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A novel substitution matrix fitted to the compositional bias in Mollicutes improves the prediction of homologous relationships

hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
hal.structure.identifierBiological systems and models, bioinformatics and sequences [SYMBIOSE]
dc.contributor.authorLEMAITRE, Claire
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
dc.contributor.authorBARRÉ, Aurélien
hal.structure.identifierInteractions hôtes-agents pathogènes [Toulouse] [IHAP]
hal.structure.identifierInstitut National de la Recherche Agronomique [INRA]
dc.contributor.authorCITTI, Christine
hal.structure.identifierLaboratoire de Lyon [ANSES]
dc.contributor.authorTARDY, Florence
hal.structure.identifierContrôle des maladies animales exotiques et émergentes [UMR CMAEE]
dc.contributor.authorTHIAUCOURT, François
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorSIRAND-PUGNET, Pascal
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorTHÉBAULT, Patricia
dc.date.issued2011
dc.identifier.issn1471-2105
dc.description.abstractEnSubstitution matrices are key parameters for the alignment of two protein sequences, and consequently for most comparative genomics studies. The composition of biological sequences can vary importantly between species and groups of species, and classical matrices such as those in the BLOSUM series fail to accurately estimate alignment scores and statistical significance with sequences sharing marked compositional biases. We present a general and simple methodology to build matrices that are especially fitted to the compositional bias of proteins. Our approach is inspired from the one used to build the BLOSUM matrices and is based on learning substitution and amino acid frequencies on real sequences with the corresponding compositional bias. We applied it to the large scale comparison of Mollicute AT-rich genomes. The new matrix, MOLLI60, was used to predict pairwise orthology relationships, as well as homolog families among 24 Mollicute genomes. We show that this new matrix enables to better discriminate between true and false orthologs and improves the clustering of homologous proteins, with respect to the use of the classical matrix BLOSUM62. We show in this paper that well-fitted matrices can improve the predictions of orthologous and homologous relationships among proteins with a similar compositional bias. With the ever-increasing number of sequenced genomes, our approach could prove valuable in numerous comparative studies focusing on atypical genomes.
dc.description.sponsorshipEtude à grande échelle des génomes des mycoplasmes de ruminants : évolution et adaptation de bactéries minimales à des hôtes complexes - ANR-07-GMGE-0001
dc.language.isoen
dc.publisherBioMed Central
dc.subjectsubstitution matrix
dc.subjectmollicutes
dc.subject.enorthologous predictions
dc.subject.enbiochemistry and molecular biology
dc.subject.enbiotechnology and applied microbiology
dc.subject.enmathematical and computational biology
dc.title.enA novel substitution matrix fitted to the compositional bias in Mollicutes improves the prediction of homologous relationships
dc.typeArticle de revue
dc.identifier.doi10.1186/1471-2105-12-457
dc.subject.halSciences du Vivant [q-bio]/Biochimie, Biologie Moléculaire/Génomique, Transcriptomique et Protéomique [q-bio.GN]
dc.subject.halSciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
dc.subject.halInformatique [cs]/Bio-informatique [q-bio.QM]
bordeaux.journalBMC Bioinformatics
bordeaux.page457
bordeaux.volume12
bordeaux.issue1
bordeaux.peerReviewedoui
hal.identifierhal-00784414
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00784414v1
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