# Large-scale characterization of the function of RNA regulatory elements

> **NIH NIH R35** · BAYLOR COLLEGE OF MEDICINE · 2022 · $480,000

## Abstract

PROJECT SUMMARY
 Once an RNA is transcribed in the nucleus, it is bound by RNA binding proteins and
other regulatory RNAs which control its sequence (by altering splicing), half-life (by modulating
RNA stability and decay) and translation (through mediation of ribosome initiation and
elongation) among other RNA processing steps. Individual RBP binding sites can have
significant physiological importance, as emphasized by the recent example of the drug
Spinraza, which is an antisense oligonucleotide that blocks a single RBP:RNA interaction in
order to cure Spinal Muscular Atrophy. Recent advances in genomics techniques have
dramatically increased our ability to identify the interaction sites for these regulatory RBPs and
RNAs, and we now have catalogs of over a million such interaction sites that are candidate RNA
regulatory elements. However, it is clear that only a small fraction of these elements truly
function as regulatory modules, as few show differences in RNA processing when the RBP is
knocked down or otherwise altered. As such, large-scale assays to sift through these elements
to identify the subset that are function are an essential missing piece in converting these
element databases into a useful tool for researchers interested in understanding whether human
genetic variation will alter RNA biology.
In this proposal, I describe my research group’s proposed efforts to address this major
knowledge gap in two areas:
 1. Using orthogonal approaches (rapid degradation of RBPs followed by genomics
 profiling to identify direct regulatory targets of RBPs and massively parallel reporter
 assays) to characterize which RBP binding sites confer regulation.
 2. Large-scale identification of regulatory targets for snoRNAs, snRNAs, and other
 regulatory RNAs through improved genomics techniques.
My extensive expertise in developing experimental and computational genomics methods to
map and understand RNA processing regulatory networks makes my newly founded lab an
ideal location to undertake these efforts, and build an improved global picture of the RNA
processing regulatory landscape. Further, it will support my efforts to develop an independent
research group that will lay the foundation to the broader effort to understand how human
genetic variation affects disease through mis-regulation of RNA processing.

## Key facts

- **NIH application ID:** 10487581
- **Project number:** 5R35HG011909-02
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Eric Lyman Van Nostrand
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $480,000
- **Award type:** 5
- **Project period:** 2021-09-10 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10487581

## Citation

> US National Institutes of Health, RePORTER application 10487581, Large-scale characterization of the function of RNA regulatory elements (5R35HG011909-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10487581. Licensed CC0.

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