Inferring Ancestral Recombination Graphs from Bacterial Genomic Data

Author:

Vaughan Timothy G12,Welch David12,Drummond Alexei J12,Biggs Patrick J3,George Tessy3,French Nigel P3

Affiliation:

1. Centre for Computational Evolution, The University of Auckland, 1010, New Zealand

2. Department of Computer Science, The University of Auckland, 1010, New Zealand

3. Molecular Epidemiology and Public Health Laboratory, Infectious Disease Research Centre, Hopkirk Research Institute, Massey University, Palmerston North 4442, New Zealand

Abstract

Abstract 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.

Publisher

Oxford University Press (OUP)

Subject

Genetics

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