Detecting recombination in evolving nucleotide sequences

<p>Abstract</p> <p>Background</p> <p>Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. These recombination events can be obscured by subsequent residue substitutions, which consequently complicate their detection. W...

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Main Authors: Ragan Mark A, Beiko Robert G, Chan Cheong
Format: Article
Language:English
Published: BMC 2006-09-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/7/412
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spelling doaj-a56b8d04cd00426db5bd26488ae1c5982020-11-24T23:22:44ZengBMCBMC Bioinformatics1471-21052006-09-017141210.1186/1471-2105-7-412Detecting recombination in evolving nucleotide sequencesRagan Mark ABeiko Robert GChan Cheong<p>Abstract</p> <p>Background</p> <p>Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. These recombination events can be obscured by subsequent residue substitutions, which consequently complicate their detection. While there are many algorithms for the identification of recombination events, little is known about the effects of subsequent substitutions on the accuracy of available recombination-detection approaches.</p> <p>Results</p> <p>We assessed the effect of subsequent substitutions on the detection of simulated recombination events within sets of four nucleotide sequences under a homogeneous evolutionary model. The amount of subsequent substitutions per site, prior evolutionary history of the sequences, and reciprocality or non-reciprocality of the recombination event all affected the accuracy of the recombination-detecting programs examined. Bayesian phylogenetic-based approaches showed high accuracy in detecting evidence of recombination event and in identifying recombination breakpoints. These approaches were less sensitive to parameter settings than other methods we tested, making them easier to apply to various data sets in a consistent manner.</p> <p>Conclusion</p> <p>Post-recombination substitutions tend to diminish the predictive accuracy of recombination-detecting programs. The best method for detecting recombined regions is not necessarily the most accurate in identifying recombination breakpoints. For difficult detection problems involving highly divergent sequences or large data sets, different types of approach can be run in succession to increase efficiency, and can potentially yield better predictive accuracy than any single method used in isolation.</p> http://www.biomedcentral.com/1471-2105/7/412
collection DOAJ
language English
format Article
sources DOAJ
author Ragan Mark A
Beiko Robert G
Chan Cheong
spellingShingle Ragan Mark A
Beiko Robert G
Chan Cheong
Detecting recombination in evolving nucleotide sequences
BMC Bioinformatics
author_facet Ragan Mark A
Beiko Robert G
Chan Cheong
author_sort Ragan Mark A
title Detecting recombination in evolving nucleotide sequences
title_short Detecting recombination in evolving nucleotide sequences
title_full Detecting recombination in evolving nucleotide sequences
title_fullStr Detecting recombination in evolving nucleotide sequences
title_full_unstemmed Detecting recombination in evolving nucleotide sequences
title_sort detecting recombination in evolving nucleotide sequences
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2006-09-01
description <p>Abstract</p> <p>Background</p> <p>Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. These recombination events can be obscured by subsequent residue substitutions, which consequently complicate their detection. While there are many algorithms for the identification of recombination events, little is known about the effects of subsequent substitutions on the accuracy of available recombination-detection approaches.</p> <p>Results</p> <p>We assessed the effect of subsequent substitutions on the detection of simulated recombination events within sets of four nucleotide sequences under a homogeneous evolutionary model. The amount of subsequent substitutions per site, prior evolutionary history of the sequences, and reciprocality or non-reciprocality of the recombination event all affected the accuracy of the recombination-detecting programs examined. Bayesian phylogenetic-based approaches showed high accuracy in detecting evidence of recombination event and in identifying recombination breakpoints. These approaches were less sensitive to parameter settings than other methods we tested, making them easier to apply to various data sets in a consistent manner.</p> <p>Conclusion</p> <p>Post-recombination substitutions tend to diminish the predictive accuracy of recombination-detecting programs. The best method for detecting recombined regions is not necessarily the most accurate in identifying recombination breakpoints. For difficult detection problems involving highly divergent sequences or large data sets, different types of approach can be run in succession to increase efficiency, and can potentially yield better predictive accuracy than any single method used in isolation.</p>
url http://www.biomedcentral.com/1471-2105/7/412
work_keys_str_mv AT raganmarka detectingrecombinationinevolvingnucleotidesequences
AT beikorobertg detectingrecombinationinevolvingnucleotidesequences
AT chancheong detectingrecombinationinevolvingnucleotidesequences
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