Inferring hominin history with recurrent gene flow from single unphased genomes and a two-locus statistic

Abstract

The emerging picture of hominin evolution is one of complexity, population structure, and gene flow, which recent genomic inference approaches have begun to resolve. Among these are methods based on two-locus statistics, which summarize information contained in genealogical correlations between linked loci. Although the inclusion of ancient samples could provide increased power to distinguish between competing models, these methods typically rely on large samples from present-day populations, and it remains challenging to apply them to ancient DNA (aDNA), which is sparsely sampled, unphased, and time-stratified. Here we develop an inference framework based on a set of multi-population two-locus statistics that are applicable to aDNA because they can be estimated from single unphased diploid genomes. We connect these statistics to an existing system of two-locus summaries and use them to model divergence and gene flow among populations represented by seven ancient hominin individuals and one contemporary human. We infer a demographic model with two episodes of gene flow from early anatomically modern humans (AMH) to Neanderthals and an introgression from an unsampled hominin lineage to Denisovan ancestors, broadly consistent with previous work. We also learn parameters of ancient Eurasian AMH population structure, reinforcing previous findings that early European farmers traced a large fraction of their ancestry to a lineage which split early from other non-African AMH and received little or no introgression from Neanderthals. Using both simulation and empirical data, we show that accurately estimating parameters associated with multiple gene flow episodes requires their joint inference due to their correlated effects on diversity.