Abstract
Acquisition and loss of genetic material are essential forces in bacterial microevolution. They have been repeatedly linked with adaptation of lineages to new lifestyles, and in particular, pathogenicity. Comparative genomics has the potential to elucidate this genetic flux, but there are many methodological challenges involved in inferring evolutionary events from collections of genome sequences. Here we describe a model-based method for using whole-genome sequences to infer the patterns of genome content evolution. A fundamental property of our model is that it allows the rates at which genetic elements are gained or lost to vary in time and from one lineage to another. Our approach is purely sequence based, and does not rely on gene identification. We show how inference can be performed under our model and illustrate its use on three datasets from Francisella tularensis, Streptococcus pyogenes, and Escherichia coli. In all three examples, we found interesting variations in the rates of genetic material gain and loss, which strongly correlate with their lifestyle. The algorithms we describe are implemented in a computer software named GenoPlast.