<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lavagnino, Nicolás</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Arbiza, Leonardo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Hasson, Esteban</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolutionary Genomics of Genes Involved in Olfactory Behavior in the Drosophila melanogaster Species Group.</style></title><secondary-title><style face="normal" font="default" size="100%">Evolutionary bioinformatics online</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%">2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3273929/?tool=pubmed</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">89-104</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Previous comparative genomic studies of genes involved in olfactory behavior in Drosophila focused only on particular gene families such as odorant receptor and/or odorant binding proteins. However, olfactory behavior has a complex genetic architecture that is orchestrated by many interacting genes. In this paper, we present a comparative genomic study of olfactory behavior in Drosophila including an extended set of genes known to affect olfactory behavior. We took advantage of the recent burst of whole genome sequences and the development of powerful statistical tools to analyze genomic data and test evolutionary and functional hypotheses of olfactory genes in the six species of the Drosophila melanogaster species group for which whole genome sequences are available. Our study reveals widespread purifying selection and limited incidence of positive selection on olfactory genes. We show that the pace of evolution of olfactory genes is mostly independent of the life cycle stage, and of the number of life cycle stages, in which they participate in olfaction. However, we detected a relationship between evolutionary rates and the position that the gene products occupy in the olfactory system, genes occupying central positions tend to be more constrained than peripheral genes. Finally, we demonstrate that specialization to one host does not seem to be associated with bursts of adaptive evolution in olfactory genes in D. sechellia and D. erecta, the two specialists species analyzed, but rather different lineages have idiosyncratic evolutionary histories in which both historical and ecological factors have been involved.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Negredo, Ana</style></author><author><style face="normal" font="default" size="100%">Palacios, Gustavo</style></author><author><style face="normal" font="default" size="100%">Vázquez-Morón, Sonia</style></author><author><style face="normal" font="default" size="100%">González, Félix</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Molero, Francisca</style></author><author><style face="normal" font="default" size="100%">Juste, Javier</style></author><author><style face="normal" font="default" size="100%">Quetglas, Juan</style></author><author><style face="normal" font="default" size="100%">Savji, Nazir</style></author><author><style face="normal" font="default" size="100%">de la Cruz Martínez, Maria</style></author><author><style face="normal" font="default" size="100%">Herrera, Jesus Enrique</style></author><author><style face="normal" font="default" size="100%">Pizarro, Manuel</style></author><author><style face="normal" font="default" size="100%">Hutchison, Stephen K</style></author><author><style face="normal" font="default" size="100%">Echevarría, Juan E</style></author><author><style face="normal" font="default" size="100%">Lipkin, W Ian</style></author><author><style face="normal" font="default" size="100%">Tenorio, Antonio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discovery of an ebolavirus-like filovirus in europe.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS pathogens</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%">2011 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e1002304</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Filoviruses, amongst the most lethal of primate pathogens, have only been reported as natural infections in sub-Saharan Africa and the Philippines. Infections of bats with the ebolaviruses and marburgviruses do not appear to be associated with disease. Here we report identification in dead insectivorous bats of a genetically distinct filovirus, provisionally named Lloviu virus, after the site of detection, Cueva del Lloviu, in Spain.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gonçalves, Luís G</style></author><author><style face="normal" font="default" size="100%">Borges, Nuno</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Fernandes, Pedro L</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Santos, Helena</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of the biosynthesis of di-myo-inositol phosphate, a marker of adaptation to hot marine environments.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental microbiology</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%">2011 Oct 26</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The synthesis of di-myo-inositol phosphate (DIP), a common compatible solute in hyperthermophiles, involves the consecutive actions of inositol-1-phosphate cytidylyltransferase (IPCT) and di-myo-inositol phosphate phosphate synthase (DIPPS). In most cases, both activities are present in a single gene product, but separate genes are also found in a few organisms. Genes for IPCT and DIPPS were found in the genomes of 33 organisms, all with thermophilic/hyperthermophilic lifestyles. Phylogeny of IPCT/DIPPS revealed an incongruent topology with 16S RNA phylogeny, thus suggesting horizontal gene transfer. The phylogenetic tree of the DIPPS domain was rooted by using phosphatidylinositol phosphate synthase sequences as out-group. The root locates at the separation of genomes with fused and split genes. We propose that the gene encoding DIPPS was recruited from the biosynthesis of phosphatidylinositol. The last DIP-synthesizing ancestor harboured separated genes for IPCT and DIPPS and this architecture was maintained in a crenarchaeal lineage, and transferred by horizontal gene transfer to hyperthermophilic marine Thermotoga species. It is plausible that the driving force for the assembly of those two genes in the early ancestor is related to the acquired advantage of DIP producers to cope with high temperature. This work corroborates the view that Archaea were the first hyperthermophilic organisms.