Quantitative models of bacterial evolution inferred from large number of draft genomes interactions

Sergei Maslov, University of Illinois at Urbana-Champaign

Usage Details

Quantitative understanding of evolution of bacterial genomes is essential to mitigate the emergence and spread of antibiotic-resistant and/or pathogenic strains. As such it has many important medical and societal applications. We recently proposed a suite of computational algorithms aimed at extracting the "basic" genome shared by most strains of a given bacterial or archaeal species. We then applied this basic genome to detect vertically and horizontally transferred genomic segments and to quantify their relative contributions to genome evolution. Here we propose to expand our computational analysis originally developed and tested for a small number (<100) of high quality "finished" genomes to a large number (>1,000) of lower quality "draft" genomes. This requires access to scalable computing resources such as Blue Waters.