The study of bacteria has become increasingly important to agriculture, healthcare, and industry. However, the evolutionary forces that enable their unparalleled ability to adapt and persist in new environments have yet to be thoroughly determined. Due to their reproduction by binary fission, most evolutionary models consider bacteria to be clonally evolving. However, this ignores the contribution of genetic material from lateral genetic transfer (i.e. homologous recombination) which may be more impactful to their species and genomic evolution than mutation alone. Furthermore, tools developed to compare the impact of homologous recombination to mutation in bacteria are often based on strong assumptions and have been used to analyze only few species represented by few genomes. This, combined with a lack of standardization across methodologies and highly inconsistent measurements between studies makes determining the true impact of homologous recombination on bacterial evolution difficult. In this presentation, I will discuss how I leveraged HPC to estimate the evolutionary impact of lateral genetic exchange via homologous recombination in 162 bacterial and one archaeal species under a unified framework based on Approximate Bayesian Computation (ABC). Using this data, I was able to map the evolution of recombination rate — as a trait — across many bacterial species represented by thousands of genomes, as well as estimate recombination rate variation on a gene-by-gene basis across bacterial chromosomes. Overall, this study provides insight into the diversity of recombination rates across bacterial species — a key step in understanding how homologous recombination plays a role in bacterial speciation, adaptation, evolution, and population diversity.
