Detecting co-selection through excess linkage disequilibrium in bacterial genomes

Area of Science:

• Genomics
• Evolutionary Biology
• Bioinformatics

Background:

• Population genomics and genome-wide association studies (GWAS) advance bacterial evolution research.
• Genome-wide epistasis and co-selection (GWES) analysis generates hypotheses on multi-locus selection.
• Current GWES methods are limited to long-range associations due to linkage disequilibrium (LD).

Purpose of the Study:

• To introduce LDWeaver, a novel method for exhaustive GWES analysis across short and long genomic distances.
• To differentiate neutral co-variation from selection acting on linked and unlinked loci.
• To facilitate hypothesis generation for bacterial evolution using population genomic data.

Main Methods:

• Developed LDWeaver for comprehensive GWES, analyzing both short- and long-range LD.
• Applied LDWeaver to large-scale genomic surveys of human bacterial pathogens.
• Validated findings using functional genomic annotation and phenotypic data.

Main Results:

• LDWeaver efficiently generates hypotheses regarding co-selection.
• The method successfully disentangles neutral co-variation from selection.
• Several co-selection findings were validated in major bacterial pathogens.

Conclusions:

• LDWeaver enhances the study of bacterial evolution by enabling comprehensive GWES.
• The tool addresses limitations of existing methods by considering short-range genomic interactions.
• This approach supports data-driven discovery in the era of expanding population genomic data.