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arbiza, Leonardo</style></author><author><style face="normal" font="default" size="100%">Patricio, Mateus</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Posada, David</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide heterogeneity of nucleotide substitution model fit.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome 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%">2011</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">896-908</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Arbiza, Leonardo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Natural selection on functional modules, a genome-wide analysis.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS Comput Biol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Drosophila</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Insect</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Mammals</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Selection, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e1001093</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Classically, the functional consequences of natural selection over genomes have been analyzed as the compound effects of individual genes. The current paradigm for large-scale analysis of adaptation is based on the observed significant deviations of rates of individual genes from neutral evolutionary expectation. This approach, which assumed independence among genes, has not been able to identify biological functions significantly enriched in positively selected genes in individual species. Alternatively, pooling related species has enhanced the search for signatures of selection. However, grouping signatures does not allow testing for adaptive differences between species. Here we introduce the Gene-Set Selection Analysis (GSSA), a new genome-wide approach to test for evidences of natural selection on functional modules. GSSA is able to detect lineage specific evolutionary rate changes in a notable number of functional modules. For example, in nine mammal and Drosophilae genomes GSSA identifies hundreds of functional modules with significant associations to high and low rates of evolution. Many of the detected functional modules with high evolutionary rates have been previously identified as biological functions under positive selection. Notably, GSSA identifies conserved functional modules with many positively selected genes, which questions whether they are exclusively selected for fitting genomes to environmental changes. Our results agree with previous studies suggesting that adaptation requires positive selection, but not every mutation under positive selection contributes to the adaptive dynamical process of the evolution of species.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/21390268?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sánchez, Rubén</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Tárraga, Joaquín</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Carbonell, José</style></author><author><style face="normal" font="default" size="100%">Pulido, Luis</style></author><author><style face="normal" font="default" size="100%">De Maria, Alejandro</style></author><author><style face="normal" font="default" size="100%">Capella-Gutíerrez, Salvador</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, Jaime</style></author><author><style face="normal" font="default" size="100%">Gabaldón, Toni</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</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><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</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</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">W470-4</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">Web Server issue</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/21646336?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cardona, Fernando</style></author><author><style face="normal" font="default" size="100%">Sánchez-Mut, Jose Vicente</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Pérez-Tur, Jordi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phylogenetic and in silico structural analysis of the Parkinson disease-related kinase PINK1.</style></title><secondary-title><style face="normal" font="default" size="100%">Human mutation</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%">2011 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">369-78</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Parkinson disease (PD) is the second most common neurodegenerative disorder and is characterized by the loss of dopaminergic neurons in the substantia nigra. Mutations in PINK1 were shown to cause recessive familial PD, and today are proposed to be associated with the disease via mitochondrial dysfunction and oxidative damage. The PINK1 gene comprises eight exons, which encode a ubiquitously expressed 581 amino acid protein that contains an N-terminal mitochondrial targeting domain and a serine/threonine protein kinase. To better understand the relationship between PINK1 and PD we have first analyzed the evolutionary history of the gene showing its late emergence in evolution. In addition, we have modeled the three-dimensional structure of PINK1 and found some evidences that help to explain the effect of some PD-related mutations in this protein’s function.