# Determining the Molecular Chain of Causality Through Which Genetic Variants Affect Physiology

> **NIH NIH F32** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $74,292

## Abstract

Project Summary
A central goal of biomedical research is to decipher the genetic basis of complex traits. Though genome-wide
association studies (GWAS) have successfully detected thousands of variants that are associated with complex
cardiovascular, autoimmune, and neurological diseases, the molecular mechanisms are only known for a very
limited subset of these risk-associated variants. A mechanistic understanding of risk-associated variants is
difficult to ascertain because a vast majority of variants identified by GWAS are located in regulatory regions,
which suggests that gene expression variation contributes a substantial portion of the genetic risk for complex
human diseases. However, statistical power to map gene expression variation to genetic variants is often limited
by the small sample sizes used in such mapping studies. Our ability to characterize the molecular chain of
causality that links genetic variants to complex physiological traits is further limited because evidence is mounting
that regulatory variants often manifest their disease-associated effects in specific cell and tissue types. Because
of these limitations, I will leverage genetic diversity in the nematode Caenorhabditis elegans to achieve the
statistical power necessary to precisely quantify the cell- and tissue-specific effects that genetic variants have
on gene expression and physiology.
 We have recently developed a technique to identify genetic variants that affect cell- and tissue- specific
gene expression (expression quantitative trait loci or eQTL) in experimental C. elegans crosses. This approach
takes advantage of the short life cycle of C. elegans, the ability to easily generate hundreds of thousands of
recombinant individuals, and well-established methods to prepare cells for single-cell RNA sequencing to
associate single-cell transcript abundance with genetic variation segregating in experimental crosses. By
combining this single-cell eQTL mapping approach with experimental evolution, I have identified several genomic
regions that affect organismal fitness and tissue-specific gene expression variation of tens to hundreds of genes.
In Aim 1, I will extend the scope of these initial experiments to survey the effects of a wide-range of C. elegans
natural genetic variation on organismal fitness and cell- and tissue- specific gene expression. In Aim 2, I will use
the vast molecular and genetic toolkit available in C. elegans to determine if the same underlying variants affect
both tissue-specific gene expression and fitness. The completion of these aims will 1) characterize the cell- and
tissue-specific phenotypic effects of hundreds of thousands of genetic variants; 2) determine if tissue-specific
expression differences can affect organismal physiology; and 3) provide a mechanistic understanding of how
genetic variation mediates its effect on organismal physiology. Together, these insights will facilitate the
interpretation of how regulatory variation affects hum...

## Key facts

- **NIH application ID:** 10558458
- **Project number:** 5F32GM145132-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Stefan Zdraljevic
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $74,292
- **Award type:** 5
- **Project period:** 2022-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10558458

## Citation

> US National Institutes of Health, RePORTER application 10558458, Determining the Molecular Chain of Causality Through Which Genetic Variants Affect Physiology (5F32GM145132-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10558458. Licensed CC0.

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