Principal Component Analysis under Population Genetic Models of Range Expansion and Admixture

In a series of highly influential publications, Cavalli-Sforza and colleagues used principal component (PC) analysis to produce maps depicting how human genetic diversity varies across geographic space. Within Europe, the first axis of variation (PC1) was interpreted as evidence for the demic diffusion model of agriculture, in which farmers expanded from the Near East similar to 10,000 years ago and replaced the resident hunter-gatherer populations wth little or no interbreeding. These interpretations of the PC maps have been recently questioned as the original results can be reproduced under models of spatially covarying allele frequencies without any expansion. Here, we study PC maps for data simulated under models of range expansion and admixture. Our simulations include a spatially realistic model of Neolithic farmer expansion and assume various levels of interbreeding between farmer and resident hunter-gatherer populatons. An important result is that under a broad range of conditions, the gradients in PC1 maps are oriented along a direction perpendicular to the axis of the expansion, rather than along the same axis as the expansion. We propose that this surprising pattern is an outcome of the allele surfing phenomenon, which creates sectors of high allele-frequency differentation that allign perpendicular to the direction of the expansion.