# Statistical Methods to Study the Genetic Basis and Mechanisms of Trans Gene Regulation

> **NIH NIH R35** · UNIVERSITY OF CHICAGO · 2021 · $405,000

## Abstract

Project Summary
Genome wide association studies (GWAS) identified thousands of genetic loci associated with a variety of
complex traits and diseases. Nonetheless, deciphering how most GWAS variants are linked to diseases
remains exceptionally challenging, as the majority of these variants are noncoding. Noncoding variation can
affect the regulation of genes that are either physically nearby (in cis), or physically distant (in trans). Mounting
evidence suggest that genetic regulation in trans plays a dominant role in the control of gene expression and
disease risk. Thus, high-quality trans-eQTL and trans regulatory networks are critically needed to fully
understand how disease-associated variants flow through gene networks to affect causal genes and pathways.
However, most studies to date have solely focused on studying genetic regulation in cis owing to the extreme
difficulty in detecting trans-QTLs. Therefore, the lack of high-quality trans-eQTL maps represents a significant
gap in our understanding of disease mechanisms. In this grant, I propose to address this gap by developing
powerful statistical methods to produce high-quality, comprehensive maps of trans-QTLs in multiple human
tissues and cell types. We will use these maps to uncover major mechanisms that underlie trans genetic
regulation. Finally, we will develop novel methods to identify disease genes using our high-quality maps of
trans-eQTLs.

## Key facts

- **NIH application ID:** 10212423
- **Project number:** 5R35GM138084-02
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Xuanyao Liu
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $405,000
- **Award type:** 5
- **Project period:** 2020-07-07 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10212423

## Citation

> US National Institutes of Health, RePORTER application 10212423, Statistical Methods to Study the Genetic Basis and Mechanisms of Trans Gene Regulation (5R35GM138084-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10212423. Licensed CC0.

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