Automated phylogenetic detection of recombination using a genetic algorithm.

By Sergei L. Kosakovsky Pond, David Posada, M. Gravenor, Christopher H. Woelk, Simon D. W. Frost. Molecular biology and evolution, 2006

930 citations recorded by the source corpus.

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, for example, those used for detecting sites evolving nonneutrally, 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 nonrecombinant fragments. We propose a model-based framework that uses a genetic algorithm to search a multiple-sequence alignment for putative recombination break points, 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 data sets. Finally, we demonstrate that prescreening alignments with our method allows one to analyze recombinant sequences for positive selection.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a176c9bd4ab2195ebb051bd30c28d8b6801a4831

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Citations in the corpus

Short Communication Comparative analysis reveals frequent recombination in the parvoviruses (2007, methodology): “To screen for recombination we employed two preliminary detection programs: RDP2 (Martin et al., 2005) and Genetic Algorithms for Recombination Detection (GARD; Kosakovsky Pond et al., 2006).”
Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses OC43 and 229e (2020, neutral): “A dramatic difference in a given isolate’s position on one tree versus another is strongly indicative of recombination ( Kosakovsky Pond et al., 2006 ).”
Molecular Evolution of Human Coronavirus Genomes (2016, neutral): “The location of recombination breakpoints can be detected using phylogenetic incongruence among segments in a sequence alignment (e.g., GARD [70]) or by evaluating the distribution of nucleotide substitution along genomic regions (e.g., Recco [71]).”
Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic (2020, methodology): “All four of these breakpoints were also identified with the tree-based recombination detection method GARD (Kosakovsky Pond et al., 2006).”