Publication: Assessment of selection pressure exerted on genes from complete pangenomes helps to improve the accuracy in the prediction of new genes
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Oxford University Press
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Bacterial genomes are massively sequenced, and they provide valuable data to better know the complete set of genes of a species. The analysis of thousands of bacterial strains can identify both shared genes and those appearing only in the pathogenic ones. Current computational gene finders facilitate this task but often miss some existing genes. However, the present availability of different genomes from the same species is useful to estimate the selective pressure applied on genes of complete pangenomes. It may assist in evaluating gene predictions either by checking the certainty of a new gene or annotating it as a gene under positive selection. Here, we estimated the selective pressure of 19 271 genes that are part of the pangenome of the human opportunistic pathogen Acinetobacter baumannii and found that most genes in this bacterium are subject to negative selection. However, 23% of them showed values compatible with positive selection. These latter were mainly uncharacterized proteins or genes required to evade the host defence system including genes related to resistance and virulence whose changes may be favoured to acquire new functions. Finally, we evaluated the utility of measuring selection pressure in the detection of sequencing errors and the validation of gene prediction.
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114861GB-I00/ES/ESTUDIO DEL CRISPROMA DEL GRUPO ESKAPE DE BACTERIAS DE INTERES CLINICO Y SU RELACION CON GENES DE LA PROPIA BACTERIA/
Ministry of Economy and Competitiveness (BFU2016-77297-P)
Ministry of Economy and Competitiveness (BFU2016-77297-P)
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Alejandro Rubio, Juan Jimenez, Antonio J Pérez-Pulido, Assessment of selection pressure exerted on genes from complete pangenomes helps to improve the accuracy in the prediction of new genes, Briefings in Bioinformatics, Volume 23, Issue 2, March 2022, bbac010, https://doi.org/10.1093/bib/bbac010






