Genome-wide epistasis and co-selection study using mutual information.

Johan Pensar,Yingying Xu,Santeri Puranen,Brian Arnold,Leonor Sánchez-Busó,Aleksi Sipola,Stephen D Bentley,Maiju Pesonen,Jukka Corander,Nicholas J Croucher,Neil Macalasdair,Gerry Tonkin-Hill,Juri Kuronen,Simon R Harris,John A Lees,Julian Parkhill,Claire Chewapreecha

doi:10.1093/nar/gkz656

Abstract

Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which adjusts for the phylogenetic signal in the data without requiring an explicit phylogenetic tree. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Simulations demonstrate the usefulness of our method and give some insight to when this type of analysis is most likely to be successful. Application of the method to large population genomic datasets of two major human pathogens, Streptococcus pneumoniae and Neisseria meningitidis, revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.

Highlights

Comparative methods for detecting co-evolutionary signals from population sequence data have received a lot of attention over the last few decades
Attention has recently been directed toward exploratory covariation analysis of genome-wide nucleotide alignments for bacterial populations, where the aim is to reveal putative sites co-evolving under a shared selective pressure and possibly, but not necessarily, being involved in epistatic interactions [9,10,11]
For short-distance single-nucleotide polymorphisms (SNPs) pairs there is a peak of high mutual information (MI) values caused by linkage disequilibrium (LD)

Summary

Introduction

Comparative methods for detecting co-evolutionary signals from population sequence data have received a lot of attention over the last few decades. Sites co-evolving under a shared selective pressure may give rise to a co-selection pattern that can be detected from sequence alignments, even in the absence of appropriate phenotypic data. Attention has recently been directed toward exploratory covariation analysis of genome-wide nucleotide alignments for bacterial populations, where the aim is to reveal putative sites co-evolving under a shared selective pressure and possibly, but not necessarily, being involved in epistatic interactions [9,10,11].

Objectives

Results

Conclusion