Detecting population continuity and ghost admixture among ancient genomes

Ancient DNA (aDNA) can prove a valuable resource when investigating the evolutionary relationships between ancient and modern populations. Performing demographic inference using datasets that include aDNA samples however, requires statistical methods that explicitly account for the differences in drift expected among a temporally distributed sample. Such drift due to temporal structure can be challenging to discriminate from admixture from an unsampled, or "ghost", population, which can give rise to very similar summary statistics and confound methods commonly used in population genetics. Sequence data from ancient individuals also have unique characteristics, including short fragments, increased sequencing-error rates, and often limited genome-coverage that poses further challenges. Here we present a novel and conceptually simple approach for assessing questions of population continuity among a temporally distributed sample. We note that conditional on heterozygote sites in an individual genome at a particular point in time, the mean proportion of derived variants at those sites in other individuals has different expectations forwards in time and backwards in time. The difference in these processes enables us to construct a statistic that can detect population continuity in a temporal sample of genomes. We show that the statistic is sensitive to historical admixture events from unsampled populations. Simulations are used to evaluate the power of this approach. We investigate a set of ancient genomes from Early Neolithic Scandinavia to assess levels of population continuity to an earlier Mesolithic individual.