Oral Presentation Society for Molecular Biology and Evolution Conference 2016

A novel algorithm for selective sweeps detection in bacteria (#146)

Oren Avram 1 , Yaara Oren 1 , Eli Levy Karin 1 , Tal Pupko 1
  1. Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel

Selective sweeps occur when a beneficial mutation spreads rapidly throughout the population due to natural selection. Searching for selective sweeps has proved to be one of the most fruitful ways to detect the footprints selection leaves on the genome.

In the last decade, methods to identify selective sweeps were developed as a powerful tool for uncovering the genomic basis of adaption. With a plethora of detection tools, the study of selective sweeps in eukaryotic systems is a well-established field of research. However, the search for selective sweeps in bacteria received little to no attention.

In our work we demonstrate that selective sweeps can also be detected in bacteria. Focusing on a comparative genomics E.coli database, we first study the performance of a commonly used selective sweep detection method in eukaryotes over these data and we discuss its limitations. Subsequently, we devise SAP, a novel phylogeny-based method for incomplete selective sweeps detection. We apply it to the E.coli database and detect several cases of incomplete selective sweeps. Using simulations, we demonstrate that most of these cases cannot be explained by neutral evolution under a model of no selection and no recombination, suggesting a bona fide signal for sweeps.

Since our methodology is not strain-specific but rather general, it can be applied to many other bacterial species, as long as they are able to share genetic material with their “neighbors”. Thus, we expect our new method should contribute to the effort of understanding bacterial phenotypic variation and adaptation at the genomic level.