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Speciation trajectories in recombining bacterial species.
Marttinen, Pekka; Hanage, William P.
Afiliação
  • Marttinen P; Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University, Espoo, Finland.
  • Hanage WP; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.
PLoS Comput Biol ; 13(7): e1005640, 2017 Jul.
Article em En | MEDLINE | ID: mdl-28671999
It is generally agreed that bacterial diversity can be classified into genetically and ecologically cohesive units, but what produces such variation is a topic of intensive research. Recombination may maintain coherent species of frequently recombining bacteria, but the emergence of distinct clusters within a recombining species, and the impact of habitat structure in this process are not well described, limiting our understanding of how new species are created. Here we present a model of bacterial evolution in overlapping habitat space. We show that the amount of habitat overlap determines the outcome for a pair of clusters, which may range from fast clonal divergence with little interaction between the clusters to a stationary population structure, where different clusters maintain an equilibrium distance between each other for an indefinite time. We fit our model to two data sets. In Streptococcus pneumoniae, we find a genomically and ecologically distinct subset, held at a relatively constant genetic distance from the majority of the population through frequent recombination with it, while in Campylobacter jejuni, we find a minority population we predict will continue to diverge at a higher rate. This approach may predict and define speciation trajectories in multiple bacterial species.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Bactérias / Evolução Molecular / Especiação Genética / Modelos Genéticos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Bactérias / Evolução Molecular / Especiação Genética / Modelos Genéticos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article