4.8 Article

Ribosomal RNA diversity predicts genome diversity in gut bacteria and their relatives

期刊

NUCLEIC ACIDS RESEARCH
卷 38, 期 12, 页码 3869-3879

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkq066

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资金

  1. Genome Databases: Mining and Management [MCDB 5621]
  2. National Institutes of Health [T32 GM08759, P01DK078669, R01HG004872]
  3. Crohn's and Colitis Foundation of America
  4. Howard Hughes Medical Institute (HHMI)
  5. NATIONAL HUMAN GENOME RESEARCH INSTITUTE [R01HG004872] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [P01DK078669] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [T32GM008759] Funding Source: NIH RePORTER

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The mammalian gut is an attractive model for exploring the general question of how habitat impacts the evolution of gene content. Therefore, we have characterized the relationship between 16S rRNA gene sequence similarity and overall levels of gene conservation in four groups of species: gut specialists and cosmopolitans, each of which can be divided into pathogens and non-pathogens. At short phylogenetic distances, specialist or cosmopolitan bacteria found in the gut share fewer genes than is typical for genomes that come from non-gut environments, but at longer phylogenetic distances gut bacteria are more similar to each other than are genomes at equivalent evolutionary distances from non-gut environments, suggesting a pattern of short-term specialization but long-term convergence. Moreover, this pattern is observed in both pathogens and non-pathogens, and can even be seen in the plasmids carried by gut bacteria. This observation is consistent with the finding that, despite considerable interpersonal variation in species content, there is surprising functional convergence in the microbiome of different humans. Finally, we observe that even within bacterial species or genera 16S rRNA divergence provides useful information about average conservation of gene content. The results described here should be useful for guiding strain selection to maximize novel gene discovery in large-scale genome sequencing projects, while the approach could be applied in studies seeking to understand the effects of habitat adaptation on genome evolution across other body habitats or environment types.

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