substitutions. Cys, Met, His, Ser and Phe accrue in at least 14 taxa, whereas Pro, Ala, Glu and Gly are consistently lost. The same nine amino acids are currently accrued or lost in human proteins, as shown by analysis of non-synonymous single-nucleotide polymorphisms. All amino acids with declining frequencies are thought to be among the first incorporated into the genetic code; conversely, all amino acids with increasing frequencies, except Ser, were probably recruited late. Thus, expansion of initially under-represented amino acids, which began over 3,400 million years ago, apparently continues to this day.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yampolsky, Lev Y.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Distribution of the Strength of Selection Against Amino acid Replacements in Human Proteins</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">3191-3201</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The impact of an amino acid replacement on the organism's fitness can vary from lethal to selectively neutral and even, in rare cases, beneficial. Substantial data are available on either pathogenic or acceptable replacements. However, the whole distribution of coefficients of selection against individual replacements is not known for any organism. To ascertain this distribution for human proteins, we combined data on pathogenic missense mutations, on human non-synonymous SNPs and on human-chimpanzee divergence of orthologous proteins. Fractions of amino acid replacements which reduce fitness by 10(-2), 10(-2)-10(-4), 10(-4)-10(-5) and 10(-5) are 25, 49, 14 and 12%, respectively. On average, the strength of selection against a replacement is substantially higher when chemically dissimilar amino acids are involved, and the Grantham's index of a replacement explains 35% of variance in the average logarithm of selection coefficients associated with different replacements. Still, the impact of a replacement depends on its context within the protein more than on its own nature. Reciprocal replacements are often associated with rather different selection coefficients, in particular, replacements of non-polar amino acids with polar ones are typically much more deleterious than replacements in the opposite direction. However, differences between evolutionary fluxes of reciprocal replacements are only weakly correlated with the differences between the corresponding selection coefficients.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of proteins and proteomes: a phylogenetics approach.</style></title><secondary-title><style face="normal" font="default" size="100%">Evol. Bioinform. Online</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19325853</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">51–61</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The study of evolutionary relationships among protein sequences was one of the first applications of bioinformatics. Since then, and accompanying the wealth of biological data produced by genome sequencing and other high-throughput techniques, the use of bioinformatics in general and phylogenetics in particular has been gaining ground in the study of protein and proteome evolution. Nowadays, the use of phylogenetics is instrumental not only to infer the evolutionary relationships among species and their genome sequences, but also to reconstruct ancestral states of proteins and proteomes and hence trace the paths followed by evolution. Here I survey recent progress in the elucidation of mechanisms of protein and proteome evolution in which phylogenetics has played a determinant role.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">ENCODE Project Consortium</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The ENCODE (ENCyclopedia Of DNA Elements) Project.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1126/science.110513</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5696</style></number><volume><style face="normal" font="default" size="100%">306</style></volume><pages><style face="normal" font="default" size="100%">636–640</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The ENCyclopedia Of DNA Elements (ENCODE) Project aims to identify all functional elements in the human genome sequence. The pilot phase of the Project is focused on a specified 30 megabases (approximately 1%) of the human genome sequence and is organized as an international consortium of computational and laboratory-based scientists working to develop and apply high-throughput approaches for detecting all sequence elements that confer biological function. The results of this pilot phase will guide future efforts to analyze the entire human genome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jaillon, O.</style></author><author><style face="normal" font="default" size="100%">Aury, JM.</style></author><author><style face="normal" font="default" size="100%">Brunet, F.</style></author><author><style face="normal" font="default" size="100%">Petit, JL.</style></author><author><style face="normal" font="default" size="100%">Stange-Thomann, N.</style></author><author><style face="normal" font="default" size="100%">Mauceli, E.</style></author><author><style face="normal" font="default" size="100%">Bouneau, L.</style></author><author><style face="normal" font="default" size="100%">Fischer, C.</style></author><author><style face="normal" font="default" size="100%">Ozouf-Costaz, C.</style></author><author><style face="normal" font="default" size="100%">Bernot, A.</style></author><author><style face="normal" font="default" size="100%">Nicaud, S.</style></author><author><style face="normal" font="default" size="100%">Jaffe, D.</style></author><author><style face="normal" font="default" size="100%">Fisher, S.</style></author><author><style face="normal" font="default" size="100%">Lutfalla, G.</style></author><author><style face="normal" font="default" size="100%">Dossat, C.</style></author><author><style face="normal" font="default" size="100%">Segurens, B.</style></author><author><style face="normal" font="default" size="100%">Dasilva, C.</style></author><author><style face="normal" font="default" size="100%">Salanoubat, M.</style></author><author><style face="normal" font="default" size="100%">Levy, M.</style></author><author><style face="normal" font="default" size="100%">Boudet, N.</style></author><author><style face="normal" font="default" size="100%">Castellano, S.</style></author><author><style face="normal" font="default" size="100%">Anthouard, V.</style></author><author><style face="normal" font="default" size="100%">Jubin, C.</style></author><author><style face="normal" font="default" size="100%">Castelli, V.</style></author><author><style face="normal" font="default" size="100%">Katinka, M.</style></author><author><style face="normal" font="default" size="100%">Vacherie, B.</style></author><author><style face="normal" font="default" size="100%">Biémont, C.</style></author><author><style face="normal" font="default" size="100%">Skalli, Z.</style></author><author><style face="normal" font="default" size="100%">Cattolico, L.</style></author><author><style face="normal" font="default" size="100%">Poulain, J.</style></author><author><style face="normal" font="default" size="100%">De Berardinis, V.</style></author><author><style face="normal" font="default" size="100%">Cruaud, C.</style></author><author><style face="normal" font="default" size="100%">Duprat, S.</style></author><author><style face="normal" font="default" size="100%">Brottier, P.</style></author><author><style face="normal" font="default" size="100%">Coutanceau, JP.</style></author><author><style face="normal" font="default" size="100%">Gouzy, J.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Lardier, G.</style></author><author><style face="normal" font="default" size="100%">Chapple, C.</style></author><author><style face="normal" font="default" size="100%">McKernan, KJ.</style></author><author><style face="normal" font="default" size="100%">McEwan, P.</style></author><author><style face="normal" font="default" size="100%">Bosak, S.</style></author><author><style face="normal" font="default" size="100%">Kellis, M.</style></author><author><style face="normal" font="default" size="100%">Volff, JN.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Zody, MC.</style></author><author><style face="normal" font="default" size="100%">Mesirov, J.</style></author><author><style face="normal" font="default" size="100%">Lindblad-Toh, K.</style></author><author><style face="normal" font="default" size="100%">Birren, B.</style></author><author><style face="normal" font="default" size="100%">Nusbaum, C.</style></author><author><style face="normal" font="default" size="100%">Kahn, D.</style></author><author><style face="normal" font="default" size="100%">Robinson-Rechavi, M.</style></author><author><style face="normal" font="default" size="100%">Laudet, V.</style></author><author><style face="normal" font="default" size="100%">Schachter, V.</style></author><author><style face="normal" font="default" size="100%">Quétier, F.</style></author><author><style face="normal" font="default" size="100%">Saurin, W.</style></author><author><style face="normal" font="default" size="100%">Scarpelli, C.</style></author><author><style face="normal" font="default" size="100%">Wincker, P.</style></author><author><style face="normal" font="default" size="100%">Lander, ES.</style></author><author><style face="normal" font="default" size="100%">Weissenbach, J.</style></author><author><style face="normal" font="default" size="100%">Roest Crollius, H.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome duplication in the teleost fish Tetraodon nigroviridis reveals the early vertebrate proto-karyotype.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0302</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7011</style></number><volume><style face="normal" font="default" size="100%">431</style></volume><pages><style face="normal" font="default" size="100%">946–957</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Tetraodon nigroviridis is a freshwater puffer fish with the smallest known vertebrate genome. Here, we report a draft genome sequence with long-range linkage and substantial anchoring to the 21 Tetraodon chromosomes. Genome analysis provides a greatly improved fish gene catalogue, including identifying key genes previously thought to be absent in fish. Comparison with other vertebrates and a urochordate indicates that fish proteins have diverged markedly faster than their mammalian homologues. Comparison with the human genome suggests approximately 900 previously unannotated human genes. Analysis of the Tetraodon and human genomes shows that whole-genome duplication occurred in the teleost fish lineage, subsequent to its divergence from mammals. The analysis also makes it possible to infer the basic structure of the ancestral bony vertebrate genome, which was composed of 12 chromosomes, and to reconstruct much of the evolutionary history of ancient and recent chromosome rearrangements leading to the modern human karyotype.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brent, MR.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Recent advances in gene structure prediction.</style></title><secondary-title><style face="normal" font="default" size="100%">Curr. Opin. Struct. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.sbi.2004.05.00</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">264–272</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">De novo gene predictors are programs that predict the exon-intron structures of genes using the sequences of one or more genomes as their only input. In the past two years, dual-genome de novo predictors, which exploit local rates and patterns of mutation inferred from alignments between two genomes, have led to significant improvements in accuracy. Systems that exploit more than two genomes simultaneously have only recently begun to appear and are not yet competitive on practical tasks, but offer the greatest hope for near-term improvements. Dual-genome de novo prediction for compact eukaryotic genomes such as those of Arabidopsis thaliana and Caenorhabditis elegans is already quite accurate. Although mammalian gene prediction lags behind in accuracy, it is yielding ever more useful results. Coupled with significant improvements in pseudogene detection methods, which have eliminated many false positives, we have reached the point where de novo gene predictions are being used as hypotheses to drive experimental annotation via systematic RT-PCR and sequencing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">O'Sullivan, O.</style></author><author><style face="normal" font="default" size="100%">Suhre, K.</style></author><author><style face="normal" font="default" size="100%">Abergel, C.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">3DCoffee: combining protein sequences and structures within multiple sequence alignments</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins/ chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 2</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">340</style></volume><pages><style face="normal" font="default" size="100%">385-95</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Most bioinformatics analyses require the assembly of a multiple sequence alignment. It has long been suspected that structural information can help to improve the quality of these alignments, yet the effect of combining sequences and structures has not been evaluated systematically. We developed 3DCoffee, a novel method for combining protein sequences and structures in order to generate high-quality multiple sequence alignments. 3DCoffee is based on TCoffee version 2.00, and uses a mixture of pairwise sequence alignments and pairwise structure comparison methods to generate multiple sequence alignments. We benchmarked 3DCoffee using a subset of HOMSTRAD, the collection of reference structural alignments. We found that combining TCoffee with the threading program Fugue makes it possible to improve the accuracy of our HOMSTRAD dataset by four percentage points when using one structure only per dataset. Using two structures yields an improvement of ten percentage points. The measures carried out on HOM39, a HOMSTRAD subset composed of distantly related sequences, show a linear correlation between multiple sequence alignment accuracy and the ratio of number of provided structure to total number of sequences. Our results suggest that in the case of distantly related sequences, a single structure may not be enough for computing an accurate multiple sequence alignment.</style></abstract><accession-num><style face="normal" font="default" size="100%">15201059</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Poirot, O.</style></author><author><style face="normal" font="default" size="100%">Suhre, K.</style></author><author><style face="normal" font="default" size="100%">Abergel, C.</style></author><author><style face="normal" font="default" size="100%">O'Toole, E.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">3DCoffee@igs: a web server for combining sequences and structures into a multiple sequence alignment</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">W37-40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents 3DCoffee@igs, a web-based tool dedicated to the computation of high-quality multiple sequence alignments (MSAs). 3D-Coffee makes it possible to mix protein sequences and structures in order to increase the accuracy of the alignments. Structures can be either provided as PDB identifiers or directly uploaded into the server. Given a set of sequences and structures, pairs of structures are aligned with SAP while sequence-structure pairs are aligned with Fugue. The resulting collection of pairwise alignments is then combined into an MSA with the T-Coffee algorithm. The server and its documentation are available from http://igs-server.cnrs-mrs.fr/Tcoffee/.</style></abstract><accession-num><style face="normal" font="default" size="100%">15215345</style></accession-num><notes><style face="normal" font="default" size="100%">Journal Article</style></notes><auth-address><style face="normal" font="default" size="100%">Information Genomique et Structurale UPR2589-CNRS, CNRS, 31, Chemin Joseph Aiguier, 13 402 Marseille Cedex 20, France.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Claude, J. B.</style></author><author><style face="normal" font="default" size="100%">Suhre, K.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Claverie, J. M.</style></author><author><style face="normal" font="default" size="100%">Abergel, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CaspR: a web server for automated molecular replacement using homology modelling</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Escherichia coli Proteins/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Structural Homology, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">W606-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Molecular replacement (MR) is the method of choice for X-ray crystallography structure determination when structural homologues are available in the Protein Data Bank (PDB). Although the success rate of MR decreases sharply when the sequence similarity between template and target proteins drops below 35% identical residues, it has been found that screening for MR solutions with a large number of different homology models may still produce a suitable solution where the original template failed. Here we present the web tool CaspR, implementing such a strategy in an automated manner. On input of experimental diffraction data, of the corresponding target sequence and of one or several potential templates, CaspR executes an optimized molecular replacement procedure using a combination of well-established stand-alone software tools. The protocol of model building and screening begins with the generation of multiple structure-sequence alignments produced with T-COFFEE, followed by homology model building using MODELLER, molecular replacement with AMoRe and model refinement based on CNS. As a result, CaspR provides a progress report in the form of hierarchically organized summary sheets that describe the different stages of the computation with an increasing level of detail. For the 10 highest-scoring potential solutions, pre-refined structures are made available for download in PDB format. Results already obtained with CaspR and reported on the web server suggest that such a strategy significantly increases the fraction of protein structures which may be solved by MR. Moreover, even in situations where standard MR yields a solution, pre-refined homology models produced by CaspR significantly reduce the time-consuming refinement process. We expect this automated procedure to have a significant impact on the throughput of large-scale structural genomics projects. CaspR is freely available at http://igs-server.cnrs-mrs.fr/Caspr/.</style></abstract><accession-num><style face="normal" font="default" size="100%">15215460</style></accession-num><notes><style face="normal" font="default" size="100%">Journal Article</style></notes><auth-address><style face="normal" font="default" size="100%">Information Genomique &amp; Structurale (UPR CNRS 2589), Institut de Biologie Structurale et Microbiologie, 31, chemin Joseph Aiguier, 13402 Marseille Cedex 20, France.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castresana, J.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Albà, MM.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Clustering of genes coding for DNA binding proteins in a region of atypical evolution of the human genome.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Evol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s00239-004-2605-</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">59</style></volume><pages><style face="normal" font="default" size="100%">72–79</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Comparison of the human and mouse genomes has revealed that significant variations in evolutionary rates exist among genomic regions and that a large part of this variation is interchromosomal. We confirm in this work, using a large collection of introns, that human chromosome 19 is the one that shows the highest divergence with respect to mouse. To search for other differences among chromosomes, we examine the distribution of gene functions in human and mouse chromosomes using the Gene Ontology definitions. We found by correspondence analysis that among the strongest clusterings of gene functions in human chromosomes is a group of genes coding for DNA binding proteins in chromosome 19. Interestingly, chromosome 19 also has a very high GC content, a feature that has been proposed to promote an opening of the chromatin, thereby facilitating binding of proteins to the DNA helix. In the mouse genome, however, a similar aggregation of genes coding for DNA binding proteins and high GC content cannot be found. This suggests that the distribution of genes coding for DNA binding proteins and the variations of the chromatin accessibility to these proteins are different in the human and mouse genomes. It is likely that the overall high synonymous and intron rates in chromosome 19 are a by-product of the high GC content of this chromosome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Cavalli, A.</style></author><author><style face="normal" font="default" size="100%">Pellarin, R.</style></author><author><style face="normal" font="default" size="100%">Caflisch, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The role of aromaticity, exposed surface, and dipole moment in determining protein aggregation rates.</style></title><secondary-title><style face="normal" font="default" size="100%">Protein Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1110/ps.04663504</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">1939–1941</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The mechanisms by which peptides and proteins form ordered aggregates are not well understood. Here we focus on the physicochemical properties of amino acids that favor ordered aggregation and suggest a parameter-free model that is able to predict the change of aggregation rates over a large set of natural sequences. Furthermore, the results of the parameter-free model correlate well with the aggregation propensities of a set of peptides designed by computer simulations.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hermoso, A.</style></author><author><style face="normal" font="default" size="100%">Aguilar, D.</style></author><author><style face="normal" font="default" size="100%">Aviles, FX.</style></author><author><style face="normal" font="default" size="100%">Querol, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">TrSDB: a proteome database of transcription factors.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkh101</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">D171–D173</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">TrSDB-TranScout Database-(http://ibb.uab.es/trsdb) is a proteome database of eukaryotic transcription factors based upon predicted motifs by TranScout and data sources such as InterPro and Gene Ontology Annotation. Nine eukaryotic proteomes are included in the current version. Extensive and diverse information for each database entry, different analyses considering TranScout classification and similarity relationships are offered for research on transcription factors or gene expression.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Espadaler, J.</style></author><author><style face="normal" font="default" size="100%">Fernandez-Fuentes, N.