Improving Selection Detection with Population Branch Statistic on Admixed Populations.

Abstract

Detecting natural selection signals in admixed populations can be problematic since the source of the signal typically dates back prior to the admixture event. On one hand, it is now possible to study various source populations before a particular admixture thanks to the developments in ancient DNA (aDNA) in the last decade. However, aDNA availability is limited to certain geographical regions and the sample sizes and quality of the data might not be sufficient for selection analysis in many cases. In this study, we explore possible ways to improve detection of pre-admixture signals in admixed populations using a local ancestry inference approach. We used masked haplotypes for population branch statistic (PBS) and full haplotypes constructed following our approach from Yelmen et al. (2019) for cross-population extended haplotype homozygosity (XP-EHH), utilizing forward simulations to test the power of our analysis. The PBS results on simulated data showed that using masked haplotypes obtained from ancestry deconvolution instead of the admixed population might improve detection quality. On the other hand, XP-EHH results using the admixed population were better compared with the local ancestry method. We additionally report correlation for XP-EHH scores between source and admixed populations, suggesting that haplotype-based approaches must be used cautiously for recently admixed populations. Additionally, we performed PBS on real South Asian populations masked with local ancestry deconvolution and report here the first possible selection signals on the autochthonous South Asian component of contemporary South Asian populations.