Beyond straight lines: migration costs considering geography enhance tracing human genetic ancestry

Reconstructing the spatio-temporal history of human genetic lineages is fundamental to understanding human evolution and population distribution. While succinct tree sequences and maximum parsimony reconstruction methods applied to large-scale genomic data have improved our ability to trace the geographic history of genetic ancestry, they have essentially relied on Euclidean distances, which ineluctably ignore opportunity costs that have shaped human mobility patterns since the earliest human migrations and settlement formations. Here we propose an approach to incorporate realistic geographical migration costs through a human movement friction surface. Using simulated data mimicking the dispersal process of human migration out of Africa, we found that, compared to the Euclidean-based benchmark (M0), the proposed friction-based model (Mf) leads to a more accurate estimation of the geographical origin (n = 346, accuracy M0 = 0.18, f = 0.27) and genetic flux (n = 30, MSE M0 = 0.20, Mf = 0.12) through the Mandeb corridor in the Horn of Africa. We further illustrate these findings in a case study, in which our model seems to better identify plausible human migration paths from Eurasia to the Americas by accounting for geographic factors affecting migration opportunity costs, such as the Alaska Range and Rocky Mountains that represent physical barriers that constraint migration. While important migration drivers such as climate change, technological advances, social organization, and culture remain omitted here, our work highlights the importance of explicitly accounting for geographic constraints to improve our ability to reconstruct past human mobility and, ultimately, understand the evolution of human populations.