# RNA Structurome in Post-Transcriptional Regulation

> **NIH NIH R35** · UNIVERSITY OF MASSACHUSETTS AMHERST · 2020 · $136,162

## Abstract

PROJECT SUMMARY/ABSTRACT
My research program focuses on development and application of computational approaches to determine the
relationship between RNA structure and function for all RNA transcripts, or the transcriptome. RNA structure
plays key roles in almost every step of RNA synthesis and function, and has significant impacts on biological
processes and human diseases. Recent high-throughput technologies have begun to revolutionize dissection
of RNA structures at the transcriptome level (termed RNA structuromes). However, little is known of the
relationship between RNA structure and function, largely because current computational approaches lack the
capacity to fully utilize the available high-throughput datasets to reveal the characteristics and functions of RNA
structuromes. To overcome these limitations, I am building a unique research program to develop novel
computational approaches to characterize, analyze and interpret the function of RNA structuromes. Over the
next five years, the goals of my research program are to comprehensively elucidate RNA structuromes and
precisely predict the functions of RNA structure in RNA-protein interactions and control of translation of RNA
into proteins. We will develop a novel analytic framework for inferring RNA structuromes that integrates
available high-throughput datasets and enables analysis of in vivo RNA structures. We will use this framework
for analyses using specific cellular model systems, including characterizing the diversity of specific RNA
structures that regulate RNA-protein interactions in a human cancer cell line, and dissecting the roles of RNA
structure in modulating interactions between RNA and proteins shown to be essential for translational
regulation of stem cell self-renewal and early embryogenesis. We will validate our computational predictions by
collaborating with experimental biologists with relevant expertise. In the immediate future we will apply our
approaches to study the roles of RNA structure in human diseases by collaborating with biologists working on
the mechanisms of human diseases, including neurological disorders and cancer. Successful development of
our approaches will allow us, and the research community, to elucidate the logic from RNA structure to RNA
function and reveal their contributions to the etiology of numerous seemingly intractable human diseases. The
overall vision of my research program is to build our burgeoning network of collaborations with colleagues at
academic medical centers and hospitals across the nation that will, in the future, enable me to incorporate our
computational approaches (using RNA structurome analysis as a springboard) to advance our capacity to
render more accurate clinical diagnoses and prognoses, and develop novel, more effective therapies.

## Key facts

- **NIH application ID:** 10138470
- **Project number:** 3R35GM124998-05S1
- **Recipient organization:** UNIVERSITY OF MASSACHUSETTS AMHERST
- **Principal Investigator:** Zhengqing Ouyang
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $136,162
- **Award type:** 3
- **Project period:** 2017-08-15 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10138470

## Citation

> US National Institutes of Health, RePORTER application 10138470, RNA Structurome in Post-Transcriptional Regulation (3R35GM124998-05S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10138470. Licensed CC0.

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