Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions

Abstract

Sex-biased admixture can be inferred from ancestry-specific proportions of X chromosome and autosomes. In a paper published in the American Journal of Human Genetics, Micheletti et al.¹ used this approach to quantify male and female contributions following the transatlantic slave trade. Using a large dataset from 23andMe, they concluded that African and European contributions to gene pools in the Americas were much more sex biased than previously thought. We show that the reported extreme sex-specific contributions can be attributed to unassigned genetic ancestry as well as the limitations of simple models of sex-biased admixture. Unassigned ancestry proportions in the study by Micheletti et al. ranged from ∼1% to 21%, depending on the type of chromosome and geographic region. A sensitivity analysis illustrates how this unassigned ancestry can create false patterns of sex bias and that mathematical models are highly sensitive to slight sampling errors when inferring mean ancestry proportions, making confidence intervals necessary. Thus, unassigned ancestry and the sensitivity of the models effectively prohibit the interpretation of estimated sex biases for many geographic regions in Micheletti et al. Furthermore, Micheletti et al. assumed models of a single admixture event. Using simulations, we find that violations of demographic assumptions, such as subsequent gene flow and/or sex-specific assortative mating, may have confounded the analyses of Micheletti et al., but unassigned ancestry was likely the more important confounding factor. Our findings underscore the importance of using complete ancestry information, sufficiently large sample sizes, and appropriate models when inferring sex-biased patterns of demography. This Matters Arising paper is in response to Micheletti et al.,¹ published in American Journal of Human Genetics. See also the response by Micheletti et al.,² published in this issue.

Keywords: Americas; admixture; genetic ancestry; mathematical models; population genetics; sex bias; slave trade.