</style></author><author><style face="normal" font="default" size="100%">Hermoso, A.</style></author><author><style face="normal" font="default" size="100%">Querol, E.</style></author><author><style face="normal" font="default" size="100%">Aviles, FX.</style></author><author><style face="normal" font="default" size="100%">Sternberg, MJ.</style></author><author><style face="normal" font="default" size="100%">Oliva, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ArchDB: automated protein loop classification as a tool for structural genomics.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1093/nar/gkh002</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">D185–D188</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The annotation of protein function has become a crucial problem with the advent of sequence and structural genomics initiatives. A large body of evidence suggests that protein structural information is frequently encoded in local sequences, and that folds are mainly made up of a number of simple local units of super-secondary structural motifs, consisting of a few secondary structures and their connecting loops. Moreover, protein loops play an important role in protein function. Here we present ArchDB, a classification database of structural motifs, consisting of one loop plus its bracing secondary structures. ArchDB currently contains 12,665 super-secondary elements classified into 1496 motif subclasses. The database provides an easy way to retrieve functional information from protein structures sharing a common motif, to search motifs found in a given SCOP family, superfamily or fold, or to search by keywords on proteins with classified loops. The ArchDB database of loops is located at http://sbi.imim.es/archdb.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Suhre, K.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computing multiple sequence/structure alignments with the T-coffee package</style></title><secondary-title><style face="normal" font="default" size="100%">Curr Protoc Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Programming Languages</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">Chapter 3</style></volume><pages><style face="normal" font="default" size="100%">Unit3 8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The FASTA package provides a comprehensive set of similarity searching programs, similar to those provided by the BLAST package, and some additional programs for searching with short peptides and oligonucleotides that are not provided by BLAST. The FASTA programs work with a wide variety of database formats, including mySQL sequence databases. FASTA provides very accurate statistical significance estimates, and is more sensitive than BLASTN when comparing DNA sequences. These protocols describe how to use the FASTA programs to characterize protein and DNA sequences, using protein:protein, protein:DNA, and DNA:DNA comparisons.</style></abstract><accession-num><style face="normal" font="default" size="100%">18428722</style></accession-num><notes><style face="normal" font="default" size="100%">Journal Article</style></notes><auth-address><style face="normal" font="default" size="100%">Swiss Institute of Bioinformatics, Epalinges, Switzerland.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vella, F.</style></author><author><style face="normal" font="default" size="100%">Mietchen, D.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Perceptions about postdocs</style></title><secondary-title><style face="normal" font="default" size="100%">EMBO Rep.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">1104</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">International Chicken Genome Sequencing Consortium</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0315</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7018</style></number><volume><style face="normal" font="default" size="100%">432</style></volume><pages><style face="normal" font="default" size="100%">695–716</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present here a draft genome sequence of the red jungle fowl, Gallus gallus. Because the chicken is a modern descendant of the dinosaurs and the first non-mammalian amniote to have its genome sequenced, the draft sequence of its genome–composed of approximately one billion base pairs of sequence and an estimated 20,000-23,000 genes–provides a new perspective on vertebrate genome evolution, while also improving the annotation of mammalian genomes. For example, the evolutionary distance between chicken and human provides high specificity in detecting functional elements, both non-coding and coding. Notably, many conserved non-coding sequences are far from genes and cannot be assigned to defined functional classes. In coding regions the evolutionary dynamics of protein domains and orthologous groups illustrate processes that distinguish the lineages leading to birds and mammals. The distinctive properties of avian microchromosomes, together with the inferred patterns of conserved synteny, provide additional insights into vertebrate chromosome architecture.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vella, F.</style></author><author><style face="normal" font="default" size="100%">Mietchen, D.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Eurodoc Council</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Perceptions about postdocs.</style></title><secondary-title><style face="normal" font="default" size="100%">EMBO Rep.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/sj.embor.7400304</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">1104</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Shaping the mitochondrial proteome.</style></title><secondary-title><style face="normal" font="default" size="100%">Biochim. Biophys. Acta</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.bbabio.2004.07.011</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2-3</style></number><volume><style face="normal" font="default" size="100%">1659</style></volume><pages><style face="normal" font="default" size="100%">212–220</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Mitochondria are eukaryotic organelles that originated from a single bacterial endosymbiosis some 2 billion years ago. The transition from the ancestral endosymbiont to the modern mitochondrion has been accompanied by major changes in its protein content, the so-called proteome. These changes included complete loss of some bacterial pathways, amelioration of others and gain of completely new complexes of eukaryotic origin such as the ATP/ADP translocase and most of the mitochondrial protein import machinery. This renewal of proteins has been so extensive that only 14-16% of modern mitochondrial proteome has an origin that can be traced back to the bacterial endosymbiont. The rest consists of proteins of diverse origin that were eventually recruited to function in the organelle. This shaping of the proteome content reflects the transformation of mitochondria into a highly specialized organelle that, besides ATP production, comprises a variety of functions within the eukaryotic metabolism. Here we review recent advances in the fields of comparative genomics and proteomics that are throwing light on the origin and evolution of the mitochondrial proteome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castelo, R.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Splice site identification by idlBNs.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/20/suppl_1/i6</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">20 Suppl 1</style></volume><pages><style face="normal" font="default" size="100%">i69–i76</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: Computational identification of functional sites in nucleotide sequences is at the core of many algorithms for the analysis of genomic data. This identification is based on the statistical parameters estimated from a training set. Often, because of the huge number of parameters, it is difficult to obtain consistent estimators. To simplify the estimation problem, one imposes independent assumptions between the nucleotides along the site. However, this can potentially limit the minimum value of the estimation error. RESULTS: In this paper, we introduce a novel method in the context of identifying functional sites, that finds a reasonable set of independence assumptions supported by the data, among the nucleotides, and uses it to perform the identification of the sites by their likelihood ratio. More importantly, in many practical situations it is capable of improving its performance as the training sample size increases. We apply the method to the identification of splice sites, and further evaluate its effect within the context of exon and gene prediction.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fernandez-Fuentes, N.</style></author><author><style face="normal" font="default" size="100%">Hermoso, A.</style></author><author><style face="normal" font="default" size="100%">Espadaler, J.</style></author><author><style face="normal" font="default" size="100%">Querol, E.</style></author><author><style face="normal" font="default" size="100%">Aviles, FX.</style></author><author><style face="normal" font="default" size="100%">Oliva, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Classification of common functional loops of kinase super-families.</style></title><secondary-title><style face="normal" font="default" size="100%">Proteins</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/prot.20136</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">56</style></volume><pages><style face="normal" font="default" size="100%">539–555</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A structural classification of loops has been obtained from a set of 141 protein structures classified as kinases. A total of 1813 loops was classified into 133 subclasses (9 betabeta(links), 15 betabeta(hairpins), 31 alpha-alpha, 46 alpha-beta and 32 beta-alpha). Functional information and specific features relating subclasses and function were included in the classification. Functional loops such as the P-loop (shared by different folds) or the Gly-rich-loop, among others, were classified into structural motifs. As a result, a common mechanism of catalysis and substrate binding was proved for most kinases. Additionally, the multiple-alignment of loop sequences made within each subclass was shown to be useful for comparative modeling of kinase loops. The classification is summarized in a kinase loop database located at http://sbi.imim.es/archki.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gibbs, RA.</style></author><author><style face="normal" font="default" size="100%">Weinstock, GM.</style></author><author><style face="normal" font="default" size="100%">Metzker, ML.</style></author><author><style face="normal" font="default" size="100%">Muzny, DM.</style></author><author><style face="normal" font="default" size="100%">Sodergren, EJ.</style></author><author><style face="normal" font="default" size="100%">Scherer, S.</style></author><author><style face="normal" font="default" size="100%">Scott, G.</style></author><author><style face="normal" font="default" size="100%">Steffen, D.</style></author><author><style face="normal" font="default" size="100%">Worley, KC.</style></author><author><style face="normal" font="default" size="100%">Burch, PE.</style></author><author><style face="normal" font="default" size="100%">Okwuonu, G.</style></author><author><style face="normal" font="default" size="100%">Hines, S.</style></author><author><style face="normal" font="default" size="100%">Lewis, L.</style></author><author><style face="normal" font="default" size="100%">DeRamo, C.</style></author><author><style face="normal" font="default" size="100%">Delgado, O.</style></author><author><style face="normal" font="default" size="100%">Dugan-Rocha, S.</style></author><author><style face="normal" font="default" size="100%">Miner, G.</style></author><author><style face="normal" font="default" size="100%">Morgan, M.</style></author><author><style face="normal" font="default" size="100%">Hawes, A.</style></author><author><style face="normal" font="default" size="100%">Gill, R.</style></author><author><style face="normal" font="default" size="100%">Celera</style></author><author><style face="normal" font="default" size="100%">Holt, RA.</style></author><author><style face="normal" font="default" size="100%">Adams, MD.</style></author><author><style face="normal" font="default" size="100%">Amanatides, PG.</style></author><author><style face="normal" font="default" size="100%">Baden-Tillson, H.</style></author><author><style face="normal" font="default" size="100%">Barnstead, M.</style></author><author><style face="normal" font="default" size="100%">Chin, S.</style></author><author><style face="normal" font="default" size="100%">Evans, CA.</style></author><author><style face="normal" font="default" size="100%">Ferriera, S.</style></author><author><style face="normal" font="default" size="100%">Fosler, C.</style></author><author><style face="normal" font="default" size="100%">Glodek, A.</style></author><author><style face="normal" font="default" size="100%">Gu, Z.</style></author><author><style face="normal" font="default" size="100%">Jennings, D.</style></author><author><style face="normal" font="default" size="100%">Kraft, CL.</style></author><author><style face="normal" font="default" size="100%">Nguyen, T.</style></author><author><style face="normal" font="default" size="100%">Pfannkoch, CM.</style></author><author><style face="normal" font="default" size="100%">Sitter, C.</style></author><author><style face="normal" font="default" size="100%">Sutton, GG.</style></author><author><style face="normal" font="default" size="100%">Venter, JC.</style></author><author><style face="normal" font="default" size="100%">Woodage, T.</style></author><author><style face="normal" font="default" size="100%">Smith, D.</style></author><author><style face="normal" font="default" size="100%">Lee, HM.</style></author><author><style face="normal" font="default" size="100%">Gustafson, E.</style></author><author><style face="normal" font="default" size="100%">Cahill, P.</style></author><author><style face="normal" font="default" size="100%">Kana, A.</style></author><author><style face="normal" font="default" size="100%">Doucette-Stamm, L.</style></author><author><style face="normal" font="default" size="100%">Weinstock, K.</style></author><author><style face="normal" font="default" size="100%">Fechtel, K.</style></author><author><style face="normal" font="default" size="100%">Weiss, RB.</style></author><author><style face="normal" font="default" size="100%">Dunn, DM.</style></author><author><style face="normal" font="default" size="100%">Green, ED.</style></author><author><style face="normal" font="default" size="100%">Blakesley, RW.</style></author><author><style face="normal" font="default" size="100%">Bouffard, GG.</style></author><author><style face="normal" font="default" size="100%">de Jong, PJ.</style></author><author><style face="normal" font="default" size="100%">Osoegawa, K.</style></author><author><style face="normal" font="default" size="100%">Zhu, B.</style></author><author><style face="normal" font="default" size="100%">Marra, M.</style></author><author><style face="normal" font="default" size="100%">Schein, J.</style></author><author><style face="normal" font="default" size="100%">Bosdet, I.</style></author><author><style face="normal" font="default" size="100%">Fjell, C.</style></author><author><style face="normal" font="default" size="100%">Jones, S.</style></author><author><style face="normal" font="default" size="100%">Krzywinski, M.</style></author><author><style face="normal" font="default" size="100%">Mathewson, C.</style></author><author><style face="normal" font="default" size="100%">Siddiqui, A.</style></author><author><style face="normal" font="default" size="100%">Wye, N.</style></author><author><style face="normal" font="default" size="100%">McPherson, J.</style></author><author><style face="normal" font="default" size="100%">Zhao, S.</style></author><author><style face="normal" font="default" size="100%">Fraser, CM.</style></author><author><style face="normal" font="default" size="100%">Shetty, J.</style></author><author><style face="normal" font="default" size="100%">Shatsman, S.</style></author><author><style face="normal" font="default" size="100%">Geer, K.</style></author><author><style face="normal" font="default" size="100%">Chen, Y.</style></author><author><style face="normal" font="default" size="100%">Abramzon, S.</style></author><author><style face="normal" font="default" size="100%">Nierman, WC.</style></author><author><style face="normal" font="default" size="100%">Havlak, PH.</style></author><author><style face="normal" font="default" size="100%">Chen, R.</style></author><author><style face="normal" font="default" size="100%">Durbin, KJ.</style></author><author><style face="normal" font="default" size="100%">Egan, A.</style></author><author><style face="normal" font="default" size="100%">Ren, Y.</style></author><author><style face="normal" font="default" size="100%">Song, XZ.</style></author><author><style face="normal" font="default" size="100%">Li, B.</style></author><author><style face="normal" font="default" size="100%">Liu, Y.</style></author><author><style face="normal" font="default" size="100%">Qin, X.</style></author><author><style face="normal" font="default" size="100%">Cawley, S.</style></author><author><style face="normal" font="default" size="100%">Worley, KC.</style></author><author><style face="normal" font="default" size="100%">Cooney, AJ.</style></author><author><style face="normal" font="default" size="100%">D'Souza, LM.</style></author><author><style face="normal" font="default" size="100%">Martin, K.</style></author><author><style face="normal" font="default" size="100%">Wu, JQ.</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Garay, ML.</style></author><author><style face="normal" font="default" size="100%">Jackson, AR.</style></author><author><style face="normal" font="default" size="100%">Kalafus, KJ.</style></author><author><style face="normal" font="default" size="100%">McLeod, MP.</style></author><author><style face="normal" font="default" size="100%">Milosavljevic, A.</style></author><author><style face="normal" font="default" size="100%">Virk, D.</style></author><author><style face="normal" font="default" size="100%">Volkov, A.</style></author><author><style face="normal" font="default" size="100%">Wheeler, DA.</style></author><author><style face="normal" font="default" size="100%">Zhang, Z.</style></author><author><style face="normal" font="default" size="100%">Bailey, JA.</style></author><author><style face="normal" font="default" size="100%">Eichler, EE.</style></author><author><style face="normal" font="default" size="100%">Tuzun, E.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Mongin, E.</style></author><author><style face="normal" font="default" size="100%">Ureta-Vidal, A.</style></author><author><style face="normal" font="default" size="100%">Woodwark, C.</style></author><author><style face="normal" font="default" size="100%">Zdobnov, E.</style></author><author><style face="normal" font="default" size="100%">Bork, P.</style></author><author><style face="normal" font="default" size="100%">Suyama, M.</style></author><author><style face="normal" font="default" size="100%">Torrents, D.</style></author><author><style face="normal" font="default" size="100%">Alexandersson, M.</style></author><author><style face="normal" font="default" size="100%">Trask, BJ.</style></author><author><style face="normal" font="default" size="100%">Young, JM.</style></author><author><style face="normal" font="default" size="100%">Huang, H.</style></author><author><style face="normal" font="default" size="100%">Wang, H.</style></author><author><style face="normal" font="default" size="100%">Xing, H.</style></author><author><style face="normal" font="default" size="100%">Daniels, S.</style></author><author><style face="normal" font="default" size="100%">Gietzen, D.</style></author><author><style face="normal" font="default" size="100%">Schmidt, J.</style></author><author><style face="normal" font="default" size="100%">Stevens, K.</style></author><author><style face="normal" font="default" size="100%">Vitt, U.</style></author><author><style face="normal" font="default" size="100%">Wingrove, J.</style></author><author><style face="normal" font="default" size="100%">Câmara, F.</style></author><author><style face="normal" font="default" size="100%">Mar Albà, M.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Smit, A.</style></author><author><style face="normal" font="default" size="100%">Dubchak, I.</style></author><author><style face="normal" font="default" size="100%">Rubin, EM.</style></author><author><style face="normal" font="default" size="100%">Couronne, O.</style></author><author><style face="normal" font="default" size="100%">Poliakov, A.</style></author><author><style face="normal" font="default" size="100%">Hübner, N.</style></author><author><style face="normal" font="default" size="100%">Ganten, D.</style></author><author><style face="normal" font="default" size="100%">Goesele, C.</style></author><author><style face="normal" font="default" size="100%">Hummel, O.</style></author><author><style face="normal" font="default" size="100%">Kreitler, T.</style></author><author><style face="normal" font="default" size="100%">Lee, YA.</style></author><author><style face="normal" font="default" size="100%">Monti, J.</style></author><author><style face="normal" font="default" size="100%">Schulz, H.</style></author><author><style face="normal" font="default" size="100%">Zimdahl, H.</style></author><author><style face="normal" font="default" size="100%">Himmelbauer, H.</style></author><author><style face="normal" font="default" size="100%">Lehrach, H.</style></author><author><style face="normal" font="default" size="100%">Jacob, HJ.</style></author><author><style face="normal" font="default" size="100%">Bromberg, S.</style></author><author><style face="normal" font="default" size="100%">Gullings-Handley, J.</style></author><author><style face="normal" font="default" size="100%">Jensen-Seaman, MI.</style></author><author><style face="normal" font="default" size="100%">Kwitek, AE.</style></author><author><style face="normal" font="default" size="100%">Lazar, J.</style></author><author><style face="normal" font="default" size="100%">Pasko, D.</style></author><author><style face="normal" font="default" size="100%">Tonellato, PJ.</style></author><author><style face="normal" font="default" size="100%">Twigger, S.</style></author><author><style face="normal" font="default" size="100%">Ponting, CP.</style></author><author><style face="normal" font="default" size="100%">Duarte, JM.</style></author><author><style face="normal" font="default" size="100%">Rice, S.</style></author><author><style face="normal" font="default" size="100%">Goodstadt, L.</style></author><author><style face="normal" font="default" size="100%">Beatson, SA.</style></author><author><style face="normal" font="default" size="100%">Emes, RD.</style></author><author><style face="normal" font="default" size="100%">Winter, EE.</style></author><author><style face="normal" font="default" size="100%">Webber, C.</style></author><author><style face="normal" font="default" size="100%">Brandt, P.</style></author><author><style face="normal" font="default" size="100%">Nyakatura, G.</style></author><author><style face="normal" font="default" size="100%">Adetobi, M.</style></author><author><style face="normal" font="default" size="100%">Chiaromonte, F.