# Analysis of functional genetic variants in RNA processing and expression

> **NIH NIH U01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $531,283

## Abstract

Project Summary
The goal of this project is to functionally annotate genetic variants in post-transcriptional
regulation of RNA expression, which extends and complements the current focus of ENCODE
data analysis. Recently, tremendous success has been achieved in constructing a catalog of
genetic variants in disease genomes or across population. The next great challenge is to
identify causal variants and elucidate their potential function in biological and disease
processes. To this end, research efforts have been directed to studying variants located in
protein-coding, promoter, and splice site regions due to their apparent impacts on gene
expression. However, many of the newly identified disease-associated variants reside in other
non-coding regions, such as introns, that may confer regulatory function to the related gene.
The mechanisms of these variants have been hard to decipher. It is expected that many of them
may function at the post-transcriptional level, thus affecting mRNA expression. In human, a
myriad of processes mediate RNA expression at the post-transcriptional stage, such as splicing,
editing, polyadenylation and mRNA decay. Post-transcriptional regulation is extremely versatile,
yet closely regulated, affecting most human genes. Despite the importance, how to accurately
identify functional genetic variants in these processes remains a key question in the field. To
address this question, the large collection of ENCODE expression and protein-binding data
represent an invaluable resource. We will develop novel methodologies to make full use of the
ENCODE and other publicly available data sets, complemented by further bioinformatic
prediction and experimental validations. This work will allow a previously unattained level of
understanding of genetic variants in post-transcriptional regulation of RNA expression and
provide new means to tackle the imperative task of functional annotations of genetic variants.

## Key facts

- **NIH application ID:** 10240961
- **Project number:** 3U01HG009417-04S2
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Xinshu Grace Xiao
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $531,283
- **Award type:** 3
- **Project period:** 2021-02-01 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10240961

## Citation

> US National Institutes of Health, RePORTER application 10240961, Analysis of functional genetic variants in RNA processing and expression (3U01HG009417-04S2). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10240961. Licensed CC0.

---

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