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MBE Advance Access published online on July 3, 2006
Molecular Biology and Evolution, doi:10.1093/molbev/msl051
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© 2006 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Accepted June 27, 2006

Research Article

Automated Phylogenetic Detection of Recombination Using a Genetic Algorithm

Sergei L. Kosakovsky Pond 1 *, David Posada 2, Michael B. Gravenor 3, Christopher H. Woelk 1, and Simon D.W. Frost 1

1 Department of Pathology, University of California San Diego, La Jolla, California, 92093
2 University of Vigo, Spain
3 School of Medicine, University of Swansea, Swansea, Wales

* To whom correspondence should be addressed.
Sergei L. Kosakovsky Pond, E-mail: spond{at}ucsd.edu


  Abstract

The evolution of homologous sequences affected by recombination or gene conversion cannot be adequately explained by a single phylogenetic tree. Many tree-based methods for sequence analysis, e.g. those used for detecting sites evolving non-neutrally, have been shown to fail if such phylogenetic incongruity is ignored. However it may be possible to propose several phylogenies that can correctly model the evolution of non-recombinant fragments. We propose a model-based framework that uses a genetic algorithm to search a multiple sequence alignment for putative recombination breakpoints, quantifies the level of support for their locations and identifies sequences or clades involved in putative recombination events. The software implementation can be run quickly and efficiently in a distributed computing environment and various components of the methods can be chosen for computational expediency or statistical rigor. We evaluate the performance of the new method on simulated alignments and on an array of published benchmark datasets. Finally, we demonstrate that pre-screening alignments with our method allows one to analyze recombinant sequences for positive selection.

Keywords: Recombination; phylogenetic incongruence; model selection; genetic algorithms; multimodel inference.
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