Cargando…

Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach

The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relativel...

Descripción completa

Detalles Bibliográficos
Autores principales: Tang, Jing, Hanage, William P., Fraser, Christophe, Corander, Jukka
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2713424/
https://www.ncbi.nlm.nih.gov/pubmed/19662158
http://dx.doi.org/10.1371/journal.pcbi.1000455
_version_ 1782169578071130112
author Tang, Jing
Hanage, William P.
Fraser, Christophe
Corander, Jukka
author_facet Tang, Jing
Hanage, William P.
Fraser, Christophe
Corander, Jukka
author_sort Tang, Jing
collection PubMed
description The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/software/baps.html.
format Text
id pubmed-2713424
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-27134242009-08-07 Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach Tang, Jing Hanage, William P. Fraser, Christophe Corander, Jukka PLoS Comput Biol Research Article The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/software/baps.html. Public Library of Science 2009-08-07 /pmc/articles/PMC2713424/ /pubmed/19662158 http://dx.doi.org/10.1371/journal.pcbi.1000455 Text en Tang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Tang, Jing
Hanage, William P.
Fraser, Christophe
Corander, Jukka
Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach
title Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach
title_full Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach
title_fullStr Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach
title_full_unstemmed Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach
title_short Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach
title_sort identifying currents in the gene pool for bacterial populations using an integrative approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2713424/
https://www.ncbi.nlm.nih.gov/pubmed/19662158
http://dx.doi.org/10.1371/journal.pcbi.1000455
work_keys_str_mv AT tangjing identifyingcurrentsinthegenepoolforbacterialpopulationsusinganintegrativeapproach
AT hanagewilliamp identifyingcurrentsinthegenepoolforbacterialpopulationsusinganintegrativeapproach
AT fraserchristophe identifyingcurrentsinthegenepoolforbacterialpopulationsusinganintegrativeapproach
AT coranderjukka identifyingcurrentsinthegenepoolforbacterialpopulationsusinganintegrativeapproach