The persistence and loss of hard selective sweeps amid admixture in ancient Eurasians

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Authors: Mariana Harris, Ziyi Mo, Adam C. Siepel, Nandita R. Garud
Cited by: 1
References: 83

Abstract

The extent to which human adaptations have persisted throughout history despite strong eroding demographic events such as admixture, genetic drift, and fluctuations in selection pressures remains unknown. Understanding which adaptations were resilient to such forces may shed light on traits that were important for humans across time. Yet, detecting selection from ancient DNA is challenging due to severe degradation of the data and/or signal. Here we detect selective sweeps using a domain-adaptive neural network (DANN) trained on simulated data and applied to more than 800 ancient and modern Eurasian genomes spanning the last 7,000 y. We show that the DANN can account for simulation misspecification, or discrepancies between simulations and real ancient DNA, improving the ability to detect sweeps in real data compared to standard convolutional neural networks or standard statistics. Application of the DANN to data recovered 16 known sweeps at loci including LCT , HLA , KITLG, and OCA2/HERC2 , and revealed 32 novel sweeps. All identified sweeps were classified as hard, consistent with historically low population sizes. While some sweeps were lost over time, 14 sweeps at loci involved in functions including neuronal, reproductive, pigmentation, and signaling traits persisted from the earliest to the most recent time periods. In most cases, the most frequent haplotype remained at high frequency across time. Together, these results indicate that hard sweeps predominated in ancient Eurasians and that several ancient selective events were resilient to strong admixture events.

Fields of Study & Subjects

Genetic Associations and Epidemiology Language and cultural evolution Forensic and Genetic Research

Publication details

Journal / source
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Volume
123
Issue
17
Pages
e2528672123–e2528672123
Publication date
20 April 2026
Language
EN