02586nas a2200193 4500008004100000245013300041210006900174520188100243653001502124653002302139653002202162100002202184700001502206700001502221700001402236700001902250700001702269856010602286 2009 eng d00aSexual selection drives weak positive selection in protamine genes and high promoter divergence, enhancing sperm competitiveness0 aSexual selection drives weak positive selection in protamine gen3 a

Phenotypic adaptations may be the result of changes in gene structure or gene regulation, but little is known about the evolution of gene expression. In addition, it is unclear whether the same selective forces may operate at both levels simultaneously. Reproductive proteins evolve rapidly, but the underlying selective forces promoting such rapid changes are still a matter of debate. In particular, the role of sexual selection in driving positive selection among reproductive proteins remains controversial, whereas its potential influence on changes in promoter regions has not been explored. Protamines are responsible for maintaining DNA in a compacted form in chromosomes in sperm and the available evidence suggests that they evolve rapidly. Because protamines condense DNA within the sperm nucleus, they influence sperm head shape. Here, we examine the influence of sperm competition upon protamine 1 and protamine 2 genes and their promoters, by comparing closely related species of Mus that differ in relative testes size, a reliable indicator of levels of sperm competition. We find evidence of positive selection in the protamine 2 gene in the species with the highest inferred levels of sperm competition. In addition, sperm competition levels across all species are strongly associated with high divergence in protamine 2 promoters that, in turn, are associated with sperm swimming speed. We suggest that changes in protamine 2 promoters are likely to enhance sperm swimming speed by making sperm heads more hydrodynamic. Such phenotypic changes are adaptive because sperm swimming speed may be a major determinant of fertilization success under sperm competition. Thus, when species have diverged recently, few changes in gene-coding sequences are found, while high divergence in promoters seems to be associated with the intensity of sexual selection.

10aAdaptation10apositive selection10asperm competition1 aMartin-Coello, J.1 aDopazo, H.1 aArbiza, L.1 aAusio, J.1 aRoldan, E., R.1 aGomendio, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1936473502909nas a2200241 4500008004100000245013300041210006900174300001200243490000700255520182100262653009602083653009302179653007402272653002302346653008902369100001802458700001502476700001602491700001502507700001502522700002402537856010602561 2008 eng d00aUse of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans0 aUse of estimated evolutionary strength at the codon level improv a198-2040 v293 aPredicting 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.10aAlgorithms Codon/genetics Computational Biology/*methods *DNA Mutational Analysis Databases10aHuman Humans Iduronic Acid/analogs & derivatives/metabolism *Point Mutation Polymorphism10aMolecular *Genetic Predisposition to Disease Genetic Variation Genome10aProtein *Evolution10aSingle Nucleotide Proteins/chemistry/*genetics Tumor Suppressor Protein p53/genetics1 aCapriotti, E.1 aArbiza, L.1 aCasadio, R.1 aDopazo, J.1 aDopazo, H.1 aMarti-Renom, M., A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1793514802367nas a2200229 4500008004100000245007200041210006900113300000800182490000600190520145600196653010501652653001501757653013601772100002401908700001501932700001501947700002101962700001601983700001701999700001502016856010602031 2007 eng d00aFrom genes to functional classes in the study of biological systems0 aFrom genes to functional classes in the study of biological syst a1140 v83 a

BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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.