</style></author><author><style face="normal" font="default" size="100%">Elnitski, L.</style></author><author><style face="normal" font="default" size="100%">Eswara, P.</style></author><author><style face="normal" font="default" size="100%">Hardison, RC.</style></author><author><style face="normal" font="default" size="100%">Hou, M.</style></author><author><style face="normal" font="default" size="100%">Kolbe, D.</style></author><author><style face="normal" font="default" size="100%">Makova, K.</style></author><author><style face="normal" font="default" size="100%">Miller, W.</style></author><author><style face="normal" font="default" size="100%">Nekrutenko, A.</style></author><author><style face="normal" font="default" size="100%">Riemer, C.</style></author><author><style face="normal" font="default" size="100%">Schwartz, S.</style></author><author><style face="normal" font="default" size="100%">Taylor, J.</style></author><author><style face="normal" font="default" size="100%">Yang, S.</style></author><author><style face="normal" font="default" size="100%">Zhang, Y.</style></author><author><style face="normal" font="default" size="100%">Lindpaintner, K.</style></author><author><style face="normal" font="default" size="100%">Andrews, TD.</style></author><author><style face="normal" font="default" size="100%">Caccamo, M.</style></author><author><style face="normal" font="default" size="100%">Clamp, M.</style></author><author><style face="normal" font="default" size="100%">Clarke, L.</style></author><author><style face="normal" font="default" size="100%">Curwen, V.</style></author><author><style face="normal" font="default" size="100%">Durbin, R.</style></author><author><style face="normal" font="default" size="100%">Eyras, E.</style></author><author><style face="normal" font="default" size="100%">Searle, SM.</style></author><author><style face="normal" font="default" size="100%">Cooper, GM.</style></author><author><style face="normal" font="default" size="100%">Batzoglou, S.</style></author><author><style face="normal" font="default" size="100%">Brudno, M.</style></author><author><style face="normal" font="default" size="100%">Sidow, A.</style></author><author><style face="normal" font="default" size="100%">Stone, EA.</style></author><author><style face="normal" font="default" size="100%">Venter, JC.</style></author><author><style face="normal" font="default" size="100%">Payseur, BA.</style></author><author><style face="normal" font="default" size="100%">Bourque, G.</style></author><author><style face="normal" font="default" size="100%">López-Otín, C.</style></author><author><style face="normal" font="default" size="100%">Puente, XS.</style></author><author><style face="normal" font="default" size="100%">Chakrabarti, K.</style></author><author><style face="normal" font="default" size="100%">Chatterji, S.</style></author><author><style face="normal" font="default" size="100%">Dewey, C.</style></author><author><style face="normal" font="default" size="100%">Pachter, L.</style></author><author><style face="normal" font="default" size="100%">Bray, N.</style></author><author><style face="normal" font="default" size="100%">Yap, VB.</style></author><author><style face="normal" font="default" size="100%">Caspi, A.</style></author><author><style face="normal" font="default" size="100%">Tesler, G.</style></author><author><style face="normal" font="default" size="100%">Pevzner, PA.</style></author><author><style face="normal" font="default" size="100%">Haussler, D.</style></author><author><style face="normal" font="default" size="100%">Roskin, KM.</style></author><author><style face="normal" font="default" size="100%">Baertsch, R.</style></author><author><style face="normal" font="default" size="100%">Clawson, H.</style></author><author><style face="normal" font="default" size="100%">Furey, TS.</style></author><author><style face="normal" font="default" size="100%">Hinrichs, AS.</style></author><author><style face="normal" font="default" size="100%">Karolchik, D.</style></author><author><style face="normal" font="default" size="100%">Kent, WJ.</style></author><author><style face="normal" font="default" size="100%">Rosenbloom, KR.</style></author><author><style face="normal" font="default" size="100%">Trumbower, H.</style></author><author><style face="normal" font="default" size="100%">Weirauch, M.</style></author><author><style face="normal" font="default" size="100%">Cooper, DN.</style></author><author><style face="normal" font="default" size="100%">Stenson, PD.</style></author><author><style face="normal" font="default" size="100%">Ma, B.</style></author><author><style face="normal" font="default" size="100%">Brent, M.</style></author><author><style face="normal" font="default" size="100%">Arumugam, M.</style></author><author><style face="normal" font="default" size="100%">Shteynberg, D.</style></author><author><style face="normal" font="default" size="100%">Copley, RR.</style></author><author><style face="normal" font="default" size="100%">Taylor, MS.</style></author><author><style face="normal" font="default" size="100%">Riethman, H.</style></author><author><style face="normal" font="default" size="100%">Mudunuri, U.</style></author><author><style face="normal" font="default" size="100%">Peterson, J.</style></author><author><style face="normal" font="default" size="100%">Guyer, M.</style></author><author><style face="normal" font="default" size="100%">Felsenfeld, A.</style></author><author><style face="normal" font="default" size="100%">Old, S.</style></author><author><style face="normal" font="default" size="100%">Mockrin, S.</style></author><author><style face="normal" font="default" size="100%">Collins, F.</style></author><author><style face="normal" font="default" size="100%">Rat Genome Sequencing Project Consortium</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome sequence of the Brown Norway rat yields insights into mammalian evolution.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0242</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6982</style></number><volume><style face="normal" font="default" size="100%">428</style></volume><pages><style face="normal" font="default" size="100%">493–521</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The laboratory rat (Rattus norvegicus) is an indispensable tool in experimental medicine and drug development, having made inestimable contributions to human health. We report here the genome sequence of the Brown Norway (BN) rat strain. The sequence represents a high-quality 'draft' covering over 90% of the genome. The BN rat sequence is the third complete mammalian genome to be deciphered, and three-way comparisons with the human and mouse genomes resolve details of mammalian evolution. This first comprehensive analysis includes genes and proteins and their relation to human disease, repeated sequences, comparative genome-wide studies of mammalian orthologous chromosomal regions and rearrangement breakpoints, reconstruction of ancestral karyotypes and the events leading to existing species, rates of variation, and lineage-specific and lineage-independent evolutionary events such as expansion of gene families, orthology relations and protein evolution.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of protein function and pathways in the genome era.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell. Mol. Life Sci.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s00018-003-3387-y</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7-8</style></number><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">930–944</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The growing number of completely sequenced genomes adds new dimensions to the use of sequence analysis to predict protein function. Compared with the classical knowledge transfer from one protein to a similar sequence (homology-based function prediction), knowledge about the corresponding genes in other genomes (orthology-based function prediction) provides more specific information about the protein's function, while the analysis of the sequence in its genomic context (context-based function prediction) provides information about its functional context. Whereas homology-based methods predict the molecular function of a protein, genomic context methods predict the biological process in which it plays a role. These complementary approaches can be combined to elucidate complete functional networks and biochemical pathways from the genome sequence of an organism. Here we review recent advances in the field of genomic-context based methods of protein function prediction. Techniques are highlighted with examples, including an analysis that combines information from genomic-context with homology to predict a role of the RNase L inhibitor in the maturation of ribosomal RNA.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Feng, J.</style></author><author><style face="normal" font="default" size="100%">Tartaglia, GG.</style></author><author><style face="normal" font="default" size="100%">Tirozzi, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A note on minimum variance theory and beyond.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Phys. A Mat.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://iopscience.iop.org/0305-4470/37/17/001</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">37</style></number><pages><style face="normal" font="default" size="100%">4685-4700</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castillo-Davis, Cristian I.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Hartl, Daniel L.</style></author><author><style face="normal" font="default" size="100%">Kulathinal, Rob J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Functional Genomic Distribution of Protein Divergence in two Animal Phyla: Coevolution, Genomic Conflict, and Constraint</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">802-811</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We compare the functional spectrum of protein evolution in two separate animal lineages with respect to two hypotheses: (1) rates of divergence are distributed similarly among functional classes within both lineages, indicating that selective pressure on the proteome is largely independent of organismic-level biological requirements; and (2) rates of divergence are distributed differently among functional classes within each lineage, indicating species-specific selective regimes impact genome-wide substitutional patterns. Integrating comparative genome sequence with data from tissue-specific expressed-sequence-tag (EST) libraries and detailed database annotations, we find a functional genomic signature of rapid evolution and selective constraint shared between mammalian and nematode lineages despite their extensive morphological and ecological differences and distant common ancestry. In both phyla, we find evidence of accelerated evolution among components of molecular systems involved in coevolutionary change. In mammals, lineage-specific fast evolving genes include those involved in reproduction, immunity, and possibly, maternal-fetal conflict. Likelihood ratio tests provide evidence for positive selection in these rapidly evolving functional categories in mammals. In contrast, slowly evolving genes, in terms of amino acid or insertion/deletion (indel) change, in both phyla are involved in core molecular processes such as transcription, translation, and protein transport. Thus, strong purifying selection appears to act on the same core cellular processes in both mammalian and nematode lineages, whereas positive and/or relaxed selection acts on different biological processes in each lineage.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kern, Andrew D.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mechanisms and Convergence of Compensatory Evolution in Mammalian Mitochondrial tRNAs</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">1207-1212</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The function of protein and RNA molecules depends on complex epistatic interactions between sites. Therefore, the deleterious effect of a mutation can be suppressed by a compensatory second-site substitution. In relating a list of 86 pathogenic mutations in human tRNAs encoded by mitochondrial genes to the sequences of their mammalian orthologs, we noted that 52 pathogenic mutations were present in normal tRNAs of one or several nonhuman mammals. We found at least five mechanisms of compensation for 32 pathogenic mutations that destroyed a Watson-Crick pair in one of the four tRNA stems: restoration of the affected Watson-Crick interaction (25 cases), strengthening of another pair (4 cases), creation of a new pair (8 cases), changes of multiple interactions in the affected stem (11 cases) and changes involving the interaction between the loop and stem structures (3 cases). A pathogenic mutation and its compensating substitution are fixed in a lineage in rapid succession, and often a compensatory interaction evolves convergently in different clades. At least 10%, and perhaps as many as 50%, of all nucleotide substitutions in evolving mammalian tRNAs participate in such interactions, indicating that the evolution of tRNAs proceeds along highly epistatic fitness ridges.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Ogurtsov, Aleksey Y.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bioinformatical Assay of Human gene Morbidity</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">1731-1737</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Only a fraction of eukaryotic genes affect the phenotype drastically. We compared 18 parameters in 1273 human morbid genes, known to cause diseases, and in the remaining 16 580 unambiguous human genes. Morbid genes evolve more slowly, have wider phylogenetic distributions, are more similar to essential genes of Drosophila melanogaster, code for longer proteins containing more alanine and glycine and less histidine, lysine and methionine, possess larger numbers of longer introns with more accurate splicing signals and have higher and broader expressions. These differences make it possible to classify as non-morbid 34% of human genes with unknown morbidity, when only 5% of known morbid genes are incorrectly classified as non-morbid. This classification can help to identify disease-causing genes among multiple candidates.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Panchenko, Anna R.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Bryant, Stephen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of Functional Sites by Analysis of Sequence and Structure Conservation</style></title><secondary-title><style face="normal" font="default" size="100%">Protein Sci</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">884-892</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a method for prediction of functional sites in a set of aligned protein sequences. The method selects sites which are both well conserved and clustered together in space, as inferred from the 3D structures of proteins included in the alignment. We tested the method using 86 alignments from the NCBI CDD database, where the sites of experimentally determined ligand and/or macromolecular interactions are annotated. In agreement with earlier investigations, we found that functional site predictions are most successful when overall background sequence conservation is low, such that sites under evolutionary constraint become apparent. In addition, we found that averaging of conservation values across spatially clustered sites improves predictions under certain conditions: that is, when overall conservation is relatively high and when the site in question involves a large macromolecular binding interface. Under these conditions it is better to look for clusters of conserved sites than to look for particular conserved sites.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Koonin, Eugene V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Common Framework for Understanding the Origin of Genetic Dominance and Evolutionary Fates of gene Duplications</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">287-290</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bazykin, Georgii A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Ogurtsov, Aleksey Y.</style></author><author><style face="normal" font="default" size="100%">Sunyaev, Shamil</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Positive Selection at Sites of Multiple Amino acid Replacements Since Rat-mouse Divergence</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><volume><style face="normal" font="default" size="100%">429</style></volume><pages><style face="normal" font="default" size="100%">558-562</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">New alleles become fixed owing to random drift of nearly neutral mutations or to positive selection of substantially advantageous mutations. After decades of debate, the fraction of fixations driven by selection remains uncertain. Within 9,390 genes, we analysed 28,196 codons at which rat and mouse differ from each other at two nucleotide sites and 1,982 codons with three differences. At codons where rat-mouse divergence involved two non-synonymous substitutions, both of them occurred in the same lineage, either rat or mouse, in 64% of cases; however, independent substitutions would occur in the same lineage with a probability of only 50%. All three non-synonymous substitutions occurred in the same lineage for 46% of codons, instead of the 25% expected. Furthermore, comparison of 12 pairs of prokaryotic genomes also shows clumping of multiple non-synonymous substitutions in the same lineage. This pattern cannot be explained by correlated mutation or episodes of relaxed negative selection, but instead indicates that positive selection acts at many sites of rapid, successive amino acid replacement.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kryukov, GV.</style></author><author><style face="normal" font="default" size="100%">Castellano, S.</style></author><author><style face="normal" font="default" size="100%">Novoselov, SV.</style></author><author><style face="normal" font="default" size="100%">Lobanov, AV.</style></author><author><style face="normal" font="default" size="100%">Zehtab, O.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Gladyshev, VN.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of mammalian selenoproteomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/300/5624/143</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5624</style></number><volume><style face="normal" font="default" size="100%">300</style></volume><pages><style face="normal" font="default" size="100%">1439–1443</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In the genetic code, UGA serves as a stop signal and a selenocysteine codon, but no computational methods for identifying its coding function are available. Consequently, most selenoprotein genes are misannotated. We identified selenoprotein genes in sequenced mammalian genomes by methods that rely on identification of selenocysteine insertion RNA structures, the coding potential of UGA codons, and the presence of cysteine-containing homologs. The human selenoproteome consists of 25 selenoproteins.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Beltran, S.</style></author><author><style face="normal" font="default" size="100%">Blanco, E.</style></author><author><style face="normal" font="default" size="100%">Serras, F.</style></author><author><style face="normal" font="default" size="100%">Pérez-Villamil, B.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Artavanis-Tsakonas, S.</style></author><author><style face="normal" font="default" size="100%">Corominas, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcriptional network controlled by the trithorax-group gene ash2 in Drosophila melanogaster.</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Natl. Acad. Sci. U.S.A.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1073/pnas.053807510</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">100</style></volume><pages><style face="normal" font="default" size="100%">3293–3298</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The transcription factor absent, small, or homeotic discs 2 (ash2) gene is a member of the trithorax group of positive regulators of homeotic genes. Mutant alleles for ash2 are larvalpupal lethals and display imaginal disc and brain abnormalities. The allele used in this study is a true mutant for the trithorax function and lacks the longest transcript present in wild-type flies. In an attempt to identify gene targets of ash2, we have performed an expression analysis by using cDNA microarrays. Genes involved in cell cycle, cell proliferation, and cell adhesion are among these targets, and some of them are validated by functional and expression studies. Even though trithorax proteins act by modulating chromatin structure at particular chromosomal locations, evidence of physical aggregation of ash2-regulated genes has not been found. This work represents the first microarray analysis, to our knowledge, of a trithorax-group gene.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Poirot, O.</style></author><author><style face="normal" font="default" size="100%">O'Toole, E.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tcoffee@igs: A web server for computing, evaluating and combining multiple sequence alignments</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Consensus Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA/methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein/methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, RNA/methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">13</style></number><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">3503-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents Tcoffee@igs, a new server provided to the community by Hewlet Packard computers and the Centre National de la Recherche Scientifique. This server is a web-based tool dedicated to the computation, the evaluation and the combination of multiple sequence alignments. It uses the latest version of the T-Coffee package. Given a set of unaligned sequences, the server returns an evaluated multiple sequence alignment and the associated phylogenetic tree. This server also makes it possible to evaluate the local reliability of an existing alignment and to combine several alternative multiple alignments into a single new one. Tcoffee@igs can be used for aligning protein, RNA or DNA sequences. Datasets of up to 100 sequences (2000 residues long) can be processed. The server and its documentation are available from: http://igs-server.cnrs-mrs.fr/Tcoffee/.</style></abstract><accession-num><style face="normal" font="default" size="100%">12824354</style></accession-num><notes><style face="normal" font="default" size="100%">Journal Article</style></notes><auth-address><style face="normal" font="default" size="100%">Information Genomique et Structurale, CNRS, 31 Chemin Joseph Aiguier, 13 402 Marseille Cedex 20, France.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mennella, MR.</style></author><author><style face="normal" font="default" size="100%">Roma, G.</style></author><author><style face="normal" font="default" size="100%">Farina, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Active poly(ADPribose) metabolism in DNAase- and salt-resistant rat testis chromatin with high transcriptional activity/competence.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Cell. Biochem.