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marigorta, Urko M</style></author><author><style face="normal" font="default" size="100%">Lao, Oscar</style></author><author><style face="normal" font="default" size="100%">Casals, Ferran</style></author><author><style face="normal" font="default" size="100%">Calafell, Francesc</style></author><author><style face="normal" font="default" size="100%">Morcillo-Suarez, Carlos</style></author><author><style face="normal" font="default" size="100%">Faria, Rui</style></author><author><style face="normal" font="default" size="100%">Bosch, Elena</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Bertranpetit, Jaume</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Recent human evolution has shaped geographical differences in susceptibility to disease.</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><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">55</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Searching for associations between genetic variants and complex diseases has been a very active area of research for over two decades. More than 51,000 potential associations have been studied and published, a figure that keeps increasing, especially with the recent explosion of array-based Genome-Wide Association Studies. Even if the number of true associations described so far is high, many of the putative risk variants detected so far have failed to be consistently replicated and are widely considered false positives. Here, we focus on the world-wide patterns of replicability of published association studies.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martín-Trillo, Mar</style></author><author><style face="normal" font="default" size="100%">Grandío, Eduardo González</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Marcel, Fabien</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Buey, María Luisa</style></author><author><style face="normal" font="default" size="100%">Schmitz, Gregor</style></author><author><style face="normal" font="default" size="100%">Theres, Klaus</style></author><author><style face="normal" font="default" size="100%">Bendahmane, Abdelhafid</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Cubas, Pilar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Role of tomato BRANCHED1-like genes in the control of shoot branching.</style></title><secondary-title><style face="normal" font="default" size="100%">The Plant journal : for cell and molecular 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%">2011 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">67</style></volume><pages><style face="normal" font="default" size="100%">701-14</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In angiosperms, shoot branching greatly determines overall plant architecture and affects fundamental aspects of plant life. Branching patterns are determined by genetic pathways conserved widely across angiosperms. In Arabidopsis thaliana (Brassicaceae, Rosidae) BRANCHED1 (BRC1) plays a central role in this process, acting locally to arrest axillary bud growth. In tomato (Solanum lycopersicum, Solanaceae, Asteridae) we have identified two BRC1-like paralogues, SlBRC1a and SlBRC1b. These genes are expressed in arrested axillary buds and both are down-regulated upon bud activation, although SlBRC1a is transcribed at much lower levels than SlBRC1b. Alternative splicing of SlBRC1a renders two transcripts that encode two BRC1-like proteins with different C-t domains due to a 3’-terminal frameshift. The phenotype of loss-of-function lines suggests that SlBRC1b has retained the ancestral role of BRC1 in shoot branch suppression. We have isolated the BRC1a and BRC1b genes of other Solanum species and have studied their evolution rates across the lineages. These studies indicate that, after duplication of an ancestral BRC1-like gene, BRC1b genes continued to evolve under a strong purifying selection that was consistent with the conserved function of SlBRC1b in shoot branching control. In contrast, the coding sequences of Solanum BRC1a genes have evolved at a higher evolution rate. Branch-site tests indicate that this difference does not reflect relaxation but rather positive selective pressure for adaptation.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lüke, Lena</style></author><author><style face="normal" font="default" size="100%">Vicens, Alberto</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Luque-Larena, Juan Jose</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Roldan, Eduardo R S</style></author><author><style face="normal" font="default" size="100%">Gomendio, Montserrat</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sexual selection halts the relaxation of protamine 2 among rodents.</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><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029247</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e29247</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Sexual selection has been proposed as the driving force promoting the rapid evolutionary changes observed in some reproductive genes including protamines. We test this hypothesis in a group of rodents which show marked differences in the intensity of sexual selection. Levels of sperm competition were not associated with the evolutionary rates of protamine 1 but, contrary to expectations, were negatively related to the evolutionary rate of cleaved- and mature-protamine 2. Since both domains were found to be under relaxation, our findings reveal an unforeseen role of sexual selection: to halt the degree of degeneration that proteins within families may experience due to functional redundancy. The degree of relaxation of protamine 2 in this group of rodents is such that in some species it has become dysfunctional and it is not expressed in mature spermatozoa. In contrast, protamine 1 is functionally conserved but shows directed positive selection on specific sites which are functionally relevant such as DNA-anchoring domains and phosphorylation sites. We conclude that in rodents protamine 2 is under relaxation and that sexual selection removes deleterious mutations among species with high levels of sperm competition to maintain the protein functional and the spermatozoa competitive.