# Novel population-genetic methods for localizing targets of natural selection in diverse human genomes

> **NIH NIH R35** · BROWN UNIVERSITY · 2022 · $373,985

## Abstract

PROJECT SUMMARY.
The PI's research program in population genetics focuses on the coalescent-based inference of population his-
tories from whole genomes, and the determination of genetic basis of adaptation and disease at multiple biolog-
ical scales—from mutations to genes to gene subnetworks. In the genomic era, computational and statistical
methods are essential for identifying candidate adaptive and disease-associated mutations in humans, in whom
mapping via linkage studies is challenging and costly. State-of-the-art approaches that scan genome-wide for
signatures of selection or association with phenotype state are routinely applied to samples from one homoge-
neous ancestry, rely on arbitrary thresholds for interpreting results, and produce results at genomic scales that
can be difficult to connect to biological mechanism (for example, analyzing linkage blocks or sliding genomic
windows). Thus, despite the enormous investments made by the NIH and biobanks around the world to generate
large-scale genomic datasets from diverse individuals, methods for analyzing such datasets are lagging behind.
This application describes a series of projects motivated by answering three fundamental questions in human
population genetics: (1) what role has balancing selection played in human adaptation? (2) to what extent has
adaptive evolution versus non-adaptive processes shaped human genomes? (3) to what extent do the genetic
architectures of human traits vary by ancestry? The overall strategy for future research plans draws on the PI's
expertise in coalescent theory, Bayesian inference, population genetics, and statistical genetics to produce new
frameworks for analyzing patterns in and evolutionary processes underlying multiethnic genomic datasets. The
outcomes of the research described in this MIRA application will give new insight into the interaction between
selection and dynamic population histories in generating human genetic diversity, while determining the different
modes of selection shaping human phenotypes and diseases.

## Key facts

- **NIH application ID:** 10321900
- **Project number:** 5R35GM139628-02
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Sohini Ramachandran
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $373,985
- **Award type:** 5
- **Project period:** 2021-01-01 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10321900

## Citation

> US National Institutes of Health, RePORTER application 10321900, Novel population-genetic methods for localizing targets of natural selection in diverse human genomes (5R35GM139628-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10321900. Licensed CC0.

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