One outcome of interspecific hybridization and subsequent effects of evolutionary
forces is introgression, which is the integration of genetic material from one species
into the genome of an individual in another species. The evolution of several groups of
eukaryotic species has involved hybridization, and cases of adaptation through
introgression have been already established. In this work, we report on a new
comparative genomic framework for detecting introgression in genomes, called
PhyloNet-HMM. The framework combines phylogenetic networks, which capture reticulate
evolutionary relationships among genomes, with hidden Markov models (HMMs), which
capture dependencies within genomes. A novel aspect of our work is that it also
accounts for incomplete lineage sorting and dependence across loci. We validate the
performance of PhyloNet-HMM using simulated and empirical data sets which include
either tree-like or non-tree-like evolutionary scenarios. Application of our model to
variation data from the mouse genome detects a recently reported adaptive introgression
event in addition to other newly detected introgression regions. Our work provides a
powerful framework for systematic analysis of introgression while simultaneously
accounting for dependence across sites, point mutations, recombination, and ancestral
polymorphism.