Estimating the relative rate of recombination to mutation in bacteria from single-locus variants using composite likelihood methods

TL;DR

This paper introduces a composite likelihood approach to estimate the ratio of recombination to mutation rates in bacteria using single-locus variants, providing confidence intervals and tests for rate variation across loci.

Contribution

It extends existing methods by enabling confidence interval construction and rate variation testing without intensive bootstrap procedures.

Findings

Detected significant rate variation in Bacillus cereus, Enterococcus faecium, and Klebsiella pneumoniae.

Developed a new statistical framework for analyzing bacterial recombination and mutation rates.

Applied the method to MLST data from eight bacteria species.

Abstract

A number of studies have suggested using comparisons between DNA sequences of closely related bacterial isolates to estimate the relative rate of recombination to mutation for that bacterial species. We consider such an approach which uses single-locus variants: pairs of isolates whose DNA differ at a single gene locus. One way of deriving point estimates for the relative rate of recombination to mutation from such data is to use composite likelihood methods. We extend recent work in this area so as to be able to construct confidence intervals for our estimates, without needing to resort to computationally-intensive bootstrap procedures, and to develop a test for whether the relative rate varies across loci. Both our test and method for constructing confidence intervals are obtained by modeling the dependence structure in the data, and then applying asymptotic theory regarding the distribution of estimators obtained using a composite likelihood. We applied these methods to multi-locus sequence typing (MLST) data from eight bacteria, finding strong evidence for considerable rate variation in three of these: Bacillus cereus, Enterococcus faecium and Klebsiella pneumoniae.