# Inferring the evolutionary history of admixed populations

> **NIH NIH R35** · DUKE UNIVERSITY · 2022 · $372,164

## Abstract

Admixture—gene flow between previously isolated populations—has shaped the genomes of almost all human
populations. The mosaic ancestry of admixed populations varies along their genomes and between individuals,
leading to differences in phenotypic variation and disease risk. Indeed, admixture is one of the fastest
evolutionary processes to dramatically change the composition of a population. Yet, methods to study the
evolutionary history of admixed populations are lacking. Admixed populations are often considered as simple
linear combinations of their sources, missing variation in mating patterns and migration rates over time. Over
the next five years, the Goldberg lab will combine quantitative methods development with empirical data
analysis to addresses two fundamental components of the evolutionary history of admixed populations: 1)
inference of demographic history and its consequences for neutral and deleterious patterns of variation, and 2)
characterization of loci under positive selection before and after admixture. Specially, we will extend our
mechanistic model of sex-specific admixed to allow for non-random mating patterns empirically observed in
admixed populations. We will apply this model to infer the demographic history of Cape Verdeans, with
Portuguese and West African ancestry, testing for differences in mating patterns between islands that differ in
their size and colonization history. Under this model, we will also use Cape Verde as a case study of the
relationship between demography and deleterious variation in admixed populations. Next, we will develop new
statistics to infer positive selection using admixed genomes both before and after admixture. Admixture can
both mask classic signatures of positive selection, and provide new genetic material upon which selection can
act. Therefore, methods that account for the specific demographic and selective signatures of admixed
populations are necessary. We will incorporate these statistics into a simulation-based learning method to
make it easily accessible. Finally, we will apply our new statistics to move beyond identification of putatively
selected loci to characterize the strength and timing of selection in multiple admixed African diaspora
populations in different environments. This proposal enhances our understanding of evolutionary processes in
admixed populations, produces usable statistical methods, and elucidates the population and selective history
of diverse global populations. The Goldberg lab is uniquely positioned to accomplish these goals because of
our experience combining exact mathematical models with realistic inference frameworks to study the
processes generating genetic variation in admixed groups.

## Key facts

- **NIH application ID:** 10450673
- **Project number:** 5R35GM133481-04
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Amy Goldberg
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $372,164
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10450673

## Citation

> US National Institutes of Health, RePORTER application 10450673, Inferring the evolutionary history of admixed populations (5R35GM133481-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10450673. Licensed CC0.

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