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Detection of Homologous Recombination Events in Bacterial Genomes

We study the detection of mutations, sequencing errors, and homologous recombination events (HREs) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNPs) and break the genomes into blocks to handle the rearrangement problem. Then we apply a dynamic...

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Detalles Bibliográficos
Autores principales: Wang, Wei-Bung, Jiang, Tao, Gardner, Shea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3792089/
https://www.ncbi.nlm.nih.gov/pubmed/24116030
http://dx.doi.org/10.1371/journal.pone.0075230
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author Wang, Wei-Bung
Jiang, Tao
Gardner, Shea
author_facet Wang, Wei-Bung
Jiang, Tao
Gardner, Shea
author_sort Wang, Wei-Bung
collection PubMed
description We study the detection of mutations, sequencing errors, and homologous recombination events (HREs) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNPs) and break the genomes into blocks to handle the rearrangement problem. Then we apply a dynamic programming algorithm to model whether changes within each block are likely a result of mutations, sequencing errors, or HREs. Results from simulation experiments show that we can detect 31%–61% of HREs and the precision of our detection is about 48%–90% depending on the rates of mutation and missing data. The HREfinder software for predicting HREs in a set of whole genomes is available as open source (http://sourceforge.net/projects/hrefinder/).
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spelling pubmed-37920892013-10-10 Detection of Homologous Recombination Events in Bacterial Genomes Wang, Wei-Bung Jiang, Tao Gardner, Shea PLoS One Research Article We study the detection of mutations, sequencing errors, and homologous recombination events (HREs) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNPs) and break the genomes into blocks to handle the rearrangement problem. Then we apply a dynamic programming algorithm to model whether changes within each block are likely a result of mutations, sequencing errors, or HREs. Results from simulation experiments show that we can detect 31%–61% of HREs and the precision of our detection is about 48%–90% depending on the rates of mutation and missing data. The HREfinder software for predicting HREs in a set of whole genomes is available as open source (http://sourceforge.net/projects/hrefinder/). Public Library of Science 2013-10-07 /pmc/articles/PMC3792089/ /pubmed/24116030 http://dx.doi.org/10.1371/journal.pone.0075230 Text en © 2013 Wang 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
Wang, Wei-Bung
Jiang, Tao
Gardner, Shea
Detection of Homologous Recombination Events in Bacterial Genomes
title Detection of Homologous Recombination Events in Bacterial Genomes
title_full Detection of Homologous Recombination Events in Bacterial Genomes
title_fullStr Detection of Homologous Recombination Events in Bacterial Genomes
title_full_unstemmed Detection of Homologous Recombination Events in Bacterial Genomes
title_short Detection of Homologous Recombination Events in Bacterial Genomes
title_sort detection of homologous recombination events in bacterial genomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3792089/
https://www.ncbi.nlm.nih.gov/pubmed/24116030
http://dx.doi.org/10.1371/journal.pone.0075230
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