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Impact of loci nature on estimating recombination and mutation rates in chlamydia trachomatis

dc.contributor.authorFerreira, Rita
dc.contributor.authorBorges, Vítor
dc.contributor.authorNunes, Alexandra
dc.contributor.authorNogueira, Paulo Jorge
dc.contributor.authorBorrego, Maria José
dc.contributor.authorGomes, João Paulo
dc.date.accessioned2012-07-23T11:35:44Z
dc.date.available2012-07-23T11:35:44Z
dc.date.issued2012
dc.descriptionCopyright © 2012 Ferreira et alpor
dc.description.abstractThe knowledge of the frequency and relative weight of mutation and recombination events in evolution is essential for understanding how microorganisms reach fitted phenotypes. Traditionally, these evolutionary parameters have been inferred by using data from multilocus sequence typing (MLST), which is known to have yielded conflicting results. In the near future, these estimations will certainly be performed by computational analyses of full-genome sequences. However, it is not known whether this approach will yield accurate results as bacterial genomes exhibit heterogeneous representation of loci categories, and it is not clear how loci nature impacts such estimations. Therefore, we assessed how mutation and recombination inferences are shaped by loci with different genetic features, using the bacterium Chlamydia trachomatis as the study model. We found that loci assigning a high number of alleles and positively selected genes yielded nonconvergent estimates and incongruent phylogenies and thus are more prone to confound algorithms. Unexpectedly, for the model under evaluation, housekeeping genes and noncoding regions shaped estimations in a similar manner, which points to a nonrandom role of the latter in C. trachomatis evolution. Although the present results relate to a specific bacterium, we speculate that microbe-specific genomic architectures (such as coding capacity, polymorphism dispersion, and fraction of positively selected loci) may differentially buffer the effect of the confounding factors when estimating recombination and mutation rates and, thus, influence the accuracy of using full-genome sequences for such purpose. This putative bias associated with in silico inferences should be taken into account when discussing the results obtained by the analyses of full-genome sequences, in which the “one size fits all” approach may not be applicable.eng
dc.description.sponsorshipThis work was supported by a grant, ERA-PTG/0004/2010, from Fundação para a Ciência e a Tecnologia (FCT) (to J.P.G.), in the frame of ERA-NET PathoGenoMics. R.F. and V.B. are recipients of Ph.D. fellowships (SFRH/BD/68532/2010 and SFRH/BD/68527/2010, respectively) from FCT. A.N. is a recipient of a post-doctoral fellowship(SFRH/BPD/75295/2010) from FCT.eng
dc.identifier.citationG3:Genes,Genomes,Genetics 2012;2:761-8.por
dc.identifier.issn2160-1836
dc.identifier.urihttp://dx.doi.org/10.1534/g3.112.002923
dc.identifier.urihttp://www.g3journal.org/content/2/7/761.abstract?sid=9048f1e9-37a5-474e-b639-e5b865b7cebc
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherGenetics Society of Americapor
dc.subjectMutation rateeng
dc.subjectRecombination rateeng
dc.subjectEvolutionary inferenceeng
dc.subjectClonalFrameeng
dc.subjectChlamydia trachomatiseng
dc.subjectGeneticseng
dc.titleImpact of loci nature on estimating recombination and mutation rates in chlamydia trachomatiseng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage768por
oaire.citation.startPage761por
oaire.citation.titleG3: Genes, Genomes, Geneticseng
rcaap.rightsrestrictedAccesspor
rcaap.typearticlepor

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