Polymorphism-Aware Phylogenetic Models and their Applications

Carolin Kosiol (University of St Andrews)

The increased availability of sequenced genomes both from closely related species and from individuals of the same species, offers a great opportunity to study the speciation and evolutionary history of populations, provided we can properly model the process of sequence evolution using inter and intraspecific data together.

In my group, we have developed a new method called POlymorphisms-aware phylogenetic MOdel (PoMo). It extends any DNA substitution model and additionally accounts for polymorphisms in the present and in the ancestral population by expanding the state space to include polymorphic states in a continuous Markov process. It is a selection-mutation model which separates the mutation process from the fixation process. Thereby, a Moran process is used to model genetic drift. PoMo naturally accounts for incomplete lineage sorting because ancestral populations can be in a polymorphic state.

Our method can accurately and time-efficiently estimate the parameters describing evolutionary patterns for phylogenetic trees of any shape (species trees, population trees, or any combination of those). We have implemented the approach into Maximum Likelihood software package and recently developed a Bayesian framework for molecular dating. I will present what can be learned by applying these new methods to genome-wide data sites of great ape populations about ancestral population history of these species. Finally, I will also discuss how the new methods could be applied to populations of fruit flies that have recently been subject to an experimental evolution study for sexual mating system.