Evidence map›Paper›PMID 24904011›Full record

ArticleGenome biology and evolution2014

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 G Vieira, Alejandro Sánchez-Gracia, Sergios-Orestis Kolokotronis, Julio Rozas

Abstract read
In one paragraph

Article in Genome biology and evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. The many lives of nontuberculous mycobacteria.Journal of bacteriology · 2018
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Evolution by gene loss.Nature reviews. Genetics · 2016
    Review
  10. Article
  11. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Pablo LibradoDepartament de Genètica and Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain.
Filipe G VieiraDepartament de Genètica and Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, SpainDepartment of Integrative Biology, University of California, Berkeley.
Alejandro Sánchez-GraciaDepartament de Genètica and Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain.
Sergios-Orestis KolokotronisDepartment of Biological Sciences, Fordham UniversitySackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York.
Julio RozasDepartament de Genètica and Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain jrozas@ub.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Evolution, MolecularPhylogenyGenome, BacterialMycobacteriumgene familiesgene gain and lossgene turnover ratesmaximum likelihoodM. tuberculosisrate heterogeneity

Identifiers

PMID24904011
PMCPMC4079203

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.