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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...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2009
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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 |
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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 |
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