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dc.contributor.authorMarttinen, Pekkaen_US
dc.contributor.authorHanage, William P.en_US
dc.date.accessioned2017-11-21T20:47:00Z
dc.date.issued2017en_US
dc.identifier.citationMarttinen, Pekka, and William P. Hanage. 2017. “Speciation trajectories in recombining bacterial species.” PLoS Computational Biology 13 (7): e1005640. doi:10.1371/journal.pcbi.1005640. http://dx.doi.org/10.1371/journal.pcbi.1005640.en
dc.identifier.issnen
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:34375335
dc.description.abstractIt 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.en
dc.language.isoen_USen
dc.publisherPublic Library of Scienceen
dc.relation.isversionofdoi:10.1371/journal.pcbi.1005640en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542674/pdf/en
dash.licenseLAAen_US
dc.subjectBiology and Life Sciencesen
dc.subjectBehavioren
dc.subjectAnimal Behavioren
dc.subjectAnimal Migrationen
dc.subjectZoologyen
dc.subjectOrganismsen
dc.subjectBacteriaen
dc.subjectStreptococcusen
dc.subjectPneumococcusen
dc.subjectMicrobiologyen
dc.subjectMedical Microbiologyen
dc.subjectMicrobial Pathogensen
dc.subjectBacterial Pathogensen
dc.subjectMedicine and Health Sciencesen
dc.subjectPathology and Laboratory Medicineen
dc.subjectPathogensen
dc.subjectEcologyen
dc.subjectEcological Nichesen
dc.subjectEcology and Environmental Sciencesen
dc.subjectBiology and life sciencesen
dc.subjectGeneticsen
dc.subjectDNAen
dc.subjectDNA recombinationen
dc.subjectBiochemistryen
dc.subjectNucleic acidsen
dc.subjectHabitatsen
dc.subjectSimulation and Modelingen
dc.subjectTheoretical Ecologyen
dc.subjectPhysical Sciencesen
dc.subjectMathematicsen
dc.subjectApproximation Methodsen
dc.titleSpeciation trajectories in recombining bacterial speciesen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalPLoS Computational Biologyen
dash.depositing.authorHanage, William P.en_US
dc.date.available2017-11-21T20:47:00Z
dc.identifier.doi10.1371/journal.pcbi.1005640*
dash.contributor.affiliatedHanage, William


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