Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis

Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. The major human pathogen Streptococcus pneumoniae represents the first bacterial organism for which densely enough sampled population data became available for such an analysis. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. Genome data from over three thousand pneumococcal isolates identified 5,199 putative epistatic interactions between 1,