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cuenca-Bono, Bernardo</style></author><author><style face="normal" font="default" size="100%">García-Molinero, Varinia</style></author><author><style face="normal" font="default" size="100%">Pascual-García, Pau</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Llopis, Ana</style></author><author><style face="normal" font="default" size="100%">Vilardell, Josep</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Navarro, Susana</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SUS1 introns are required for efficient mRNA nuclear export in yeast.</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%">2011 Oct 1</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">8599-611</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Efficient coupling between mRNA synthesis and export is essential for gene expression. Sus1/ENY2, a component of the SAGA and TREX-2 complexes, is involved in both transcription and mRNA export. While most yeast genes lack introns, we previously reported that yeast SUS1 bears two. Here we show that this feature is evolutionarily conserved and critical for Sus1 function. We determine that while SUS1 splicing is inefficient, it responds to cellular conditions, and intronic mutations either promoting or blocking splicing lead to defects in mRNA export and cell growth. Consistent with this, we find that an intron-less SUS1 only partially rescues sus1&amp;Delta; phenotypes. Remarkably, splicing of each SUS1 intron is also affected by the presence of the other and by SUS1 exonic sequences. Moreover, by following SUS1 RNA and protein levels we establish that nonsense-mediated decay (NMD) pathway and the splicing factor Mud2 both play a role in SUS1 expression. Our data (and those of the accompanying work by Hossain et al.) provide evidence of the involvement of splicing, translation, and decay in the regulation of early events in mRNP biogenesis; and imply the additional requirement for a balance in splicing isoforms from a single gene.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Capriotti, Emidio</style></author><author><style face="normal" font="default" size="100%">Arbiza, Leonardo</style></author><author><style face="normal" font="default" size="100%">Casadio, Rita</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Marti-Renom, Marc A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mutat</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Codon</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Iduronic Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Point Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Tumor Suppressor Protein p53</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%">2008 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">198-204</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Predicting the functional impact of protein variation is one of the most challenging problems in bioinformatics. A rapidly growing number of genome-scale studies provide large amounts of experimental data, allowing the application of rigorous statistical approaches for predicting whether a given single point mutation has an impact on human health. Up until now, existing methods have limited their source data to either protein or gene information. Novel in this work, we take advantage of both and focus on protein evolutionary information by using estimated selective pressures at the codon level. Here we introduce a new method (SeqProfCod) to predict the likelihood that a given protein variant is associated with human disease or not. Our method relies on a support vector machine (SVM) classifier trained using three sources of information: protein sequence, multiple protein sequence alignments, and the estimation of selective pressure at the codon level. SeqProfCod has been benchmarked with a large dataset of 8,987 single point mutations from 1,434 human proteins from SWISS-PROT. It achieves 82% overall accuracy and a correlation coefficient of 0.59, indicating that the estimation of the selective pressure helps in predicting the functional impact of single-point mutations. Moreover, this study demonstrates the synergic effect of combining two sources of information for predicting the functional effects of protein variants: protein sequence/profile-based information and the evolutionary estimation of the selective pressures at the codon level. The results of large-scale application of SeqProfCod over all annotated point mutations in SWISS-PROT (available for download at http://sgu.bioinfo.cipf.es/services/Omidios/; last accessed: 24 August 2007), could be used to support clinical studies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/17935148?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Al-Shahrour, Fátima</style></author><author><style face="normal" font="default" size="100%">Arbiza, Leonardo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, Jaime</style></author><author><style face="normal" font="default" size="100%">Minguez, Pablo</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">From genes to functional classes in the study of biological systems.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Multigene Family</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Systems biology</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%">2007 Apr 03</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;With the popularization of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Here we present FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;Methods for gene set enrichment which, in addition, are independent from the original data and experimental design constitute a promising alternative for the functional profiling of genome-scale experiments. A web server that performs the test described and other similar ones can be found at: http://www.babelomics.org.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/17407596?dopt=Abstract</style></custom1></record></records></xml>