Estimating human mobility in Holocene Western Eurasia with large-scale ancient genomic data

The recent increase in openly available ancient human DNA samples allows for new, large-scale meta analysis applications. Trans-generational past human mobility is one of the key aspects that ancient genomics can contribute to, since changes in ancestry – unlike cultural changes seen in the archaeological record – necessarily reflect movements of people. Here we present a new algorithm to quantify past human mobility from large ancient genomic datasets. The key idea of the method is for each individual to compare a hypothetical genetic “origin” point with its actual burial point in space. This is achieved by first creating an interpolated ancestry field through space and time based on Multidimensional scaling and Gaussian process regression, and then using this field to map the ancient individuals into space according to their genetic profile. We apply this new algorithm to a dataset of 3191 aDNA samples with genome-wide data from Western Eurasia in the last 10,000 years and derive a diachronic measure of mobility for subregions in Western, Central, Southern and Eastern Europe. For regions and periods with sufficient data coverage, our mobility estimates show general concordance with previous results, but also reveal new signals of movements beyond the well-known key events. Significance Statement Ancient human DNA (aDNA) extracted from archaeological contexts (e.g. burials) allows to reconstruct past population movements. Relevant methods work by calculating proportions of shared ancestry among individuals or groups in order to answer specific, regional research questions. Here, we propose a largescale algorithm to quantify human mobility through time and space using bulk aDNA data. The algorithm has two core components: i) Interpolation of the spatio-temporal distribution of genetic ancestry to obtain a continuous ancestry information field and ii) estimation of the spatial origin of each input sample by projecting its ancestry into this field. We apply this to thousands of published genomic samples in the last 10,000 years to trace diachronic mobility patterns across Western Eurasia.