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

Area of Science:

• Genomics
• Population Genetics
• Computational Biology

Background:

• Ancient human DNA (aDNA) availability enables large-scale meta-analyses.
• Ancient genomics is crucial for understanding trans-generational human mobility, as genetic ancestry changes reflect population movements.
• Existing methods may not fully capture the spatiotemporal dynamics of past human mobility.

Approach:

• Developed a novel algorithm for spatiotemporal mapping of genetic profiles.
• Utilized multivariate statistics and Gaussian process regression to create an interpolated ancestry field through space and time.
• Mapped ancient individuals into past space based on their genetic profiles to estimate mobility.

Key Points:

• Applied the algorithm to 3138 ancient DNA samples from Western Eurasia spanning the last 10,000 years.
• Derived spatial probability surfaces of genetic similarity for individuals in their past contexts.
• Generated diachronic measures of mobility for subregions in Europe.

Conclusions:

• The algorithm provides direct estimates of past human mobility from ancient genomic data.
• Results show concordance with previous findings, offering a meta-perspective on genetic changes and mobility.
• This method enhances our understanding of population dynamics and genetic ancestry in Western Eurasia.