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/jcb.10552</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">89</style></volume><pages><style face="normal" font="default" size="100%">688–697</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A chromatin fraction, named pP fraction, was prepared from rat testis nuclei, which had been digested with nuclease in order to separate soluble and insoluble chromatin. This fraction resembled nuclear matrix as it was highly resistant to DNAase digestion, had a high content of proteins compared to the low DNA percentage, and a noticeable transcriptional activity. Moreover, poly(ADPribosyl)ation system (i.e., poly(ADPR)polymerase, poly(ADPribose), and acceptor proteins) was still present at high levels. In order to study whether it might be identified as the protein support surrounding chromatin loops, this pP fraction was further analyzed after 3 M NaCl extraction. The 3 M NaCl extract and the highly insoluble pellet, named Nuclear Matrix Pellet, were characterized as it regards DNA, newly synthesized RNA and proteins. Furthermore, poly(ADPribose) metabolism was analyzed by measuring both poly(ADPribose) polymerase and poly(ADPribose) glycohydrolase activities, poly(ADPribose) distribution and by identifying protein acceptors. The final pellet had features of nuclear matrix containing less than 10% DNA and high percentage of proteins; 28% of newly synthesized RNA was still associated with this fraction. Long and branched polyADPribose were found in the nuclear matrix-like pellet, although ADPribose acceptors (mainly H1 and core histones) appeared to be modified mostly with short ADPribose oligomers. Longest and branched polymers were retained on the top of protein gel, likely bound to automodified poly(ADPribose) polymerase.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Agarwal, P.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Wiehe, T.</style></author><author><style face="normal" font="default" size="100%">Fickett, JW.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparative gene prediction in human and mouse.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1101/gr.87140</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">108–117</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The completion of the sequencing of the mouse genome promises to help predict human genes with greater accuracy. While current ab initio gene prediction programs are remarkably sensitive (i.e., they predict at least a fragment of most genes), their specificity is often low, predicting a large number of false-positive genes in the human genome. Sequence conservation at the protein level with the mouse genome can help eliminate some of those false positives. Here we describe SGP2, a gene prediction program that combines ab initio gene prediction with TBLASTX searches between two genome sequences to provide both sensitive and specific gene predictions. The accuracy of SGP2 when used to predict genes by comparing the human and mouse genomes is assessed on a number of data sets, including single-gene data sets, the highly curated human chromosome 22 predictions, and entire genome predictions from ENSEMBL. Results indicate that SGP2 outperforms purely ab initio gene prediction methods. Results also indicate that SGP2 works about as well with 3x shotgun data as it does with fully assembled genomes. SGP2 provides a high enough specificity that its predictions can be experimentally verified at a reasonable cost. SGP2 was used to generate a complete set of gene predictions on both the human and mouse by comparing the genomes of these two species. Our results suggest that another few thousand human and mouse genes currently not in ENSEMBL are worth verifying experimentally.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, ET.</style></author><author><style face="normal" font="default" size="100%">Agarwal, P.</style></author><author><style face="normal" font="default" size="100%">Ponting, CP.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Keibler, E.</style></author><author><style face="normal" font="default" size="100%">Lyle, R.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Brent, MR.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of mouse and human genomes followed by experimental verification yields an estimated 1,019 additional genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Natl. Acad. Sci. U.S.A.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1073/pnas.033756110</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">100</style></volume><pages><style face="normal" font="default" size="100%">1140–1145</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A primary motivation for sequencing the mouse genome was to accelerate the discovery of mammalian genes by using sequence conservation between mouse and human to identify coding exons. Achieving this goal proved challenging because of the large proportion of the mouse and human genomes that is apparently conserved but apparently does not code for protein. We developed a two-stage procedure that exploits the mouse and human genome sequences to produce a set of genes with a much higher rate of experimental verification than previously reported prediction methods. RT-PCR amplification and direct sequencing applied to an initial sample of mouse predictions that do not overlap previously known genes verified the regions flanking one intron in 139 predictions, with verification rates reaching 76%. On average, the confirmed predictions show more restricted expression patterns than the mouse orthologs of known human genes, and two-thirds lack homologs in fish genomes, demonstrating the sensitivity of this dual-genome approach to hard-to-find genes. We verified 112 previously unknown homologs of known proteins, including two homeobox proteins relevant to developmental biology, an aquaporin, and a homolog of dystrophin. We estimate that transcription and splicing can be verified for &gt;1,000 gene predictions identified by this method that do not overlap known genes. This is likely to constitute a significant fraction of the previously unknown, multiexon mammalian genes.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang, Z.</style></author><author><style face="normal" font="default" size="100%">Harrison, PM.</style></author><author><style face="normal" font="default" size="100%">Liu, Y.</style></author><author><style face="normal" font="default" size="100%">Gerstein, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Millions of years of evolution preserved: a comprehensive catalog of the processed pseudogenes in the human genome.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/13/12/254</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">2541–2558</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Processed pseudogenes were created by reverse-transcription of mRNAs; they provide snapshots of ancient genes existing millions of years ago in the genome. To find them in the present-day human, we developed a pipeline using features such as intron-absence, frame-disruption, polyadenylation, and truncation. This has enabled us to identify in recent genome drafts approximately 8000 processed pseudogenes (distributed from http://pseudogene.org). Overall, processed pseudogenes are very similar to their closest corresponding human gene, being 94% complete in coding regions, with sequence similarity of 75% for amino acids and 86% for nucleotides. Their chromosomal distribution appears random and dispersed, with the numbers on chromosomes proportional to length, suggesting sustained &quot;bombardment&quot; over evolution. However, it does vary with GC-content: Processed pseudogenes occur mostly in intermediate GC-content regions. This is similar to Alus but contrasts with functional genes and L1-repeats. Pseudogenes, moreover, have age profiles similar to Alus. The number of pseudogenes associated with a given gene follows a power-law relationship, with a few genes giving rise to many pseudogenes and most giving rise to few. The prevalence of processed pseudogenes agrees well with germ-line gene expression. Highly expressed ribosomal proteins account for approximately 20% of the total. Other notables include cyclophilin-A, keratin, GAPDH, and cytochrome c.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Wiehe, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">gff2aplot: Plotting sequence comparisons.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/1466823</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">18</style></number><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">2477–2479</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">SUMMARY: gff2aplot is a program to visualize the alignment of two sequences together with their annotations. Input for the program consists of single or multiple files in GFF-format which specify the alignment coordinates and annotation features of both sequences. Output is in PostScript format of any size. The features to be displayed are highly customizable to meet user specific needs. The program serves to generate print-quality images for comparative genome sequence analysis. AVAILABILITY: gff2aplot is freely available under the GNU software licence and can be downloaded from the address specified below. Supplementary information: http://genome.imim.es/software/gfftools/GFF2APLOT.html</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huynen, MA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reconstruction of the proto-mitochondrial metabolism.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/301/5633/60</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5633</style></number><volume><style face="normal" font="default" size="100%">301</style></volume><pages><style face="normal" font="default" size="100%">609</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sunyaev, Shamil</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Bork, Peer</style></author><author><style face="normal" font="default" size="100%">Ramensky, Vasily</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of Selection, Mutation rate and Genetic Drift on Human Genetic Variation</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">3325-3330</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The accumulation of genome-wide information on single nucleotide polymorphisms in humans provides an unprecedented opportunity to detect the evolutionary forces responsible for heterogeneity of the level of genetic variability across loci. Previous studies have shown that history of recombination events has produced long haplotype blocks in the human genome, which contribute to this heterogeneity. Other factors, however, such as natural selection or the heterogeneity of mutation rates across loci, may also lead to heterogeneity of genetic variability. We compared synonymous and non-synonymous variability within human genes with their divergence from murine orthologs. We separately analyzed the non-synonymous variants predicted to damage protein structure or function and the variants predicted to be functionally benign. The predictions were based on comparative sequence analysis and, in some cases, on the analysis of protein structure. A strong correlation between non-synonymous, benign variability and non-synonymous human-mouse divergence suggests that selection played an important role in shaping the pattern of variability in coding regions of human genes. However, the lack of correlation between deleterious variability and evolutionary divergence shows that a substantial proportion of the observed non-synonymous single-nucleotide polymorphisms reduces fitness and never reaches fixation. Evolutionary and medical implications of the impact of selection on human polymorphisms are discussed.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Koonin, Eugene V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of Alternative Splicing: Deletions, Insertions and Origin of Functional Parts of Proteins from Intron Sequences</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">115-119</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Alternative splicing is thought to be a major source of functional diversity in animal proteins. We analyzed the evolutionary conservation of proteins encoded by alternatively spliced genes and predicted the ancestral state for 73 cases of alternative splicing (25 insertions and 48 deletions). The amino acid sequences of most of the inserts in proteins produced by alternative splicing are as conserved as the surrounding sequences. Thus, alternative splicing often creates novel isoforms by the insertion of new, functional protein sequences that probably originated from noncoding sequences of introns.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">O'Sullivan, O.</style></author><author><style face="normal" font="default" size="100%">Zehnder, M.</style></author><author><style face="normal" font="default" size="100%">Higgins, D.</style></author><author><style face="normal" font="default" size="100%">Bucher, P</style></author><author><style face="normal" font="default" size="100%">Grosdidier, A.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">APDB: a novel measure for benchmarking sequence alignment methods without reference alignments</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Benchmarking/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Reference Standards</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Sensitivity and Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods/standards</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA/ methods/standards</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein/ methods/standards</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Software Validation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><volume><style face="normal" font="default" size="100%">19 Suppl 1</style></volume><pages><style face="normal" font="default" size="100%">i215-21</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: We describe APDB, a novel measure for evaluating the quality of a protein sequence alignment, given two or more PDB structures. This evaluation does not require a reference alignment or a structure superposition. APDB is designed to efficiently and objectively benchmark multiple sequence alignment methods. RESULTS: Using existing collections of reference multiple sequence alignments and existing alignment methods, we show that APDB gives results that are consistent with those obtained using conventional evaluations. We also show that APDB is suitable for evaluating sequence alignments that are structurally equivalent. We conclude that APDB provides an alternative to more conventional methods used for benchmarking sequence alignment packages.</style></abstract><accession-num><style face="normal" font="default" size="100%">12855461</style></accession-num><notes><style face="normal" font="default" size="100%">Comparative StudyEvaluation StudiesJournal ArticleValidation Studies</style></notes><auth-address><style face="normal" font="default" size="100%">Department of Biochemistry, University College, Cork, Ireland.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Abergel, C.</style></author><author><style face="normal" font="default" size="100%">Coutard, B.</style></author><author><style face="normal" font="default" size="100%">Byrne, D.</style></author><author><style face="normal" font="default" size="100%">Chenivesse, S.</style></author><author><style face="normal" font="default" size="100%">Claude, J. B.</style></author><author><style face="normal" font="default" size="100%">Deregnaucourt, C.</style></author><author><style face="normal" font="default" size="100%">Fricaux, T.</style></author><author><style face="normal" font="default" size="100%">Gianesini-Boutreux, C.</style></author><author><style face="normal" font="default" size="100%">Jeudy, S.</style></author><author><style face="normal" font="default" size="100%">Lebrun, R.</style></author><author><style face="normal" font="default" size="100%">Maza, C.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Poirot, O.</style></author><author><style face="normal" font="default" size="100%">Suhre, K.</style></author><author><style face="normal" font="default" size="100%">Varagnol, M.</style></author><author><style face="normal" font="default" size="100%">Claverie, J. M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Structural genomics of highly conserved microbial genes of unknown function in search of new antibacterial targets</style></title><secondary-title><style face="normal" font="default" size="100%">J Struct Funct Genomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acid Anhydride Hydrolases/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Alcohol Oxidoreductases/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Anti-Bacterial Agents/ pharmacology</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacterial Proteins/ chemistry/genetics/isolation &amp; purification/metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">Carrier Proteins/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Conserved Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Crystallography, X-Ray</style></keyword><keyword><style  face="normal" font="default" size="100%">Drug Design</style></keyword><keyword><style  face="normal" font="default" size="100%">Endopeptidases/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxidoreductases/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymerase Chain Reaction/methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><number><style face="normal" font="default" size="100%">2-3</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">141-57</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">With more than 100 antibacterial drugs at our disposal in the 1980's, the problem of bacterial infection was considered solved. Today, however, most hospital infections are insensitive to several classes of antibacterial drugs, and deadly strains of Staphylococcus aureus resistant to vancomycin--the last resort antibiotic--have recently begin to appear. Other life-threatening microbes, such as Enterococcus faecalis and Mycobacterium tuberculosis are already able to resist every available antibiotic. There is thus an urgent, and continuous need for new, preferably large-spectrum, antibacterial molecules, ideally targeting new biochemical pathways. Here we report on the progress of our structural genomics program aiming at the discovery of new antibacterial gene targets among evolutionary conserved genes of uncharacterized function. A series of bioinformatic and comparative genomics analyses were used to identify a set of 221 candidate genes common to Gram-positive and Gram-negative bacteria. These genes were split between two laboratories. They are now submitted to a systematic 3-D structure determination protocol including cloning, protein expression and purification, crystallization, X-ray diffraction, structure interpretation, and function prediction. We describe here our strategies for the 111 genes processed in our laboratory. Bioinformatics is used at most stages of the production process and out of 111 genes processed--and 17 months into the project--108 have been successfully cloned, 103 have exhibited detectable expression, 84 have led to the production of soluble protein, 46 have been purified, 12 have led to usable crystals, and 7 structures have been determined.</style></abstract><accession-num><style face="normal" font="default" size="100%">14649299</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Structural and Genomic Information Laboratory, UMR 1889 CNRS-AVENTIS, 13402 Marseille cedex 20, France. Chantal.Abergel@igs.cnrs-mrs.fr</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Holt, RA.</style></author><author><style face="normal" font="default" size="100%">Subramanian, GM.</style></author><author><style face="normal" font="default" size="100%">Halpern, A.</style></author><author><style face="normal" font="default" size="100%">Sutton, GG.</style></author><author><style face="normal" font="default" size="100%">Charlab, R.</style></author><author><style face="normal" font="default" size="100%">Nusskern, DR.</style></author><author><style face="normal" font="default" size="100%">Wincker, P.</style></author><author><style face="normal" font="default" size="100%">Clark, AG.</style></author><author><style face="normal" font="default" size="100%">Ribeiro, JM.</style></author><author><style face="normal" font="default" size="100%">Wides, R.</style></author><author><style face="normal" font="default" size="100%">Salzberg, SL.</style></author><author><style face="normal" font="default" size="100%">Loftus, B.</style></author><author><style face="normal" font="default" size="100%">Yandell, M.</style></author><author><style face="normal" font="default" size="100%">Majoros, WH.</style></author><author><style face="normal" font="default" size="100%">Rusch, DB.</style></author><author><style face="normal" font="default" size="100%">Lai, Z.</style></author><author><style face="normal" font="default" size="100%">Kraft, CL.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Anthouard, V.</style></author><author><style face="normal" font="default" size="100%">Arensburger, P.</style></author><author><style face="normal" font="default" size="100%">Atkinson, PW.</style></author><author><style face="normal" font="default" size="100%">Baden, H.</style></author><author><style face="normal" font="default" size="100%">De Berardinis, V.</style></author><author><style face="normal" font="default" size="100%">Baldwin, D.</style></author><author><style face="normal" font="default" size="100%">Benes, V.</style></author><author><style face="normal" font="default" size="100%">Biedler, J.</style></author><author><style face="normal" font="default" size="100%">Blass, C.</style></author><author><style face="normal" font="default" size="100%">Bolanos, R.</style></author><author><style face="normal" font="default" size="100%">Boscus, D.</style></author><author><style face="normal" font="default" size="100%">Barnstead, M.</style></author><author><style face="normal" font="default" size="100%">Cai, S.</style></author><author><style face="normal" font="default" size="100%">Center, A.</style></author><author><style face="normal" font="default" size="100%">Chaturverdi, K.</style></author><author><style face="normal" font="default" size="100%">Christophides, GK.</style></author><author><style face="normal" font="default" size="100%">Chrystal, MA.</style></author><author><style face="normal" font="default" size="100%">Clamp, M.</style></author><author><style face="normal" font="default" size="100%">Cravchik, A.</style></author><author><style face="normal" font="default" size="100%">Curwen, V.</style></author><author><style face="normal" font="default" size="100%">Dana, A.</style></author><author><style face="normal" font="default" size="100%">Delcher, A.</style></author><author><style face="normal" font="default" size="100%">Dew, I.</style></author><author><style face="normal" font="default" size="100%">Evans, CA.</style></author><author><style face="normal" font="default" size="100%">Flanigan, M.</style></author><author><style face="normal" font="default" size="100%">Grundschober-Freimoser, A.</style></author><author><style face="normal" font="default" size="100%">Friedli, L.</style></author><author><style face="normal" font="default" size="100%">Gu, Z.</style></author><author><style face="normal" font="default" size="100%">Guan, P.</style></author><author><style face="normal" font="default" size="100%">Guigo, R.</style></author><author><style face="normal" font="default" size="100%">Hillenmeyer, ME.</style></author><author><style face="normal" font="default" size="100%">Hladun, SL.</style></author><author><style face="normal" font="default" size="100%">Hogan, JR.