Detecting range expansions from genetic data

TL;DR

This paper introduces a genetic statistic called the directionality index to detect and locate recent range expansions, outperforming traditional methods like Fst and heterozygosity clines, with applications to human data.

Contribution

The paper presents a novel statistic, the directionality index, for identifying and inferring the origin of range expansions from genetic data, including complex scenarios.

Findings

The directionality index effectively detects recent range expansions.

It outperforms Fst and heterozygosity clines in power.

Application to human data demonstrates practical utility.

Abstract

We propose a method that uses genetic data to test for the occurrence of a recent range expansion and to infer the location of the origin of the expansion. We introduce a statistic for pairs of populations $\psi$ (the directionality index) that detects asymmetries in the two-dimensional allele frequency spectrum caused by the series of founder events that happen during an expansion. Such asymmetry arises because low frequency alleles tend to be lost during founder events, thus creating clines in the frequencies of surviving low-frequency alleles. Using simulations, we further show that $\psi$ is more powerful for detecting range expansions than both $F_{ST}$ and clines in heterozygosity. We illustrate the utility of $\psi$ by applying it to a data set from modern humans and show how we can include more complicated scenarios such as multiple expansion origins or barriers to migration in the model.