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Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins

Croucher, Nicholas J., Page, Andrew J., Connor, Thomas R. ORCID:, Delaney, Aidan J., Keane, Jacqueline A., Bentley, Stephen D., Parkhill, Julian and Harris, Simon R. 2015. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Research 43 (3) , e15. 10.1093/nar/gku1196

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The emergence of new sequencing technologies has facilitated the use of bacterial whole genome alignments for evolutionary studies and outbreak analyses. These datasets, of increasing size, often include examples of multiple different mechanisms of horizontal sequence transfer resulting in substantial alterations to prokaryotic chromosomes. The impact of these processes demands rapid and flexible approaches able to account for recombination when reconstructing isolates' recent diversification. Gubbins is an iterative algorithm that uses spatial scanning statistics to identify loci containing elevated densities of base substitutions suggestive of horizontal sequence transfer while concurrently constructing a maximum likelihood phylogeny based on the putative point mutations outside these regions of high sequence diversity. Simulations demonstrate the algorithm generates highly accurate reconstructions under realistically parameterized models of bacterial evolution, and achieves convergence in only a few hours on alignments of hundreds of bacterial genome sequences. Gubbins is appropriate for reconstructing the recent evolutionary history of a variety of haploid genotype alignments, as it makes no assumptions about the underlying mechanism of recombination. The software is freely available for download at, implemented in Python and C and supported on Linux and Mac OS X.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Biosciences
Systems Immunity Research Institute (SIURI)
Additional Information: This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher: Oxford University Press
ISSN: 0305-1048
Date of First Compliant Deposit: 8 March 2019
Date of Acceptance: 4 November 2014
Last Modified: 06 May 2023 09:49

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