# Natural Selection in Admixed Populations

> **NIH NIH F32** · DUKE UNIVERSITY · 2021 · $48,816

## Abstract

PROJECT SUMMARY
Human populations across the globe have been shaped by admixture--gene flow between previously diverging
groups. The sudden combination of previously distinct genotypes through admixture can rapidly change allele
frequencies, heterozygosity, and patterns of linkage-disequilibrium. These processes create new material for
both positive and negative selection to act upon, but also depend on the independent adaptive histories of the
source populations. Admixed populations also provide powerful test cases for understanding how selection
shapes evolution in general, since changes in ancestry patterns in admixed populations are much easier to
observe on short timescales compared to changes in allele frequencies in source populations. Despite the
ubiquity of admixture, current methods for inferring selection do not consider how admixture changes the
action of selection and the genetic signatures that it leaves. Standard methods to detect selection do not work
in admixed populations; since selection post-admixture is often on a very short timescale, and admixture-
induced shifts in allele frequencies and haplotype structure can obscure classic signals of selection. The lack
of appropriate methods constrains our understanding of disease risk and human evolution. Further, few studies
have addressed how recombination modulates selection in admixed populations by shuffling haplotypes from
distinct source populations and influencing the exposure of deleterious variation. To address these gaps, this
proposal tests how two important evolutionary forces--positive and negative selection--shape the genetics of
admixed populations. This proposal combines methods development and empirical analyses to provide insight
into how admixture shapes fundamental evolutionary processes in multiple admixed African diaspora
populations. Specific Aim 1 will develop statistics to detect positive selection in admixed populations by
leveraging local ancestry information to incorporate the effects of admixture on haplotype structure. These new
statistics will be integrated into open-access software and applied to infer selection in both simulated and
empirical data representing diverse demographic scenarios. Specific Aim 2 will test how admixture combines
the distinct distributions of deleterious variation found in source populations. Tracking the frequencies of
segregating deleterious alleles and their membership in runs-of-homozygosity will determine how admixture
and the landscape of recombination modulate the exposure of deleterious variation. Characterizing the
dynamics of deleterious variation in admixed populations and their source populations will provide a window
into how admixture changes genetic load. This proposal will advance methodology for the study of natural
selection in admixed populations and elucidate how both positive and negative selection shape patterns of
genetic variation and disease risk in understudied admixed populations.

## Key facts

- **NIH application ID:** 10212352
- **Project number:** 5F32GM139313-02
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Katharine Love Korunes
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $48,816
- **Award type:** 5
- **Project period:** 2020-07-01 → 2022-03-05

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10212352

## Citation

> US National Institutes of Health, RePORTER application 10212352, Natural Selection in Admixed Populations (5F32GM139313-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10212352. Licensed CC0.

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