# Multi-omics functional analysis of non-coding regulatory genome for genomic medicine

> **NIH NIH R35** · DUKE UNIVERSITY · 2020 · $483,000

## Abstract

ABSTRACT
Less than 2% of the human genome sequences are protein-coding genes. It has been shown that at least
80% of the non-coding sequences of human genome are associated with certain chromatin biochemical
modifications, and more than 70% of the genomic DNA can be transcribed into RNAs at various stages
during development. Accumulating evidence suggests that these non-coding regulatory sequences are
critical for spatial and temporal gene expression control. However, it remains challenging to determine
whether and how these non-coding regulatory DNA and RNA sequences play a causal in a variety biological
processes including diseases. In particular, questions of how the activity of enhancers are precisely
controlled, and how non-coding RNAs recruit effector proteins to control gene expression and genome
function, are largely unexplored. My overall hypothesis is that, cells integrate effector proteins and regulatory
non-coding DNA and RNA sequences to create a spectrum of functionalities for precise gene regulation
control. The rules governing these functionalities can then be derived by defining the key components, and
examining how each functions alone and in combination. To test this, we have developed a robust,
innovative multi-omics approaches allowing for comprehensive analysis of the molecular composition
associated with non-coding DNA and RNA sequences. My long-term goal is to develop a predictive and
functional understanding of the non-coding genome, which will elucidate how these regions can be
specifically targeted for genomic medicine. Toward this goal, we seek to achieve three major goals: 1)
Control enhancer activity through systematic and targeted recruitment of epigenetic effectors; 2) Define the
regulome of lncRNA-mediated gene regulation; 3). Develop innovative mouse model to study the function
and regulation of non-coding genome disease model in vivo. Our work will have a broad impact to advance
genomics research and genomics medicine by developing new approaches and new mouse models to
deepen our knowledge on non-coding regulatory genome.

## Key facts

- **NIH application ID:** 10048357
- **Project number:** 1R35HG011328-01
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Yarui Diao
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $483,000
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10048357

## Citation

> US National Institutes of Health, RePORTER application 10048357, Multi-omics functional analysis of non-coding regulatory genome for genomic medicine (1R35HG011328-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10048357. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*