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Inferring Ancestral Recombination Graphs from Bacterial Genomic Data
Author(s) -
Timothy G. Vaughan,
David Welch,
Alexei J. Drummond,
Patrick J. Biggs,
Tessy George,
Nigel French
Publication year - 2016
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1534/genetics.116.193425
Subject(s) - biology , phylogenetic tree , genetics , multilocus sequence typing , recombination , computational biology , inference , evolutionary biology , computer science , artificial intelligence , gene , genotype
Homologous recombination is a central feature of bacterial evolution, yet it confounds traditional phylogenetic methods. While a number of methods specific to bacterial evolution have been developed, none of these permit joint inference of a bacterial recombination graph and associated parameters. In this article, we present a new method which addresses this shortcoming. Our method uses a novel Markov chain Monte Carlo algorithm to perform phylogenetic inference under the ClonalOrigin model. We demonstrate the utility of our method by applying it to ribosomal multilocus sequence typing data sequenced from pathogenic and nonpathogenic Escherichia coli serotype O157 and O26 isolates collected in rural New Zealand. The method is implemented as an open source BEAST 2 package, Bacter, which is available via the project web page at http://tgvaughan.github.io/bacter.

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