Mycobacterial phylogenomics: an enhanced method for gene turnover analysis reveals uneven levels of gene gain and loss among species and gene families

Pablo Librado, Filipe Jorge Garrett Vieira, Alejandro Sánchez-Gracia, Sergios Orestis Kolokotronis, Julio Rozas

12 Citations (Scopus)

Abstract

Species of the genus Mycobacterium differ in several features, from geographic ranges, and degree of pathogenicity, to ecological and host preferences. The recent availability of several fully sequenced genomes for a number of these species enabled the comparative study of the genetic determinants of this wide lifestyle diversity. Here, we applied two complementary phylogenetic-based approaches using information from 19 Mycobacterium genomes to obtain a more comprehensive view of the evolution of this genus. First, we inferred the phylogenetic relationships using two new approaches, one based on a Mycobacterium-specific amino acid substitution matrix and the other on a gene content dissimilarity matrix. Then, we utilized our recently developed gain-and-death stochastic models to study gene turnover dynamics in this genus in a maximum-likelihood framework. We uncovered a scenario that differs markedly from traditional 16S rRNA data and improves upon recent phylogenomic approaches. We also found that the rates of gene gain and death are high and unevenly distributed both across species and across gene families, further supporting the utility of the new models of rate heterogeneity applied in a phylogenetic context. Finally, the functional annotation of the most expanded or contracted gene families revealed that the transposable elements and the fatty acid metabolism-related gene families are the most important drivers of gene content evolution in Mycobacterium.

Original languageEnglish
JournalGenome Biology and Evolution
Volume6
Issue number6
Pages (from-to)1454-1465
Number of pages12
ISSN1759-6653
DOIs
Publication statusPublished - Jun 2014
Externally publishedYes

Keywords

  • gene families
  • gene gain and loss
  • gene turnover rates
  • M. tuberculosis
  • maximum likelihood
  • rate heterogeneity

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