</style></author><author><style face="normal" font="default" size="100%">Hong, YS.</style></author><author><style face="normal" font="default" size="100%">Hoover, J.</style></author><author><style face="normal" font="default" size="100%">Jaillon, O.</style></author><author><style face="normal" font="default" size="100%">Ke, Z.</style></author><author><style face="normal" font="default" size="100%">Kodira, C.</style></author><author><style face="normal" font="default" size="100%">Kokoza, E.</style></author><author><style face="normal" font="default" size="100%">Koutsos, A.</style></author><author><style face="normal" font="default" size="100%">Letunic, I.</style></author><author><style face="normal" font="default" size="100%">Levitsky, A.</style></author><author><style face="normal" font="default" size="100%">Liang, Y.</style></author><author><style face="normal" font="default" size="100%">Lin, JJ.</style></author><author><style face="normal" font="default" size="100%">Lobo, NF.</style></author><author><style face="normal" font="default" size="100%">Lopez, JR.</style></author><author><style face="normal" font="default" size="100%">Malek, JA.</style></author><author><style face="normal" font="default" size="100%">McIntosh, TC.</style></author><author><style face="normal" font="default" size="100%">Meister, S.</style></author><author><style face="normal" font="default" size="100%">Miller, J.</style></author><author><style face="normal" font="default" size="100%">Mobarry, C.</style></author><author><style face="normal" font="default" size="100%">Mongin, E.</style></author><author><style face="normal" font="default" size="100%">Murphy, SD.</style></author><author><style face="normal" font="default" size="100%">O'Brochta, DA.</style></author><author><style face="normal" font="default" size="100%">Pfannkoch, C.</style></author><author><style face="normal" font="default" size="100%">Qi, R.</style></author><author><style face="normal" font="default" size="100%">Regier, MA.</style></author><author><style face="normal" font="default" size="100%">Remington, K.</style></author><author><style face="normal" font="default" size="100%">Shao, H.</style></author><author><style face="normal" font="default" size="100%">Sharakhova, MV.</style></author><author><style face="normal" font="default" size="100%">Sitter, CD.</style></author><author><style face="normal" font="default" size="100%">Shetty, J.</style></author><author><style face="normal" font="default" size="100%">Smith, TJ.</style></author><author><style face="normal" font="default" size="100%">Strong, R.</style></author><author><style face="normal" font="default" size="100%">Sun, J.</style></author><author><style face="normal" font="default" size="100%">Thomasova, D.</style></author><author><style face="normal" font="default" size="100%">Ton, LQ.</style></author><author><style face="normal" font="default" size="100%">Topalis, P.</style></author><author><style face="normal" font="default" size="100%">Tu, Z.</style></author><author><style face="normal" font="default" size="100%">Unger, MF.</style></author><author><style face="normal" font="default" size="100%">Walenz, B.</style></author><author><style face="normal" font="default" size="100%">Wang, A.</style></author><author><style face="normal" font="default" size="100%">Wang, J.</style></author><author><style face="normal" font="default" size="100%">Wang, M.</style></author><author><style face="normal" font="default" size="100%">Wang, X.</style></author><author><style face="normal" font="default" size="100%">Woodford, KJ.</style></author><author><style face="normal" font="default" size="100%">Wortman, JR.</style></author><author><style face="normal" font="default" size="100%">Wu, M.</style></author><author><style face="normal" font="default" size="100%">Yao, A.</style></author><author><style face="normal" font="default" size="100%">Zdobnov, EM.</style></author><author><style face="normal" font="default" size="100%">Zhang, H.</style></author><author><style face="normal" font="default" size="100%">Zhao, Q.</style></author><author><style face="normal" font="default" size="100%">Zhao, S.</style></author><author><style face="normal" font="default" size="100%">Zhu, SC.</style></author><author><style face="normal" font="default" size="100%">Zhimulev, I.</style></author><author><style face="normal" font="default" size="100%">Coluzzi, M.</style></author><author><style face="normal" font="default" size="100%">della Torre, A.</style></author><author><style face="normal" font="default" size="100%">Roth, CW.</style></author><author><style face="normal" font="default" size="100%">Louis, C.</style></author><author><style face="normal" font="default" size="100%">Kalush, F.</style></author><author><style face="normal" font="default" size="100%">Mural, RJ.</style></author><author><style face="normal" font="default" size="100%">Myers, EW.</style></author><author><style face="normal" font="default" size="100%">Adams, MD.</style></author><author><style face="normal" font="default" size="100%">Smith, HO.</style></author><author><style face="normal" font="default" size="100%">Broder, S.</style></author><author><style face="normal" font="default" size="100%">Gardner, MJ.</style></author><author><style face="normal" font="default" size="100%">Fraser, CM.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Bork, P.</style></author><author><style face="normal" font="default" size="100%">Brey, PT.</style></author><author><style face="normal" font="default" size="100%">Venter, JC.</style></author><author><style face="normal" font="default" size="100%">Weissenbach, J.</style></author><author><style face="normal" font="default" size="100%">Kafatos, FC.</style></author><author><style face="normal" font="default" size="100%">Collins, FH.</style></author><author><style face="normal" font="default" size="100%">Hoffman, SL.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The genome sequence of the malaria mosquito Anopheles gambiae.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/298/5591/12</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5591</style></number><volume><style face="normal" font="default" size="100%">298</style></volume><pages><style face="normal" font="default" size="100%">129–149</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Anopheles gambiae is the principal vector of malaria, a disease that afflicts more than 500 million people and causes more than 1 million deaths each year. Tenfold shotgun sequence coverage was obtained from the PEST strain of A. gambiae and assembled into scaffolds that span 278 million base pairs. A total of 91% of the genome was organized in 303 scaffolds; the largest scaffold was 23.1 million base pairs. There was substantial genetic variation within this strain, and the apparent existence of two haplotypes of approximately equal frequency (&quot;dual haplotypes&quot;) in a substantial fraction of the genome likely reflects the outbred nature of the PEST strain. The sequence produced a conservative inference of more than 400,000 single-nucleotide polymorphisms that showed a markedly bimodal density distribution. Analysis of the genome sequence revealed strong evidence for about 14,000 protein-encoding transcripts. Prominent expansions in specific families of proteins likely involved in cell adhesion and immunity were noted. An expressed sequence tag analysis of genes regulated by blood feeding provided insights into the physiological adaptations of a hematophagous insect.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Glöckner, G.</style></author><author><style face="normal" font="default" size="100%">Eichinger, L.</style></author><author><style face="normal" font="default" size="100%">Szafranski, K.</style></author><author><style face="normal" font="default" size="100%">Pachebat, JA.</style></author><author><style face="normal" font="default" size="100%">Bankier, AT.</style></author><author><style face="normal" font="default" size="100%">Dear, PH.</style></author><author><style face="normal" font="default" size="100%">Lehmann, R.</style></author><author><style face="normal" font="default" size="100%">Baumgart, C.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Kumpf, K.</style></author><author><style face="normal" font="default" size="100%">Tunggal, B.</style></author><author><style face="normal" font="default" size="100%">Cox, E.</style></author><author><style face="normal" font="default" size="100%">Quail, MA.</style></author><author><style face="normal" font="default" size="100%">Platzer, M.</style></author><author><style face="normal" font="default" size="100%">Rosenthal, A.</style></author><author><style face="normal" font="default" size="100%">Noegel, AA.</style></author><author><style face="normal" font="default" size="100%">Dictyostelium Genome Sequencing Consortium</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sequence and analysis of chromosome 2 of Dictyostelium discoideum.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0084</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6893</style></number><volume><style face="normal" font="default" size="100%">418</style></volume><pages><style face="normal" font="default" size="100%">79–85</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The genome of the lower eukaryote Dictyostelium discoideum comprises six chromosomes. Here we report the sequence of the largest, chromosome 2, which at 8 megabases (Mb) represents about 25% of the genome. Despite an A + T content of nearly 80%, the chromosome codes for 2,799 predicted protein coding genes and 73 transfer RNA genes. This gene density, about 1 gene per 2.6 kilobases (kb), is surpassed only by Saccharomyces cerevisiae (one per 2 kb) and is similar to that of Schizosaccharomyces pombe (one per 2.5 kb). If we assume that the other chromosomes have a similar gene density, we can expect around 11,000 genes in the D. discoideum genome. A significant number of the genes show higher similarities to genes of vertebrates than to those of other fully sequenced eukaryotes. This analysis strengthens the view that the evolutionary position of D. discoideum is located before the branching of metazoa and fungi but after the divergence of the plant kingdom, placing it close to the base of metazoan evolution.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Recent progress in multiple sequence alignment: a survey</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacogenomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">131-44</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The assembly of a multiple sequence alignment (MSA) has become one of the most common tasks when dealing with sequence analysis. Unfortunately, the wide range of available methods and the differences in the results given by these methods makes it hard for a non-specialist to decide which program is best suited for a given purpose. In this review we briefly describe existing techniques and expose the potential strengths and weaknesses of the most widely used multiple alignment packages.</style></abstract><accession-num><style face="normal" font="default" size="100%">11966409</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleReview</style></notes><auth-address><style face="normal" font="default" size="100%">Information Genetique et Structurale, UMR 1889, 31 Chemin Joseph Aiguier, 13 006 Marseille, France. cedric.notredame@igs.cnrs-mrs.fr</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mouse Genome Sequencing Consortium</style></author><author><style face="normal" font="default" size="100%">Waterston, RH.</style></author><author><style face="normal" font="default" size="100%">Lindblad-Toh, K.</style></author><author><style face="normal" font="default" size="100%">Birney, E.</style></author><author><style face="normal" font="default" size="100%">Rogers, J.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Agarwal, P.</style></author><author><style face="normal" font="default" size="100%">Agarwala, R.</style></author><author><style face="normal" font="default" size="100%">Ainscough, R.</style></author><author><style face="normal" font="default" size="100%">Alexandersson, M.</style></author><author><style face="normal" font="default" size="100%">An, P.</style></author><author><style face="normal" font="default" size="100%">Antonarakis, SE.</style></author><author><style face="normal" font="default" size="100%">Attwood, J.</style></author><author><style face="normal" font="default" size="100%">Baertsch, R.</style></author><author><style face="normal" font="default" size="100%">Bailey, J.</style></author><author><style face="normal" font="default" size="100%">Barlow, K.</style></author><author><style face="normal" font="default" size="100%">Beck, S.</style></author><author><style face="normal" font="default" size="100%">Berry, E.</style></author><author><style face="normal" font="default" size="100%">Birren, B.</style></author><author><style face="normal" font="default" size="100%">Bloom, T.</style></author><author><style face="normal" font="default" size="100%">Bork, P.</style></author><author><style face="normal" font="default" size="100%">Botcherby, M.</style></author><author><style face="normal" font="default" size="100%">Bray, N.</style></author><author><style face="normal" font="default" size="100%">Brent, MR.</style></author><author><style face="normal" font="default" size="100%">Brown, DG.</style></author><author><style face="normal" font="default" size="100%">Brown, SD.</style></author><author><style face="normal" font="default" size="100%">Bult, C.</style></author><author><style face="normal" font="default" size="100%">Burton, J.</style></author><author><style face="normal" font="default" size="100%">Butler, J.</style></author><author><style face="normal" font="default" size="100%">Campbell, RD.</style></author><author><style face="normal" font="default" size="100%">Carninci, P.</style></author><author><style face="normal" font="default" size="100%">Cawley, S.</style></author><author><style face="normal" font="default" size="100%">Chiaromonte, F.</style></author><author><style face="normal" font="default" size="100%">Chinwalla, AT.</style></author><author><style face="normal" font="default" size="100%">Church, DM.</style></author><author><style face="normal" font="default" size="100%">Clamp, M.</style></author><author><style face="normal" font="default" size="100%">Clee, C.</style></author><author><style face="normal" font="default" size="100%">Collins, FS.</style></author><author><style face="normal" font="default" size="100%">Cook, LL.</style></author><author><style face="normal" font="default" size="100%">Copley, RR.</style></author><author><style face="normal" font="default" size="100%">Coulson, A.</style></author><author><style face="normal" font="default" size="100%">Couronne, O.</style></author><author><style face="normal" font="default" size="100%">Cuff, J.</style></author><author><style face="normal" font="default" size="100%">Curwen, V.</style></author><author><style face="normal" font="default" size="100%">Cutts, T.</style></author><author><style face="normal" font="default" size="100%">Daly, M.</style></author><author><style face="normal" font="default" size="100%">David, R.</style></author><author><style face="normal" font="default" size="100%">Davies, J.</style></author><author><style face="normal" font="default" size="100%">Delehaunty, KD.</style></author><author><style face="normal" font="default" size="100%">Deri, J.</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, ET.</style></author><author><style face="normal" font="default" size="100%">Dewey, C.</style></author><author><style face="normal" font="default" size="100%">Dickens, NJ.</style></author><author><style face="normal" font="default" size="100%">Diekhans, M.</style></author><author><style face="normal" font="default" size="100%">Dodge, S.</style></author><author><style face="normal" font="default" size="100%">Dubchak, I.</style></author><author><style face="normal" font="default" size="100%">Dunn, DM.</style></author><author><style face="normal" font="default" size="100%">Eddy, SR.</style></author><author><style face="normal" font="default" size="100%">Elnitski, L.</style></author><author><style face="normal" font="default" size="100%">Emes, RD.</style></author><author><style face="normal" font="default" size="100%">Eswara, P.</style></author><author><style face="normal" font="default" size="100%">Eyras, E.</style></author><author><style face="normal" font="default" size="100%">Felsenfeld, A.</style></author><author><style face="normal" font="default" size="100%">Fewell, GA.</style></author><author><style face="normal" font="default" size="100%">Flicek, P.</style></author><author><style face="normal" font="default" size="100%">Foley, K.</style></author><author><style face="normal" font="default" size="100%">Frankel, WN.</style></author><author><style face="normal" font="default" size="100%">Fulton, LA.</style></author><author><style face="normal" font="default" size="100%">Fulton, RS.</style></author><author><style face="normal" font="default" size="100%">Furey, TS.</style></author><author><style face="normal" font="default" size="100%">Gage, D.</style></author><author><style face="normal" font="default" size="100%">Gibbs, RA.</style></author><author><style face="normal" font="default" size="100%">Glusman, G.</style></author><author><style face="normal" font="default" size="100%">Gnerre, S.</style></author><author><style face="normal" font="default" size="100%">Goldman, N.</style></author><author><style face="normal" font="default" size="100%">Goodstadt, L.</style></author><author><style face="normal" font="default" size="100%">Grafham, D.</style></author><author><style face="normal" font="default" size="100%">Graves, TA.</style></author><author><style face="normal" font="default" size="100%">Green, ED.</style></author><author><style face="normal" font="default" size="100%">Gregory, S.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Guyer, M.</style></author><author><style face="normal" font="default" size="100%">Hardison, RC.</style></author><author><style face="normal" font="default" size="100%">Haussler, D.</style></author><author><style face="normal" font="default" size="100%">Hayashizaki, Y.</style></author><author><style face="normal" font="default" size="100%">Hillier, LW.</style></author><author><style face="normal" font="default" size="100%">Hinrichs, A.</style></author><author><style face="normal" font="default" size="100%">Hlavina, W.</style></author><author><style face="normal" font="default" size="100%">Holzer, T.</style></author><author><style face="normal" font="default" size="100%">Hsu, F.</style></author><author><style face="normal" font="default" size="100%">Hua, A.</style></author><author><style face="normal" font="default" size="100%">Hubbard, T.</style></author><author><style face="normal" font="default" size="100%">Hunt, A.</style></author><author><style face="normal" font="default" size="100%">Jackson, I.</style></author><author><style face="normal" font="default" size="100%">Jaffe, DB.</style></author><author><style face="normal" font="default" size="100%">Johnson, LS.</style></author><author><style face="normal" font="default" size="100%">Jones, M.</style></author><author><style face="normal" font="default" size="100%">Jones, TA.</style></author><author><style face="normal" font="default" size="100%">Joy, A.</style></author><author><style face="normal" font="default" size="100%">Kamal, M.</style></author><author><style face="normal" font="default" size="100%">Karlsson, EK.</style></author><author><style face="normal" font="default" size="100%">Karolchik, D.</style></author><author><style face="normal" font="default" size="100%">Kasprzyk, A.</style></author><author><style face="normal" font="default" size="100%">Kawai, J.</style></author><author><style face="normal" font="default" size="100%">Keibler, E.</style></author><author><style face="normal" font="default" size="100%">Kells, C.</style></author><author><style face="normal" font="default" size="100%">Kent, WJ.</style></author><author><style face="normal" font="default" size="100%">Kirby, A.</style></author><author><style face="normal" font="default" size="100%">Kolbe, DL.</style></author><author><style face="normal" font="default" size="100%">Korf, I.</style></author><author><style face="normal" font="default" size="100%">Kucherlapati, RS.</style></author><author><style face="normal" font="default" size="100%">Kulbokas, EJ.</style></author><author><style face="normal" font="default" size="100%">Kulp, D.</style></author><author><style face="normal" font="default" size="100%">Landers, T.</style></author><author><style face="normal" font="default" size="100%">Leger, JP.</style></author><author><style face="normal" font="default" size="100%">Leonard, S.</style></author><author><style face="normal" font="default" size="100%">Letunic, I.</style></author><author><style face="normal" font="default" size="100%">Levine, R.</style></author><author><style face="normal" font="default" size="100%">Li, J.</style></author><author><style face="normal" font="default" size="100%">Li, M.</style></author><author><style face="normal" font="default" size="100%">Lloyd, C.</style></author><author><style face="normal" font="default" size="100%">Lucas, S.</style></author><author><style face="normal" font="default" size="100%">Ma, B.</style></author><author><style face="normal" font="default" size="100%">Maglott, DR.</style></author><author><style face="normal" font="default" size="100%">Mardis, ER.</style></author><author><style face="normal" font="default" size="100%">Matthews, L.</style></author><author><style face="normal" font="default" size="100%">Mauceli, E.</style></author><author><style face="normal" font="default" size="100%">Mayer, JH.</style></author><author><style face="normal" font="default" size="100%">McCarthy, M.</style></author><author><style face="normal" font="default" size="100%">McCombie, WR.</style></author><author><style face="normal" font="default" size="100%">McLaren, S.</style></author><author><style face="normal" font="default" size="100%">McLay, K.</style></author><author><style face="normal" font="default" size="100%">McPherson, JD.</style></author><author><style face="normal" font="default" size="100%">Meldrim, J.</style></author><author><style face="normal" font="default" size="100%">Meredith, B.</style></author><author><style face="normal" font="default" size="100%">Mesirov, JP.</style></author><author><style face="normal" font="default" size="100%">Miller, W.</style></author><author><style face="normal" font="default" size="100%">Miner, TL.</style></author><author><style face="normal" font="default" size="100%">Mongin, E.</style></author><author><style face="normal" font="default" size="100%">Montgomery, KT.</style></author><author><style face="normal" font="default" size="100%">Morgan, M.</style></author><author><style face="normal" font="default" size="100%">Mott, R.</style></author><author><style face="normal" font="default" size="100%">Mullikin, JC.</style></author><author><style face="normal" font="default" size="100%">Muzny, DM.</style></author><author><style face="normal" font="default" size="100%">Nash, WE.</style></author><author><style face="normal" font="default" size="100%">Nelson, JO.</style></author><author><style face="normal" font="default" size="100%">Nhan, MN.</style></author><author><style face="normal" font="default" size="100%">Nicol, R.</style></author><author><style face="normal" font="default" size="100%">Ning, Z.</style></author><author><style face="normal" font="default" size="100%">Nusbaum, C.</style></author><author><style face="normal" font="default" size="100%">O'Connor, MJ.</style></author><author><style face="normal" font="default" size="100%">Okazaki, Y.