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

Abstract

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 github.com/sanger-pathogens/Gubbins, implemented in Python and C and supported on Linux and Mac OS X.

Correlated Mutations and Homologous Recombination Within Bacterial Populations

“…As noted in previous studies (Croucher et al 2011(Croucher et al , 2015Chewapreecha et al 2014), calling recombination events on a locus-by-locus basis is confounded by overlapping recombination events, which often cannot be detected, and is strongly affected by the age of the sample. For this reason, such methods are typically conservative, and their estimates are in effect lower bounds.…”

“…Using a coalescent model with gene-conversion, computationally intensive methods have been developed that allow estimation of recombination rates on a whole-genome scale (Didelot et al 2010;Ansari and Didelot 2014). Other methods detect recombination events based on regional differences of single nucleotide polymorphism (SNP) density (Croucher et al 2015) or inferred phylogeny (Marttinen et al 2012), and are often used to establish a clonal phylogeny for a sample based on the vertically inherited regions. Patterns of SNP density combined with Markov Chain Monte Carlo simulations have also been used to infer genome-wide recombination parameters (Dixit et al 2015).…”

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

“…Recombinations result in a large number of SNPs against a reference; because phylogenetic methods assume vertical evolution, recombination tends to inflate estimated branch lengths. The best practice is to try to remove these regions before performing phylogenetic reconstruction 47 . When picking an MLST scheme for an organism, given a choice of genes to use, these phylogenetic signals may be a useful additional consideration.…”

Closing gaps for performing a risk assessment on Listeria monocytogenes in ready‐to‐eat (RTE) foods: activity 3, the comparison of isolates from different compartments along the food chain, and from humans using whole genome sequencing (WGS) analysis

“…Gubbins (Croucher et al, 2014) was be used to identify recombinant regions of the genome within clonal groups. These positions can then be filtered as appropriate when inferring the ancestry of strains.…”