Detecting Recombination in Evolving Nucleotide Sequences

Chan, Cheong Xin, Beiko, Robert G. and Ragan, Mark A. (2006) Detecting Recombination in Evolving Nucleotide Sequences. BMC Bioinformatics, 7 Article 412: 1-15. doi:10.1186/1471-2105-7-412

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Author Chan, Cheong Xin
Beiko, Robert G.
Ragan, Mark A.
Title Detecting Recombination in Evolving Nucleotide Sequences
Journal name BMC Bioinformatics   Check publisher's open access policy
ISSN 1471-2105
Publication date 2006-09-01
Sub-type Article (original research)
DOI 10.1186/1471-2105-7-412
Open Access Status DOI
Volume 7
Issue Article 412
Start page 1
End page 15
Total pages 15
Editor Timothy Aitman
Place of publication London
Publisher Biomed Central Ltd
Collection year 2006
Language eng
Subject 270799 Ecology and Evolution not elsewhere classified
239901 Biological Mathematics
279999 Biological Sciences not elsewhere classified
270209 Meiosis and Recombination
270208 Molecular Evolution
780105 Biological sciences
Formatted abstract
Background:  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.

:  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.

Conclusions:  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.
Keyword recombination
nucleotide sequences
molecular evolution
gene transfer
gene conversion
Bacterial Genomes
Phylogenetic Networks
Chain Monte-carlo
Horizontal Gene-transfer
Biotechnology & Applied Microbiology
Biochemical Research Methods
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Additional Notes Article number: 412

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Created: Wed, 20 Sep 2006, 10:00:00 EST by Cheong Xin Chan on behalf of Institute for Molecular Bioscience