</style></author><author><style face="normal" font="default" size="100%">Oliver, K.</style></author><author><style face="normal" font="default" size="100%">Overton-Larty, E.</style></author><author><style face="normal" font="default" size="100%">Pachter, L.</style></author><author><style face="normal" font="default" size="100%">Parra, G.</style></author><author><style face="normal" font="default" size="100%">Pepin, KH.</style></author><author><style face="normal" font="default" size="100%">Peterson, J.</style></author><author><style face="normal" font="default" size="100%">Pevzner, P.</style></author><author><style face="normal" font="default" size="100%">Plumb, R.</style></author><author><style face="normal" font="default" size="100%">Pohl, CS.</style></author><author><style face="normal" font="default" size="100%">Poliakov, A.</style></author><author><style face="normal" font="default" size="100%">Ponce, TC.</style></author><author><style face="normal" font="default" size="100%">Ponting, CP.</style></author><author><style face="normal" font="default" size="100%">Potter, S.</style></author><author><style face="normal" font="default" size="100%">Quail, M.</style></author><author><style face="normal" font="default" size="100%">Reymond, A.</style></author><author><style face="normal" font="default" size="100%">Roe, BA.</style></author><author><style face="normal" font="default" size="100%">Roskin, KM.</style></author><author><style face="normal" font="default" size="100%">Rubin, EM.</style></author><author><style face="normal" font="default" size="100%">Rust, AG.</style></author><author><style face="normal" font="default" size="100%">Santos, R.</style></author><author><style face="normal" font="default" size="100%">Sapojnikov, V.</style></author><author><style face="normal" font="default" size="100%">Schultz, B.</style></author><author><style face="normal" font="default" size="100%">Schultz, J.</style></author><author><style face="normal" font="default" size="100%">Schwartz, MS.</style></author><author><style face="normal" font="default" size="100%">Schwartz, S.</style></author><author><style face="normal" font="default" size="100%">Scott, C.</style></author><author><style face="normal" font="default" size="100%">Seaman, S.</style></author><author><style face="normal" font="default" size="100%">Searle, S.</style></author><author><style face="normal" font="default" size="100%">Sharpe, T.</style></author><author><style face="normal" font="default" size="100%">Sheridan, A.</style></author><author><style face="normal" font="default" size="100%">Shownkeen, R.</style></author><author><style face="normal" font="default" size="100%">Sims, S.</style></author><author><style face="normal" font="default" size="100%">Singer, JB.</style></author><author><style face="normal" font="default" size="100%">Slater, G.</style></author><author><style face="normal" font="default" size="100%">Smit, A.</style></author><author><style face="normal" font="default" size="100%">Smith, DR.</style></author><author><style face="normal" font="default" size="100%">Spencer, B.</style></author><author><style face="normal" font="default" size="100%">Stabenau, A.</style></author><author><style face="normal" font="default" size="100%">Stange-Thomann, N.</style></author><author><style face="normal" font="default" size="100%">Sugnet, C.</style></author><author><style face="normal" font="default" size="100%">Suyama, M.</style></author><author><style face="normal" font="default" size="100%">Tesler, G.</style></author><author><style face="normal" font="default" size="100%">Thompson, J.</style></author><author><style face="normal" font="default" size="100%">Torrents, D.</style></author><author><style face="normal" font="default" size="100%">Trevaskis, E.</style></author><author><style face="normal" font="default" size="100%">Tromp, J.</style></author><author><style face="normal" font="default" size="100%">Ucla, C.</style></author><author><style face="normal" font="default" size="100%">Ureta-Vidal, A.</style></author><author><style face="normal" font="default" size="100%">Vinson, JP.</style></author><author><style face="normal" font="default" size="100%">Von Niederhausern, AC.</style></author><author><style face="normal" font="default" size="100%">Wade, CM.</style></author><author><style face="normal" font="default" size="100%">Wall, M.</style></author><author><style face="normal" font="default" size="100%">Weber, RJ.</style></author><author><style face="normal" font="default" size="100%">Weiss, RB.</style></author><author><style face="normal" font="default" size="100%">Wendl, MC.</style></author><author><style face="normal" font="default" size="100%">West, AP.</style></author><author><style face="normal" font="default" size="100%">Wetterstrand, K.</style></author><author><style face="normal" font="default" size="100%">Wheeler, R.</style></author><author><style face="normal" font="default" size="100%">Whelan, S.</style></author><author><style face="normal" font="default" size="100%">Wierzbowski, J.</style></author><author><style face="normal" font="default" size="100%">Willey, D.</style></author><author><style face="normal" font="default" size="100%">Williams, S.</style></author><author><style face="normal" font="default" size="100%">Wilson, RK.</style></author><author><style face="normal" font="default" size="100%">Winter, E.</style></author><author><style face="normal" font="default" size="100%">Worley, KC.</style></author><author><style face="normal" font="default" size="100%">Wyman, D.</style></author><author><style face="normal" font="default" size="100%">Yang, S.</style></author><author><style face="normal" font="default" size="100%">Yang, SP.</style></author><author><style face="normal" font="default" size="100%">Zdobnov, EM.</style></author><author><style face="normal" font="default" size="100%">Zody, MC.</style></author><author><style face="normal" font="default" size="100%">Lander, ES.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Initial sequencing and comparative analysis of the mouse genome.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nature0126</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6915</style></number><volume><style face="normal" font="default" size="100%">420</style></volume><pages><style face="normal" font="default" size="100%">520–562</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Perelygin, Andrey A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Rogozin, Igor B.</style></author><author><style face="normal" font="default" size="100%">Brinton, Margo A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of the Mouse polyubiquitin-C gene</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Evol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">55</style></volume><pages><style face="normal" font="default" size="100%">202-210</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The polymeric ubiquitin (poly-u) genes are composed of tandem 228-bp repeats with no spacer sequences between individual monomer units. Ubiquitin is one of the most conserved proteins known to date, and the individual units within a number of poly-u genes are significantly more similar to each other than would be expected if each unit evolved independently. It has been proposed that the rather striking similarity among poly-u monomers in some lineages is caused by a series of homogenization events. Here we report the sequences of the polyubiquitin-C (Ubc) genes in two mouse strains. Analysis of these sequences, as well as those of the previously reported Chinese hamster and rat poly-u genes, supports the assertion that the homogenization of the ubiquitin-C gene in rodents is due to unequal crossing-over events. The sequence divergence of noncoding DNA was used to estimate the frequency of unequal crossing-over events (6.3 x 10(-5) events per generation) in the Ubc gene, as well as to provide evidence of apparent selection in the poly-u gene.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Alexey S.</style></author><author><style face="normal" font="default" size="100%">Sunyaev, Shamil</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dobzhansky-Muller Incompatibilities in Protein Evolution</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Natl Acad Sci U S A</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">99</style></volume><pages><style face="normal" font="default" size="100%">14878-14883</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We study fitness landscape in the space of protein sequences by relating sets of human pathogenic missense mutations in 32 proteins to amino acid substitutions that occurred in the course of evolution of these proteins. On average, approximately 10% of deviations of a nonhuman protein from its human ortholog are compensated pathogenic deviations (CPDs), i.e., are caused by an amino acid substitution that, at this site, would be pathogenic to humans. Normal functioning of a CPD-containing protein must be caused by other, compensatory deviations of the nonhuman species from humans. Together, a CPD and the corresponding compensatory deviation form a Dobzhansky-Muller incompatibility that can be visualized as the corner on a fitness ridge. Thus, proteins evolve along fitness ridges which contain only approximately 10 steps between successive corners. The fraction of CPDs among all deviations of a protein from its human ortholog does not increase with the evolutionary distance between the proteins, indicating that substitutions that carry evolving proteins around these corners occur in rapid succession, driven by positive selection. Data on fitness of interspecies hybrids suggest that the compensatory change that makes a CPD fit usually occurs within the same protein. Data on protein structures and on cooccurrence of amino acids at different sites of multiple orthologous proteins often make it possible to provisionally identify the substitution that compensates a particular CPD.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castillo-Davis, Cristian I.</style></author><author><style face="normal" font="default" size="100%">Mekhedov, Sergei L.</style></author><author><style face="normal" font="default" size="100%">Hartl, Daniel L.</style></author><author><style face="normal" font="default" size="100%">Koonin, Eugene V.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selection for Short Introns in Highly Expressed Genes</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">415-418</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Transcription is a slow and expensive process: in eukaryotes, approximately 20 nucleotides can be transcribed per second at the expense of at least two ATP molecules per nucleotide. Thus, at least for highly expressed genes, transcription of long introns, which are particularly common in mammals, is costly. Using data on the expression of genes that encode proteins in Caenorhabditis elegans and Homo sapiens, we show that introns in highly expressed genes are substantially shorter than those in genes that are expressed at low levels. This difference is greater in humans, such that introns are, on average, 14 times shorter in highly expressed genes than in genes with low expression, whereas in C. elegans the difference in intron length is only twofold. In contrast, the density of introns in a gene does not strongly depend on the level of gene expression. Thus, natural selection appears to favor short introns in highly expressed genes to minimize the cost of transcription and other molecular processes, such as splicing.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Rogozin, Igor B.</style></author><author><style face="normal" font="default" size="100%">Wolf, Yuri I.</style></author><author><style face="normal" font="default" size="100%">Koonin, Eugene V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selection in the Evolution of gene Duplications</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">RESEARCH0008-RESEARCH0008</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Gene duplications have a major role in the evolution of new biological functions. Theoretical studies often assume that a duplication per se is selectively neutral and that, following a duplication, one of the gene copies is freed from purifying (stabilizing) selection, which creates the potential for evolution of a new function. RESULTS: In search of systematic evidence of accelerated evolution after duplication, we used data from 26 bacterial, six archaeal, and seven eukaryotic genomes to compare the mode and strength of selection acting on recently duplicated genes (paralogs) and on similarly diverged, unduplicated orthologous genes in different species. We find that the ratio of nonsynonymous to synonymous substitutions (Kn/Ks) in most paralogous pairs is &lt;1 and that paralogs typically evolve at similar rates, without significant asymmetry, indicating that both paralogs produced by a duplication are subject to purifying selection. This selection is, however, substantially weaker than the purifying selection affecting unduplicated orthologs that have diverged to the same extent as the analyzed paralogs. Most of the recently duplicated genes appear to be involved in various forms of environmental response; in particular, many of them encode membrane and secreted proteins. CONCLUSIONS: The results of this analysis indicate that recently duplicated paralogs evolve faster than orthologs with the same level of divergence and similar functions, but apparently do not experience a phase of neutral evolution. We hypothesize that gene duplications that persist in an evolving lineage are beneficial from the time of their origin, due primarily to a protein dosage effect in response to variable environmental conditions; duplications are likely to give rise to new functions at a later phase of their evolution once a higher level of divergence is reached.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dietmann, S.</style></author><author><style face="normal" font="default" size="100%">Park, J.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Heger, A.</style></author><author><style face="normal" font="default" size="100%">Lappe, M.</style></author><author><style face="normal" font="default" size="100%">Holm, L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A fully automatic evolutionary classification of protein folds: Dali Domain Dictionary version 3</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Motifs</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Factual</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structure, Tertiary</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins/chemistry/classification/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology, Amino Acid</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 1</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">55-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The Dali Domain Dictionary (http://www.ebi.ac.uk/dali/domain) is a numerical taxonomy of all known structures in the Protein Data Bank (PDB). The taxonomy is derived fully automatically from measurements of structural, functional and sequence similarities. Here, we report the extension of the classification to match the traditional four hierarchical levels corresponding to: (i) supersecondary structural motifs (attractors in fold space), (ii) the topology of globular domains (fold types), (iii) remote homologues (functional families) and (iv) homologues with sequence identity above 25% (sequence families). The computational definitions of attractors and functional families are new. In September 2000, the Dali classification contained 10 531 PDB entries comprising 17 101 chains, which were partitioned into five attractor regions, 1375 fold types, 2582 functional families and 3724 domain sequence families. Sequence families were further associated with 99 582 unique homologous sequences in the HSSP database, which increases the number of effectively known structures several-fold. The resulting database contains the description of protein domain architecture, the definition of structural neighbours around each known structure, the definition of structurally conserved cores and a comprehensive library of explicit multiple alignments of distantly related protein families.</style></abstract><accession-num><style face="normal" font="default" size="100%">11125048</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">Structural Genomics Group, EMBL-EBI, Cambridge CB10 1SD, UK.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Venter, JC.</style></author><author><style face="normal" font="default" size="100%">Adams, MD.</style></author><author><style face="normal" font="default" size="100%">Myers, EW.</style></author><author><style face="normal" font="default" size="100%">Li, PW.</style></author><author><style face="normal" font="default" size="100%">Mural, RJ.</style></author><author><style face="normal" font="default" size="100%">Sutton, GG.</style></author><author><style face="normal" font="default" size="100%">Smith, HO.</style></author><author><style face="normal" font="default" size="100%">Yandell, M.</style></author><author><style face="normal" font="default" size="100%">Evans, CA.</style></author><author><style face="normal" font="default" size="100%">Holt, RA.</style></author><author><style face="normal" font="default" size="100%">Gocayne, JD.</style></author><author><style face="normal" font="default" size="100%">Amanatides, P.</style></author><author><style face="normal" font="default" size="100%">Ballew, RM.</style></author><author><style face="normal" font="default" size="100%">Huson, DH.</style></author><author><style face="normal" font="default" size="100%">Wortman, JR.</style></author><author><style face="normal" font="default" size="100%">Zhang, Q.</style></author><author><style face="normal" font="default" size="100%">Kodira, CD.</style></author><author><style face="normal" font="default" size="100%">Zheng, XH.</style></author><author><style face="normal" font="default" size="100%">Chen, L.</style></author><author><style face="normal" font="default" size="100%">Skupski, M.</style></author><author><style face="normal" font="default" size="100%">Subramanian, G.</style></author><author><style face="normal" font="default" size="100%">Thomas, PD.</style></author><author><style face="normal" font="default" size="100%">Zhang, J.</style></author><author><style face="normal" font="default" size="100%">Gabor Miklos, GL.</style></author><author><style face="normal" font="default" size="100%">Nelson, C.</style></author><author><style face="normal" font="default" size="100%">Broder, S.</style></author><author><style face="normal" font="default" size="100%">Clark, AG.</style></author><author><style face="normal" font="default" size="100%">Nadeau, J.</style></author><author><style face="normal" font="default" size="100%">McKusick, VA.</style></author><author><style face="normal" font="default" size="100%">Zinder, N.</style></author><author><style face="normal" font="default" size="100%">Levine, AJ.</style></author><author><style face="normal" font="default" size="100%">Roberts, RJ.</style></author><author><style face="normal" font="default" size="100%">Simon, M.</style></author><author><style face="normal" font="default" size="100%">Slayman, C.</style></author><author><style face="normal" font="default" size="100%">Hunkapiller, M.</style></author><author><style face="normal" font="default" size="100%">Bolanos, R.</style></author><author><style face="normal" font="default" size="100%">Delcher, A.</style></author><author><style face="normal" font="default" size="100%">Dew, I.</style></author><author><style face="normal" font="default" size="100%">Fasulo, D.</style></author><author><style face="normal" font="default" size="100%">Flanigan, M.</style></author><author><style face="normal" font="default" size="100%">Florea, L.</style></author><author><style face="normal" font="default" size="100%">Halpern, A.</style></author><author><style face="normal" font="default" size="100%">Hannenhalli, S.</style></author><author><style face="normal" font="default" size="100%">Kravitz, S.</style></author><author><style face="normal" font="default" size="100%">Levy, S.</style></author><author><style face="normal" font="default" size="100%">Mobarry, C.</style></author><author><style face="normal" font="default" size="100%">Reinert, K.</style></author><author><style face="normal" font="default" size="100%">Remington, K.</style></author><author><style face="normal" font="default" size="100%">Abu-Threideh, J.</style></author><author><style face="normal" font="default" size="100%">Beasley, E.</style></author><author><style face="normal" font="default" size="100%">Biddick, K.</style></author><author><style face="normal" font="default" size="100%">Bonazzi, V.</style></author><author><style face="normal" font="default" size="100%">Brandon, R.</style></author><author><style face="normal" font="default" size="100%">Cargill, M.</style></author><author><style face="normal" font="default" size="100%">Chandramouliswaran, I.</style></author><author><style face="normal" font="default" size="100%">Charlab, R.</style></author><author><style face="normal" font="default" size="100%">Chaturvedi, K.</style></author><author><style face="normal" font="default" size="100%">Deng, Z.</style></author><author><style face="normal" font="default" size="100%">Di Francesco, V.</style></author><author><style face="normal" font="default" size="100%">Dunn, P.</style></author><author><style face="normal" font="default" size="100%">Eilbeck, K.</style></author><author><style face="normal" font="default" size="100%">Evangelista, C.</style></author><author><style face="normal" font="default" size="100%">Gabrielian, AE.</style></author><author><style face="normal" font="default" size="100%">Gan, W.</style></author><author><style face="normal" font="default" size="100%">Ge, W.</style></author><author><style face="normal" font="default" size="100%">Gong, F.</style></author><author><style face="normal" font="default" size="100%">Gu, Z.</style></author><author><style face="normal" font="default" size="100%">Guan, P.</style></author><author><style face="normal" font="default" size="100%">Heiman, TJ.</style></author><author><style face="normal" font="default" size="100%">Higgins, ME.</style></author><author><style face="normal" font="default" size="100%">Ji, RR.</style></author><author><style face="normal" font="default" size="100%">Ke, Z.</style></author><author><style face="normal" font="default" size="100%">Ketchum, KA.</style></author><author><style face="normal" font="default" size="100%">Lai, Z.</style></author><author><style face="normal" font="default" size="100%">Lei, Y.</style></author><author><style face="normal" font="default" size="100%">Li, Z.</style></author><author><style face="normal" font="default" size="100%">Li, J.</style></author><author><style face="normal" font="default" size="100%">Liang, Y.</style></author><author><style face="normal" font="default" size="100%">Lin, X.</style></author><author><style face="normal" font="default" size="100%">Lu, F.</style></author><author><style face="normal" font="default" size="100%">Merkulov, GV.</style></author><author><style face="normal" font="default" size="100%">Milshina, N.</style></author><author><style face="normal" font="default" size="100%">Moore, HM.</style></author><author><style face="normal" font="default" size="100%">Naik, AK.</style></author><author><style face="normal" font="default" size="100%">Narayan, VA.</style></author><author><style face="normal" font="default" size="100%">Neelam, B.</style></author><author><style face="normal" font="default" size="100%">Nusskern, D.</style></author><author><style face="normal" font="default" size="100%">Rusch, DB.