10aAlgorithms Chromosome Mapping/*methods Computer Simulation Gene Expression Profiling/methods *Models10ababelomics10aBiological Multigene Family/*physiology Signal Transduction/*physiology *Software Systems Biology/*methods *User-Computer Interface1 aAl-Shahrour, Fatima1 aArbiza, L.1 aDopazo, H.1 aHuerta-Cepas, J.1 aMinguez, P.1 aMontaner, D.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1740759602437nas a2200265 4500008004100000245009200041210006900133300001100202490000700213520143600220653005301656653002601709653002201735653005701757653004501814653008601859100001601945700002001961700001501981700002101996700001802017700001502035700001502050856010602065 2007 eng d00aPhylemon: a suite of web tools for molecular evolution, phylogenetics and phylogenomics0 aPhylemon a suite of web tools for molecular evolution phylogenet aW38-420 v353 aPhylemon is an online platform for phylogenetic and evolutionary analyses of molecular sequence data. It has been developed as a web server that integrates a suite of different tools selected among the most popular stand-alone programs in phylogenetic and evolutionary analysis. It has been conceived as a natural response to the increasing demand of data analysis of many experimental scientists wishing to add a molecular evolution and phylogenetics insight into their research. Tools included in Phylemon cover a wide yet selected range of programs: from the most basic for multiple sequence alignment to elaborate statistical methods of phylogenetic reconstruction including methods for evolutionary rates analyses and molecular adaptation. Phylemon has several features that differentiates it from other resources: (i) It offers an integrated environment that enables the direct concatenation of evolutionary analyses, the storage of results and handles required data format conversions, (ii) Once an outfile is produced, Phylemon suggests the next possible analyses, thus guiding the user and facilitating the integration of multi-step analyses, and (iii) users can define and save complete pipelines for specific phylogenetic analysis to be automatically used on many genes in subsequent sessions or multiple genes in a single session (phylogenomics). The Phylemon web server is available at http://phylemon.bioinfo.cipf.es.10aAnimals Computational Biology/*methods Databases10aDNA Sequence Analysis10aGenetic Evolution10aMolecular Genetic Techniques Humans *Internet Models10aProtein Software User-Computer Interface10aStatistical *Phylogeny Programming Languages Sequence Alignment Sequence Analysis1 aTarraga, J.1 aMedina, Ignacio1 aArbiza, L.1 aHuerta-Cepas, J.1 aGabaldón, T.1 aDopazo, J.1 aDopazo, H. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1745234602542nas a2200181 4500008004100000245010000041210006900141300000800210490000600218520184100224653001502065653004302080653008602123100001502209700001502224700001502239856010602254 2006 eng d00aPositive selection, relaxation, and acceleration in the evolution of the human and chimp genome0 aPositive selection relaxation and acceleration in the evolution  ae380 v23 aFor years evolutionary biologists have been interested in searching for the genetic bases underlying humanness. Recent efforts at a large or a complete genomic scale have been conducted to search for positively selected genes in human and in chimp. However, recently developed methods allowing for a more sensitive and controlled approach in the detection of positive selection can be employed. Here, using 13,198 genes, we have deduced the sets of genes involved in rate acceleration, positive selection, and relaxation of selective constraints in human, in chimp, and in their ancestral lineage since the divergence from murids. Significant deviations from the strict molecular clock were observed in 469 human and in 651 chimp genes. The more stringent branch-site test of positive selection detected 108 human and 577 chimp positively selected genes. An important proportion of the positively selected genes did not show a significant acceleration in rates, and similarly, many of the accelerated genes did not show significant signals of positive selection. Functional differentiation of genes under rate acceleration, positive selection, and relaxation was not statistically significant between human and chimp with the exception of terms related to G-protein coupled receptors and sensory perception. Both of these were over-represented under relaxation in human in relation to chimp. Comparing differences between derived and ancestral lineages, a more conspicuous change in trends seems to have favored positive selection in the human lineage. Since most of the positively selected genes are different under the same functional categories between these species, we suggest that the individual roles of the alternative positively selected genes may be an important factor underlying biological differences between these species.10aAdaptation10aBiological/genetics Animals *Evolution10aMolecular Genome/*genetics Humans Pan troglodytes/*genetics *Selection (Genetics)1 aArbiza, L.1 aDopazo, J.1 aDopazo, H. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1668301901783nas a2200253 4500008004100000245010200041210006900143300001100212490000700223520089100230653004301121653008001164653002701244653005601271100001401327700002301341700001501364700001501379700001601394700001701410700002001427700001501447856006701462 2006 eng d00aPupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes0 aPupaSuite finding functional single nucleotide polymorphisms for aW621-50 v343 a

We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of user’s data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through http://pupasuite.bioinfo.cipf.es and through http://www.pupasnp.org.

10aAlgorithms Computer Graphics Databases10aMolecular Genotype Haplotypes Internet Linkage Disequilibrium *Polymorphism10aNucleic Acid Evolution10aSingle Nucleotide *Software User-Computer Interface1 aConde, L.1 aVaquerizas, J., M.1 aDopazo, H.1 aArbiza, L.1 aReumers, J.1 aRousseau, F.1 aSchymkowitz, J.1 aDopazo, J. uhttp://nar.oxfordjournals.org/cgi/content/full/34/suppl_2/W62102859nas a2200301 4500008004100000245009400041210006900135300001300204490000800217520172300225653007401948653002202022653001902044653002402063653002802087653002002115653015502135653002502290100001502315700001402330700001702344700001602361700002202377700002202399700001502421700001502436856010602451 2006 eng d00aSelective pressures at a codon-level predict deleterious mutations in human disease genes0 aSelective pressures at a codonlevel predict deleterious mutation a1390-4040 v3583 aDeleterious mutations affecting biological function of proteins are constantly being rejected by purifying selection from the gene pool. The non-synonymous/synonymous substitution rate ratio (omega) is a measure of selective pressure on amino acid replacement mutations for protein-coding genes. Different methods have been developed in order to predict non-synonymous changes affecting gene function. However, none has considered the estimation of selective constraints acting on protein residues. Here, we have used codon-based maximum likelihood models in order to estimate the selective pressures on the individual amino acid residues of a well-known model protein: p53. We demonstrate that the number of residues under strong purifying selection in p53 is much higher than those that are strictly conserved during the evolution of the species. In agreement with theoretical expectations, residues that have been noted to be of structural relevance, or in direct association with DNA, were among those showing the highest signals of purifying selection. Conversely, those changing according to a neutral, or nearly neutral mode of evolution, were observed to be irrelevant for protein function. Finally, using more than 40 human disease genes, we demonstrate that residues evolving under strong selective pressures (omega<0.1) are significantly associated (p<0.01) with human disease. We hypothesize that non-synonymous change on amino acids showing omega<0.1 will most likely affect protein function. The application of this evolutionary prediction at a genomic scale will provide an a priori hypothesis of the phenotypic effect of non-synonymous coding single nucleotide polymorphisms (SNPs) in the human genome.10aAmino Acid Sequence Amino Acid Substitution Codon/*genetics Databases10aGenetic Evolution10aGenetic Models10aHuman Humans Models10aInborn/*genetics Genome10aMolecular Genes10aMolecular Molecular Sequence Data *Mutation Neoplasms/genetics Proteins/genetics *Selection (Genetics) Tumor Suppressor Protein p53/chemistry/genetics10ap53 Genetic Diseases1 aArbiza, L.1 aDuchi, S.1 aMontaner, D.1 aBurguet, J.1 aPantoja-Uceda, D.1 aPineda-Lucena, A.1 aDopazo, J.1 aDopazo, H. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16584746