Hey, J., Chung, Y., Sethuraman, A., Lachance, J., Tishkoff, S., Sousa, V.C. & Wang, Y. (2018) Phylogeny estimation by integration over isolation with migration models.Molecular Biology and Evolution, Online early, . DOI:10.1093/molbev/msy162 (IF2017 10,217; Q1 Evolutionary Biology)
Phylogeny estimation is difficult for closely related populations and species, especially if they have been exchanging genes. We present a hierarchical Bayesian, Markov-chain Monte Carlo method with a state space that includes all possible phylogenies in a full Isolation-with-Migration model framework. The method is based on a new type of genealogy augmentation called a ‘hidden genealogy’ that enables efficient updating of the phylogeny. This is the first likelihood-based method to fully incorporate directional gene flow and genetic drift for estimation of a species or population phylogeny. Application to human hunter-gatherer populations from Africa revealed a clear phylogenetic history, with strong support for gene exchange with an un-sampled ghost population, and relatively ancient divergence between a ghost population and modern human populations, consistent with human/archaic divergence. In contrast, a study of five chimpanzee populations reveals a clear phylogeny with several pairs of populations having exchanged DNA, but does not support a history with an unsampled ghost population.