</style></author><author><style face="normal" font="default" size="100%">Salzberg, S.</style></author><author><style face="normal" font="default" size="100%">Shao, W.</style></author><author><style face="normal" font="default" size="100%">Shue, B.</style></author><author><style face="normal" font="default" size="100%">Sun, J.</style></author><author><style face="normal" font="default" size="100%">Wang, Z.</style></author><author><style face="normal" font="default" size="100%">Wang, A.</style></author><author><style face="normal" font="default" size="100%">Wang, X.</style></author><author><style face="normal" font="default" size="100%">Wang, J.</style></author><author><style face="normal" font="default" size="100%">Wei, M.</style></author><author><style face="normal" font="default" size="100%">Wides, R.</style></author><author><style face="normal" font="default" size="100%">Xiao, C.</style></author><author><style face="normal" font="default" size="100%">Yan, C.</style></author><author><style face="normal" font="default" size="100%">Yao, A.</style></author><author><style face="normal" font="default" size="100%">Ye, J.</style></author><author><style face="normal" font="default" size="100%">Zhan, M.</style></author><author><style face="normal" font="default" size="100%">Zhang, W.</style></author><author><style face="normal" font="default" size="100%">Zhang, H.</style></author><author><style face="normal" font="default" size="100%">Zhao, Q.</style></author><author><style face="normal" font="default" size="100%">Zheng, L.</style></author><author><style face="normal" font="default" size="100%">Zhong, F.</style></author><author><style face="normal" font="default" size="100%">Zhong, W.</style></author><author><style face="normal" font="default" size="100%">Zhu, S.</style></author><author><style face="normal" font="default" size="100%">Zhao, S.</style></author><author><style face="normal" font="default" size="100%">Gilbert, D.</style></author><author><style face="normal" font="default" size="100%">Baumhueter, S.</style></author><author><style face="normal" font="default" size="100%">Spier, G.</style></author><author><style face="normal" font="default" size="100%">Carter, C.</style></author><author><style face="normal" font="default" size="100%">Cravchik, A.</style></author><author><style face="normal" font="default" size="100%">Woodage, T.</style></author><author><style face="normal" font="default" size="100%">Ali, F.</style></author><author><style face="normal" font="default" size="100%">An, H.</style></author><author><style face="normal" font="default" size="100%">Awe, A.</style></author><author><style face="normal" font="default" size="100%">Baldwin, D.</style></author><author><style face="normal" font="default" size="100%">Baden, H.</style></author><author><style face="normal" font="default" size="100%">Barnstead, M.</style></author><author><style face="normal" font="default" size="100%">Barrow, I.</style></author><author><style face="normal" font="default" size="100%">Beeson, K.</style></author><author><style face="normal" font="default" size="100%">Busam, D.</style></author><author><style face="normal" font="default" size="100%">Carver, A.</style></author><author><style face="normal" font="default" size="100%">Center, A.</style></author><author><style face="normal" font="default" size="100%">Cheng, ML.</style></author><author><style face="normal" font="default" size="100%">Curry, L.</style></author><author><style face="normal" font="default" size="100%">Danaher, S.</style></author><author><style face="normal" font="default" size="100%">Davenport, L.</style></author><author><style face="normal" font="default" size="100%">Desilets, R.</style></author><author><style face="normal" font="default" size="100%">Dietz, S.</style></author><author><style face="normal" font="default" size="100%">Dodson, K.</style></author><author><style face="normal" font="default" size="100%">Doup, L.</style></author><author><style face="normal" font="default" size="100%">Ferriera, S.</style></author><author><style face="normal" font="default" size="100%">Garg, N.</style></author><author><style face="normal" font="default" size="100%">Gluecksmann, A.</style></author><author><style face="normal" font="default" size="100%">Hart, B.</style></author><author><style face="normal" font="default" size="100%">Haynes, J.</style></author><author><style face="normal" font="default" size="100%">Haynes, C.</style></author><author><style face="normal" font="default" size="100%">Heiner, C.</style></author><author><style face="normal" font="default" size="100%">Hladun, S.</style></author><author><style face="normal" font="default" size="100%">Hostin, D.</style></author><author><style face="normal" font="default" size="100%">Houck, J.</style></author><author><style face="normal" font="default" size="100%">Howland, T.</style></author><author><style face="normal" font="default" size="100%">Ibegwam, C.</style></author><author><style face="normal" font="default" size="100%">Johnson, J.</style></author><author><style face="normal" font="default" size="100%">Kalush, F.</style></author><author><style face="normal" font="default" size="100%">Kline, L.</style></author><author><style face="normal" font="default" size="100%">Koduru, S.</style></author><author><style face="normal" font="default" size="100%">Love, A.</style></author><author><style face="normal" font="default" size="100%">Mann, F.</style></author><author><style face="normal" font="default" size="100%">May, D.</style></author><author><style face="normal" font="default" size="100%">McCawley, S.</style></author><author><style face="normal" font="default" size="100%">McIntosh, T.</style></author><author><style face="normal" font="default" size="100%">McMullen, I.</style></author><author><style face="normal" font="default" size="100%">Moy, M.</style></author><author><style face="normal" font="default" size="100%">Moy, L.</style></author><author><style face="normal" font="default" size="100%">Murphy, B.</style></author><author><style face="normal" font="default" size="100%">Nelson, K.</style></author><author><style face="normal" font="default" size="100%">Pfannkoch, C.</style></author><author><style face="normal" font="default" size="100%">Pratts, E.</style></author><author><style face="normal" font="default" size="100%">Puri, V.</style></author><author><style face="normal" font="default" size="100%">Qureshi, H.</style></author><author><style face="normal" font="default" size="100%">Reardon, M.</style></author><author><style face="normal" font="default" size="100%">Rodriguez, R.</style></author><author><style face="normal" font="default" size="100%">Rogers, YH.</style></author><author><style face="normal" font="default" size="100%">Romblad, D.</style></author><author><style face="normal" font="default" size="100%">Ruhfel, B.</style></author><author><style face="normal" font="default" size="100%">Scott, R.</style></author><author><style face="normal" font="default" size="100%">Sitter, C.</style></author><author><style face="normal" font="default" size="100%">Smallwood, M.</style></author><author><style face="normal" font="default" size="100%">Stewart, E.</style></author><author><style face="normal" font="default" size="100%">Strong, R.</style></author><author><style face="normal" font="default" size="100%">Suh, E.</style></author><author><style face="normal" font="default" size="100%">Thomas, R.</style></author><author><style face="normal" font="default" size="100%">Tint, NN.</style></author><author><style face="normal" font="default" size="100%">Tse, S.</style></author><author><style face="normal" font="default" size="100%">Vech, C.</style></author><author><style face="normal" font="default" size="100%">Wang, G.</style></author><author><style face="normal" font="default" size="100%">Wetter, J.</style></author><author><style face="normal" font="default" size="100%">Williams, S.</style></author><author><style face="normal" font="default" size="100%">Williams, M.</style></author><author><style face="normal" font="default" size="100%">Windsor, S.</style></author><author><style face="normal" font="default" size="100%">Winn-Deen, E.</style></author><author><style face="normal" font="default" size="100%">Wolfe, K.</style></author><author><style face="normal" font="default" size="100%">Zaveri, J.</style></author><author><style face="normal" font="default" size="100%">Zaveri, K.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Campbell, MJ.</style></author><author><style face="normal" font="default" size="100%">Sjolander, KV.</style></author><author><style face="normal" font="default" size="100%">Karlak, B.</style></author><author><style face="normal" font="default" size="100%">Kejariwal, A.</style></author><author><style face="normal" font="default" size="100%">Mi, H.</style></author><author><style face="normal" font="default" size="100%">Lazareva, B.</style></author><author><style face="normal" font="default" size="100%">Hatton, T.</style></author><author><style face="normal" font="default" size="100%">Narechania, A.</style></author><author><style face="normal" font="default" size="100%">Diemer, K.</style></author><author><style face="normal" font="default" size="100%">Muruganujan, A.</style></author><author><style face="normal" font="default" size="100%">Guo, N.</style></author><author><style face="normal" font="default" size="100%">Sato, S.</style></author><author><style face="normal" font="default" size="100%">Bafna, V.</style></author><author><style face="normal" font="default" size="100%">Istrail, S.</style></author><author><style face="normal" font="default" size="100%">Lippert, R.</style></author><author><style face="normal" font="default" size="100%">Schwartz, R.</style></author><author><style face="normal" font="default" size="100%">Walenz, B.</style></author><author><style face="normal" font="default" size="100%">Yooseph, S.</style></author><author><style face="normal" font="default" size="100%">Allen, D.</style></author><author><style face="normal" font="default" size="100%">Basu, A.</style></author><author><style face="normal" font="default" size="100%">Baxendale, J.</style></author><author><style face="normal" font="default" size="100%">Blick, L.</style></author><author><style face="normal" font="default" size="100%">Caminha, M.</style></author><author><style face="normal" font="default" size="100%">Carnes-Stine, J.</style></author><author><style face="normal" font="default" size="100%">Caulk, P.</style></author><author><style face="normal" font="default" size="100%">Chiang, YH.</style></author><author><style face="normal" font="default" size="100%">Coyne, M.</style></author><author><style face="normal" font="default" size="100%">Dahlke, C.</style></author><author><style face="normal" font="default" size="100%">Mays, A.</style></author><author><style face="normal" font="default" size="100%">Dombroski, M.</style></author><author><style face="normal" font="default" size="100%">Donnelly, M.</style></author><author><style face="normal" font="default" size="100%">Ely, D.</style></author><author><style face="normal" font="default" size="100%">Esparham, S.</style></author><author><style face="normal" font="default" size="100%">Fosler, C.</style></author><author><style face="normal" font="default" size="100%">Gire, H.</style></author><author><style face="normal" font="default" size="100%">Glanowski, S.</style></author><author><style face="normal" font="default" size="100%">Glasser, K.</style></author><author><style face="normal" font="default" size="100%">Glodek, A.</style></author><author><style face="normal" font="default" size="100%">Gorokhov, M.</style></author><author><style face="normal" font="default" size="100%">Graham, K.</style></author><author><style face="normal" font="default" size="100%">Gropman, B.</style></author><author><style face="normal" font="default" size="100%">Harris, M.</style></author><author><style face="normal" font="default" size="100%">Heil, J.</style></author><author><style face="normal" font="default" size="100%">Henderson, S.</style></author><author><style face="normal" font="default" size="100%">Hoover, J.</style></author><author><style face="normal" font="default" size="100%">Jennings, D.</style></author><author><style face="normal" font="default" size="100%">Jordan, C.</style></author><author><style face="normal" font="default" size="100%">Jordan, J.</style></author><author><style face="normal" font="default" size="100%">Kasha, J.</style></author><author><style face="normal" font="default" size="100%">Kagan, L.</style></author><author><style face="normal" font="default" size="100%">Kraft, C.</style></author><author><style face="normal" font="default" size="100%">Levitsky, A.</style></author><author><style face="normal" font="default" size="100%">Lewis, M.</style></author><author><style face="normal" font="default" size="100%">Liu, X.</style></author><author><style face="normal" font="default" size="100%">Lopez, J.</style></author><author><style face="normal" font="default" size="100%">Ma, D.</style></author><author><style face="normal" font="default" size="100%">Majoros, W.</style></author><author><style face="normal" font="default" size="100%">McDaniel, J.</style></author><author><style face="normal" font="default" size="100%">Murphy, S.</style></author><author><style face="normal" font="default" size="100%">Newman, M.</style></author><author><style face="normal" font="default" size="100%">Nguyen, T.</style></author><author><style face="normal" font="default" size="100%">Nguyen, N.</style></author><author><style face="normal" font="default" size="100%">Nodell, M.</style></author><author><style face="normal" font="default" size="100%">Pan, S.</style></author><author><style face="normal" font="default" size="100%">Peck, J.</style></author><author><style face="normal" font="default" size="100%">Peterson, M.</style></author><author><style face="normal" font="default" size="100%">Rowe, W.</style></author><author><style face="normal" font="default" size="100%">Sanders, R.</style></author><author><style face="normal" font="default" size="100%">Scott, J.</style></author><author><style face="normal" font="default" size="100%">Simpson, M.</style></author><author><style face="normal" font="default" size="100%">Smith, T.</style></author><author><style face="normal" font="default" size="100%">Sprague, A.</style></author><author><style face="normal" font="default" size="100%">Stockwell, T.</style></author><author><style face="normal" font="default" size="100%">Turner, R.</style></author><author><style face="normal" font="default" size="100%">Venter, E.</style></author><author><style face="normal" font="default" size="100%">Wang, M.</style></author><author><style face="normal" font="default" size="100%">Wen, M.</style></author><author><style face="normal" font="default" size="100%">Wu, D.</style></author><author><style face="normal" font="default" size="100%">Wu, M.</style></author><author><style face="normal" font="default" size="100%">Xia, A.</style></author><author><style face="normal" font="default" size="100%">Zandieh, A.</style></author><author><style face="normal" font="default" size="100%">Zhu, X.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The sequence of the human genome.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/291/5507/130</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5507</style></number><volume><style face="normal" font="default" size="100%">291</style></volume><pages><style face="normal" font="default" size="100%">1304–1351</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies-a whole-genome assembly and a regional chromosome assembly-were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional approximately 12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mocca: semi-automatic method for domain hunting</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Automation</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Factual</style></keyword><keyword><style  face="normal" font="default" size="100%">Information Storage and Retrieval</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structure, Tertiary</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins/ analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">373-4</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: Multiple OCCurrences Analysis (Mocca) is a new method for repeat extraction. It is based on the T-Coffee package (Notredame et al., JMB, 302, 205-217, 2000). Given a sequence or a set of sequences, and a library of local alignments, Mocca extracts every segment of sequence homologous to a pre-specified master. The implementation is meant for domain hunting and makes it fast and easy to test for new boundaries or extend known repeats in an interactive manner. Mocca is designed to deal with highly divergent protein repeats (less than 30% amino acid identity) of more than 30 amino acids.</style></abstract><accession-num><style face="normal" font="default" size="100%">11301309</style></accession-num><notes><style face="normal" font="default" size="100%">Journal Article</style></notes><auth-address><style face="normal" font="default" size="100%">Information Genetique et Structurale, CNRS-UMR 1889, 31 Ch. Joseph Aiguier, 13 402 Marseille, France.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rogozin, I.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Glazko, G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Use of Mutation Spectra Analysis Software</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">83-8102</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The study and comparison of mutation(al) spectra is an important problem in molecular biology, because these spectra often reflect on important features of mutations and their fixation. Such features include the interaction of DNA with various mutagens, the function of repair/replication enzymes, and properties of target proteins. It is known that mutability varies significantly along nucleotide sequences, such that mutations often concentrate at certain positions, called ``hotspots,'' in a sequence. In this paper, we discuss in detail two approaches for mutation spectra analysis: the comparison of mutation spectra with a HG-PUBL program, (FTP: sunsite.unc.edu/pub/academic/biology/dna-mutations/hyperg) and hotspot prediction with the CLUSTERM program (www.itba.mi.cnr.it/webmutation; ftp.bionet.nsc.ru/pub/biology/dbms/clusterm.zip). Several other approaches for mutational spectra analysis, such as the analysis of a target protein structure, hotspot context revealing, multiple spectra comparisons, as well as a number of mutation databases are briefly described. Mutation spectra in the lacI gene of E. coli and the human p53 gene are used for illustration of various difficulties of such analysis.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rogozin, I. B.</style></author><author><style face="normal" font="default" size="100%">Kochetov, A. V.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Koonin, E. V.</style></author><author><style face="normal" font="default" size="100%">Milanesi, L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Presence of ATG Triplets in 5' Untranslated Regions of Eukaryotic cDNAs Correlates with a 'weak' Context of the Start Codon</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">890-900</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: The context of the start codon (typically, AUG) and the features of the 5' Untranslated Regions (5' UTRs) are important for understanding translation regulation in eukaryotic mRNAs and for accurate prediction of the coding region in genomic and cDNA sequences. The presence of AUG triplets in 5' UTRs (upstream AUGs) might effect the initiation rate and, in the context of gene prediction, could reduce the accuracy of the identification of the authentic start. To reveal potential connections between the presence of upstream AUGs and other features of 5' UTRs, such as their length and the start codon context, we undertook a systematic analysis of the available eukaryotic 5' UTR sequences. RESULTS: We show that a large fraction of 5' UTRs in the available cDNA sequences, 15-53% depending on the organism, contain upstream ATGs. A negative correlation was observed between the information content of the translation start signal and the length of the 5' UTR. Similarly, a negative correlation exists between the 'strength' of the start context and the number of upstream ATGs. Typically, cDNAs containing long 5' UTRs with multiple upstream ATGs have a 'weak' start context, and in contrast, cDNAs containing short 5' UTRs without ATGs have 'strong' starts. These counter-intuitive results may be interpreted in terms of upstream AUGs having an important role in the regulation of translation efficiency by ensuring low basal translation level via double negative control and creating the potential for additional regulatory mechanisms. One of such mechanisms, supported by experimental studies of some mRNAs, includes removal of the AUG-containing portion of the 5' UTR by alternative splicing. AVAILABILITY: An ATG_ EVALUATOR program is available upon request or at www.itba.mi.cnr.it/webgene. CONTACT: rogozin@ncbi.nlm.nih.gov, milanesi@itba.mi.cnr.it.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, A. S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multidimensional Epistasis and the Disadvantage of sex</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Natl Acad Sci U S A</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><volume><style face="normal" font="default" size="100%">98</style></volume><pages><style face="normal" font="default" size="100%">12089-12092</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Sex is thought to facilitate accumulation of initially rare beneficial mutations by allowing simultaneous allele replacements at many loci. However, this advantage of sex depends on a restrictive assumption that the fitness of a genotype is determined by fitness potential, a single intermediate variable to which all loci contribute additively, so that new alleles can accumulate in any order. Individual-based simulations of sexual and asexual populations reveal that under generic selection, sex often retards adaptive evolution. When new alleles are beneficial only if they accumulate in a prescribed order, a sexual population may evolve two or more times slower than an asexual population because only asexual reproduction allows some overlap of successive allele replacements. Many other fitness surfaces lead to an even greater disadvantage of sex. Thus, either sex exists in spite of its impact on the rate of adaptive allele replacements, or natural fitness surfaces have rather specific properties, at least at the scale of intrapopulation genetic variability.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wolf, Y. I.