# Reconstructing the history of polygenic adaptation using ancestral recombimation graphs

> **NIH NIH F32** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2020 · $41,854

## Abstract

Project Summary/Abstract
 The main objective of this proposal is to develop methods for reconstructing the
evolution of polygenic traits using contemporary genetic sequence data. Genome-wide
association studies (GWAS) are revealing that most human traits—including traits of biomedical
interest—are polygenic, meaning that they are influenced by small-effect variants at many
genetic loci. Standard population-genetic methods for reconstructing evolutionary history are
underpowered for polygenic traits—when there are many variants of small effect, signatures of
natural selection are spread across the genome and subtle at any one locus. Dr. Coop (sponsor)
and others have developed methods for detecting selection on polygenic traits, but existing
methods are limited: they do not reveal the timing and strength of selection, and they do not
reveal the course of either selected or neutral change in the trait over time.
 The applicant will develop methods that improve on existing approaches by working
with ancestral recombination graphs (ARGs), a rich representation of a sample’s history of
recombination and common-ancestor events across the genome. ARG estimation from whole-
genome data is improving rapidly, and ARG-based approaches are positioned to benefit from
these advances. AIM 1 will produce statistical methods that estimate a population’s historical
mean values for a trait’s polygenic score, as well as statistical tests to identify trait histories that
are inconsistent with neutral evolution. These procedures will be assessed for robustness in
extensive simulations. AIM 2 will apply the methods of Aim 1 to human genomic data using
GWAS effect sizes and genomic data from the 1000 Genomes project. The applicant will seek to
replicate and refine previous results suggesting recent natural selection on height in Europe and
examine many other phenotypes.
 The applicant will receive training in the population genetics of natural selection,
quantitative genetics, and the processing and analysis of whole-genome data. The sponsor and
the institutional environment are well-suited to support the applicant in this training. The new
skills gained by the applicant will equip him to answer questions about polygenic traits
throughout a research career in statistical population genetics.

## Key facts

- **NIH application ID:** 9840393
- **Project number:** 5F32GM130050-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Michael Donald Edge
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $41,854
- **Award type:** 5
- **Project period:** 2019-02-01 → 2020-08-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9840393

## Citation

> US National Institutes of Health, RePORTER application 9840393, Reconstructing the history of polygenic adaptation using ancestral recombimation graphs (5F32GM130050-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9840393. Licensed CC0.

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