Fine-Resolution Asymmetric Migration Estimation

The genetic structure of populations is often shaped by processes and events that introduce asymmetries to gene flow between geographic locations. Here, we first develop an algorithm that allows efficient computation of pairwise coalescent times in time-homogeneous models of population structure at migration-drift equilibrium. We then use the algorithm as the foundation for a new method to infer asymmetric migration rates in spatial models of population structure. The inferred equilibrium migration rates provide a novel representation of the geographic structure of genetic variation. We assess the method using a variety of simulated histories of gene flow, and apply the method to datasets from poplar trees, North American gray wolves, and human archaeogenetic samples, revealing complex asymmetric migration signals and providing a more refined view of the geographic structure of genetic variation.