Inferring Population Histories for Ancient Genomes Using Genome-Wide Genealogies

Ancient genomes anchor genealogies in directly observed historical genetic variation and contextualize ancestral lineages with archaeological insights into their geography and cultural associations. However, the majority of ancient genomes are of lower coverage and cannot be directly built into genealogies. Here, we present a fast and scalable method, Colate, the first approach for inferring ancestral relationships through time between low-coverage genomes without requiring phasing or imputation. Our approach leverages sharing patterns of mutations dated using a genealogy to infer coalescence rates. For deeply sequenced ancient genomes, we additionally introduce an extension of the Relate algorithm for joint inference of genealogies incorporating such genomes. Application to 278 present-day and 430 ancient DNA samples of >0.5x mean coverage allows us to identify dynamic population structure and directional gene flow between early farmer and European hunter-gatherer groups. We further show that the previously reported, but still unexplained, increase in the TCC/TTC mutation rate, which is strongest in West Eurasia today, was already present at similar strength and widespread in the Late Glacial Period similar to 10k-15k years ago, but is not observed in samples >30k years old. It is strongest in Neolithic farmers, and highly correlated with recent coalescence rates between other genomes and a 10,000-year-old Anatolian hunter-gatherer. This suggests gene-flow among ancient peoples postdating the last glacial maximum as widespread and localizes the driver of this mutational signal in both time and geography in that region. Our approach should be widely applicable in future for addressing other evolutionary questions, and in other species.

Automated summary

The study introduces a fast and scalable approach, Colate, for inferring ancestral relationships between low-coverage genomes without requiring phasing or imputation. The method leverages sharing patterns of mutations dated using a genealogy to infer coalescence rates. By applying this approach to modern and ancient DNA samples, the research identifies dynamic population structure and gene flow between early farmers and European hunter-gatherer groups.