# Rapid Evolution of Genomic Architecture and Multi-omics Traits

> **NIH NIH R35** · UNIVERSITY OF MARYLAND BALTIMORE · 2020 · $463,057

## Abstract

Abstract
The evolution of phenotypic traits is important both for our understanding of evolutionary theory, but also for
genetic epidemiology and statistical genetics. Through this proposal, I will use large scale sequencing and
multi-omics profiling to test the rapidness of trait evolution. To test this hypothesis, I will advance our
understanding of rare variation and mutation, fine-scale population structure, and multi-omics traits and
disease.
Current Projects
1) Native American evolution and health. In a collaboration I started with the Peruvian National Institute
of Health, we have sequence 150 predominantly Native American ancestry individuals from Peru, recently
published in PNAS and now are evaluating the global evolutionary dynamics of the Fatty Acid Desaturase
(FADS) gene cluster, which is critical to poly-unsaturated fatty acid regulation.
2) Rare variants in TOPMed. Within the Trans-Omics for Precision Medicine (TOPMed) project, I
developed a new means of evaluating different annotation categories of rare variation between closely related
cohorts. I find that functional variation (e.g. non-sense) are also more susceptible to population structure.
3) Mutation by ancestry. In two projects, I test for differences in mutational patterns by ancestry. In the
first, I demonstrate that cancer cell lines have differences in somatic mutation rates by ancestry. In the second,
I show that Amish individuals have on average 3 less de novo mutations than non-Founder Europeans.
Future Projects
1) Rare variants and study design. Expanding from our analysis in current project 3, we will extend this
methodology to compare variation not by categories, but for some continuous values for in silico predictors of
deleteriousness and for a wider range of methodologies.
2) Rare variant IBD. We will develop a new method to identify small segments that are identical-by-
descent (IBD) by leveraging rare variation. This will be critical in how we model the genomic relationship matrix
for association models.
3) Mutation rate variation by ancestry. Building from current project 3, we will use the de novo mutation
counts we identify in trios across TOPMed as a phenotypic outcome for a genome-wide association analysis.
Preliminary findings show some promising results that we will follow-up using molecular assays in yeast.
4) Evolutionary systems biology of rapidly changing traits. Using this program, we will develop an
Approximate Bayesian Computation (ABC) framework to identify complex systems biology models of disease
traits mediated by molecular phenotypes.

## Key facts

- **NIH application ID:** 10003377
- **Project number:** 5R35HG010692-02
- **Recipient organization:** UNIVERSITY OF MARYLAND BALTIMORE
- **Principal Investigator:** Timothy David O'Connor
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $463,057
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10003377

## Citation

> US National Institutes of Health, RePORTER application 10003377, Rapid Evolution of Genomic Architecture and Multi-omics Traits (5R35HG010692-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10003377. Licensed CC0.

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