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Koonin, E. V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Footprints of Primordial Introns on the Eukaryotic Genome: Still no Clear Traces</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">499-501</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><custom7><style face="normal" font="default" size="100%">unique</style></custom7></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Koonin, E. V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Origin of Alternative Splicing by Tandem exon Duplication</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">2661-2669</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Genes with new functions often evolve by gene duplication. Alternative splicing is another means of evolutionary innovation in eukaryotes, which allows a single gene to encode functionally diverse proteins. We investigate a connection between these two evolutionary phenomena. For approximately 10% of the described cases of substitution alternative splicing, such that either one or another amino acid sequence is included into the protein, evidence of origin by tandem exon duplication was found. This is a conservative estimate because alternative exons are typically short and, on many occasions, duplicates may have diverged beyond recognition. Dating exon duplications through a combination of the available experimental data on alternative splicing in orthologous genes from different species and computational analysis indicates that most of the duplications antedate at least the radiation of mammalian orders or even the radiation of vertebrate classes. At present, tandem exon duplication is the only mechanism of evolution of substitution alternative splicing that can be specifically demonstrated. Along with gene duplication, this could be a major route for generating functional diversity during evolution of multicellular eukaryotes.</style></abstract><custom7><style face="normal" font="default" size="100%">unique</style></custom7></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jordan, IK.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Rogozin, IB.</style></author><author><style face="normal" font="default" size="100%">Tatusov, RL.</style></author><author><style face="normal" font="default" size="100%">Wolf, YI.</style></author><author><style face="normal" font="default" size="100%">Koonin, EV.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Constant relative rate of protein evolution and detection of functional diversification among bacterial, archaeal and eukaryotic proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/11790256</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">RESEARCH0053</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Detection of changes in a protein's evolutionary rate may reveal cases of change in that protein's function. We developed and implemented a simple relative rates test in an attempt to assess the rate constancy of protein evolution and to detect cases of functional diversification between orthologous proteins. The test was performed on clusters of orthologous protein sequences from complete bacterial genomes (Chlamydia trachomatis, C. muridarum and Chlamydophila pneumoniae), complete archaeal genomes (Pyrococcus horikoshii, P. abyssi and P. furiosus) and partially sequenced mammalian genomes (human, mouse and rat). RESULTS: Amino-acid sequence evolution rates are significantly correlated on different branches of phylogenetic trees representing the great majority of analyzed orthologous protein sets from all three domains of life. However, approximately 1% of the proteins from each group of species deviates from this pattern and instead shows variation that is consistent with an acceleration of the rate of amino-acid substitution, which may be due to functional diversification. Most of the putative functionally diversified proteins from all three species groups are predicted to function at the periphery of the cells and mediate their interaction with the environment. CONCLUSIONS: Relative rates of protein evolution are remarkably constant for the three species groups analyzed here. Deviations from this rate constancy are probably due to changes in selective constraints associated with diversification between orthologs. Functional diversification between orthologs is thought to be a relatively rare event. However, the resolution afforded by the test designed specifically for genomic-scale datasets allowed us to identify numerous cases of possible functional diversification between orthologous proteins.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author><author><style face="normal" font="default" size="100%">Heringa, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">T-Coffee: A novel method for fast and accurate multiple sequence alignment</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Motifs</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein-Serine-Threonine Kinases/chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Sensitivity and Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology, Amino Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep 8</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">302</style></volume><pages><style face="normal" font="default" size="100%">205-17</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe a new method (T-Coffee) for multiple sequence alignment that provides a dramatic improvement in accuracy with a modest sacrifice in speed as compared to the most commonly used alternatives. The method is broadly based on the popular progressive approach to multiple alignment but avoids the most serious pitfalls caused by the greedy nature of this algorithm. With T-Coffee we pre-process a data set of all pair-wise alignments between the sequences. This provides us with a library of alignment information that can be used to guide the progressive alignment. Intermediate alignments are then based not only on the sequences to be aligned next but also on how all of the sequences align with each other. This alignment information can be derived from heterogeneous sources such as a mixture of alignment programs and/or structure superposition. Here, we illustrate the power of the approach by using a combination of local and global pair-wise alignments to generate the library. The resulting alignments are significantly more reliable, as determined by comparison with a set of 141 test cases, than any of the popular alternatives that we tried. The improvement, especially clear with the more difficult test cases, is always visible, regardless of the phylogenetic spread of the sequences in the tests.</style></abstract><accession-num><style face="normal" font="default" size="100%">10964570</style></accession-num><notes><style face="normal" font="default" size="100%">Journal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">National Institute for Medical Research, The Ridgeway, London, NW7 1AA, UK. cedric.notredame@europe.com</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Agarwal, P.</style></author><author><style face="normal" font="default" size="100%">Abril, JF.</style></author><author><style face="normal" font="default" size="100%">Burset, M.</style></author><author><style face="normal" font="default" size="100%">Fickett, JW.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An assessment of gene prediction accuracy in large DNA sequences.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/1104216</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">1631–1642</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wolf, Y. I.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author><author><style face="normal" font="default" size="100%">Koonin, E. V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">No Footprints of Primordial Introns in a Eukaryotic Genome</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Genet</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">333-334</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kondrashov, A. S.</style></author><author><style face="normal" font="default" size="100%">Kondrashov, Fyodor A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interactions Among Quantitative Traits in the Course of Sympatric Speciation</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><volume><style face="normal" font="default" size="100%">400</style></volume><pages><style face="normal" font="default" size="100%">351-354</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Sympatric speciation, the origin of two or more species from a single local population, has almost certainly been involved in formation of several species flocks, and may be fairly common in nature. The most straightforward scenario for sympatric speciation requires disruptive selection favouring two substantially different phenotypes, and consists of the evolution of reproductive isolation between them followed by the elimination of all intermediate phenotypes. Here we use the hypergeometric phenotypic model to show that sympatric speciation is possible even when fitness and mate choice depend on different quantitative traits, so that speciation must involve formation of covariance between these traits. The increase in the number of variable loci affecting fitness facilitates sympatric speciation, whereas the increase in the number of variable loci affecting mate choice has the opposite effect. These predictions may enable more cases of sympatric speciation to be identified.</style></abstract><custom7><style face="normal" font="default" size="100%">unique</style></custom7></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Holm, L.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">COFFEE: an objective function for multiple sequence alignments</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Factual</style></keyword><keyword><style  face="normal" font="default" size="100%">Evaluation Studies as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Fibronectins/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods/statistics &amp; numerical data</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology, Amino Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1998</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">407-22</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: In order to increase the accuracy of multiple sequence alignments, we designed a new strategy for optimizing multiple sequence alignments by genetic algorithm. We named it COFFEE (Consistency based Objective Function For alignmEnt Evaluation). The COFFEE score reflects the level of consistency between a multiple sequence alignment and a library containing pairwise alignments of the same sequences. RESULTS: We show that multiple sequence alignments can be optimized for their COFFEE score with the genetic algorithm package SAGA. The COFFEE function is tested on 11 test cases made of structural alignments extracted from 3D_ali. These alignments are compared to those produced using five alternative methods. Results indicate that COFFEE outperforms the other methods when the level of identity between the sequences is low. Accuracy is evaluated by comparison with the structural alignments used as references. We also show that the COFFEE score can be used as a reliability index on multiple sequence alignments. Finally, we show that given a library of structure-based pairwise sequence alignments extracted from FSSP, SAGA can produce high-quality multiple sequence alignments. The main advantage of COFFEE is its flexibility. With COFFEE, any method suitable for making pairwise alignments can be extended to making multiple alignments. AVAILABILITY: The package is available along with the test cases through the WWW: http://www. ebi.ac.uk/cedric CONTACT: cedric.notredame@ebi.ac.uk</style></abstract><accession-num><style face="normal" font="default" size="100%">9682054</style></accession-num><notes><style face="normal" font="default" size="100%">Comparative StudyJournal Article</style></notes><auth-address><style face="normal" font="default" size="100%">EMBL Outstation-The European Bioinformatics Institute, Hinxton Hall, Hinxton, Cambridge CB10 1SD, UK.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">O'Brien, E. A.</style></author><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimization of ribosomal RNA profile alignments</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structure, Secondary</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Ribosomal/ chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">332-41</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: Large alignments of ribosomal RNA sequences are maintained at various sites. New sequences are added to these alignments using a combination of manual and automatic methods. We examine the use of profile alignment methods for rRNA alignment and try to optimize the choice of parameters and sequence weights. RESULTS: Using a large alignment of eukaryotic SSU rRNA sequences as a test case, we empirically compared the performance of various sequence weighting schemes over a range of gap penalties. We developed a new weighting scheme which gives most weight to the sequences in the profile that are most similar to the new sequence. We show that it gives the most accurate alignments when combined with a more traditional sequence weighting scheme. AVAILABILITY: The source code of all software is freely available by anonymous ftp from chah.ucc.ie in the directory /home/ftp/pub/emmet,in the compressed file PRNAA.tar: CONTACT: emmet@chah.ucc.ie, des@chah.ucc.ie</style></abstract><accession-num><style face="normal" font="default" size="100%">9632828</style></accession-num><notes><style face="normal" font="default" size="100%">Comparative StudyJournal Article</style></notes><auth-address><style face="normal" font="default" size="100%">Department of Biochemistry, University College, Cork, Ireland and EMBL-European Bioinformatics Institute, Hinxton, Cambridge CB10 1RQ, UK. emmet@chah.ucc.ie</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">O'Brien, E. A.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">RAGA: RNA sequence alignment by genetic algorithm</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Evaluation Studies as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Nucleic Acid Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Ribosomal/ genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA/ genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment/ methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1997</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov 15</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">22</style></number><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">4570-80</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe a new approach for accurately aligning two homologous RNA sequences when the secondary structure of one of them is known. To do so we developed two software packages, called RAGA and PRAGA, which use a genetic algorithm approach to optimize the alignments. RAGA is mainly an extension of SAGA, an earlier package for multiple protein sequence alignment. In PRAGA several genetic algorithms run in parallel and exchange individual solutions. This method allows us to optimize an objective function that describes the quality of a RNA pairwise alignment, taking into account both primary and secondary structure, including pseudoknots. We report results obtained using PRAGA on nine test cases of pairs of eukaryotic small subunit rRNA sequence (nuclear and mitochondrial).</style></abstract><accession-num><style face="normal" font="default" size="100%">9358168</style></accession-num><notes><style face="normal" font="default" size="100%">Comparative StudyJournal ArticleResearch Support, Non-U.S. Gov't</style></notes><auth-address><style face="normal" font="default" size="100%">EMBL Outstation-The European Bioinformatics Institute, Welcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. cedric.notredame@ebi.ac.uk</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Falaschi, PA.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Human molecular genetics research at the International Centre for Genetic Engineering and Biotechnology.</style></title><secondary-title><style face="normal" font="default" size="100%">Southeast Asian J. Trop. Med. Public Health</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/9561632</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">28 Suppl 2</style></volume><pages><style face="normal" font="default" size="100%">14–18</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The ICGEB started its activity in 1987 as a special project of UNIDO (United Nations Industrial Development Organization) and operates now as a fully autonomous International Organization, of which 40 countries are members at present. The mandate of ICGEB is to become a Centre of excellence for research and training in modern biology addressed to the needs of the developing world. The ICGEB consists of two main laboratories, one in Trieste (where the direction of the Centre is also located) and one in New Delhi, plus a network of 30 Affiliated Centres. The Centre operates through: 1) specific research programs of hish scientific content at the Trieste and New Delhi laboratories; 2) long term training through post-doctoral and pre-doctoral fellowships; 3) short term training; 4) collaborative research program, through which the Centre finances research projects of major impact to the need of the Member States; 5) scientific services, namely consultation for scientific programs, distribution of reagents and a bioinformatics network particularly geared to the human genome research. The research on human molecular genetics in particularly active in the Trieste Component and concerns the study at the molecular level of several genes important for human health: control of DNA replication, response to infectious diseases, cardiocirculatory diseases, cystic fibrosis and cancer. The methodologies for developing new diagnostic methods and for developing gene therapy protocols are actively pursued. Through these programs, the member countries have access to state-of-the-art technologies anf know-how essential for the development of the molecular approaches to medicine brought forward by the study of the human genome.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Burset, M.</style></author><author><style face="normal" font="default" size="100%">Guigó, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluation of gene structure prediction programs.</style></title><secondary-title><style face="normal" font="default" size="100%">Genomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1996</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jun</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1006/geno.1996.029</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">353–367</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We evaluate a number of computer programs designed to predict the structure of protein coding genes in genomic DNA sequences. Computational gene identification is set to play an increasingly important role in the development of the genome projects, as emphasis turns from mapping to large-scale sequencing. The evaluation presented here serves both to assess the current status of the problem and to identify the most promising approaches to ensure further progress. The programs analyzed were uniformly tested on a large set of vertebrate sequences with simple gene structure, and several measures of predictive accuracy were computed at the nucleotide, exon, and protein product levels. The results indicated that the predictive accuracy of the programs analyzed was lower than originally found. The accuracy was even lower when considering only those sequences that had recently been entered and that did not show any similarity to previously entered sequences. This indicates that the programs are overly dependent on the particularities of the examples they learn from. For most of the programs, accuracy in this test set ranged from 0.60 to 0.70 as measured by the Correlation Coefficient (where 1.0 corresponds to a perfect prediction and 0.0 is the value expected for a random prediction), and the average percentage of exons exactly identified was less than 50%. Only those programs including protein sequence database searches showed substantially greater accuracy. The accuracy of the programs was severely affected by relatively high rates of sequence errors. Since the set on which the programs were tested included only relatively short sequences with simple gene structure, the accuracy of the programs is likely to be even lower when used for large uncharacterized genomic sequences with complex structure. While in such cases, programs currently available may still be of great use in pinpointing the regions likely to contain exons, they are far from being powerful enough to elucidate its genomic structure completely.</style></abstract></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Notredame, C.</style></author><author><style face="normal" font="default" size="100%">Higgins, D. G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SAGA: sequence alignment by genetic algorithm</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1996</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Apr 15</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">1515-24</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe a new approach to multiple sequence alignment using genetic algorithms and an associated software package called SAGA. The method involves evolving a population of alignments in a quasi evolutionary manner and gradually improving the fitness of the population as measured by an objective function which measures multiple alignment quality. SAGA uses an automatic scheduling scheme to control the usage of 22 different operators for combining alignments or mutating them between generations. When used to optimise the well known sums of pairs objective function, SAGA performs better than some of the widely used alternative packages. This is seen with respect to the ability to achieve an optimal solution and with regard to the accuracy of alignment by comparison with reference alignments based on sequences of known tertiary structure. The general attraction of the approach is the ability to optimise any objective function that one can invent.</style></abstract><accession-num><style face="normal" font="default" size="100%">8628686</style></accession-num><notes><style face="normal" font="default" size="100%">Journal Article</style></notes><auth-address><style face="normal" font="default" size="100%">EMBL outstation, The European Bioinformatics Institute, Cambridge, UK.</style></auth-address></record><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Guigó, R.</style></author><author><style face="normal" font="default" size="100%">Knudsen, S.</style></author><author><style face="normal" font="default" size="100%">Drake, N.</style></author><author><style face="normal" font="default" size="100%">Smith, T.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of gene structure.</style></title><secondary-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1992</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jul</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/161964</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">226</style></volume><pages><style face="normal" font="default" size="100%">141–157</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We have developed a hierarchical rule base system for identifying genes in DNA sequences. Atomic sites (such as initiation codons, stop codons, acceptor sites and donor sites) are identified by a number of different methods and evaluated by a set of filters and rules chosen to maximize sensitivity; these are combined into higher-order gene elements (such as exons), evaluated, filtered and combined as equivalence classes into probable genes, which are evaluated and ranked. The system has been tested on an extensive collection of vertebrate genes smaller than 15,000 bases. Results obtained show that, on average, 88% of the predicted coding region for a transcription unit is actually coding, and 80% of the actual coding is correctly predicted. This will, in most applications, be sufficient for a search against protein sequence databases for the identification of probable gene function. In addition, the system provides a general test platform for both gene atomic site identification and the rules for their evaluation and assembly.</style></abstract></record></records></xml>
