# Quantitative and Predictive Analysis of 5' Splice Site Recognition by U1 snRNP using Massively Parallel Arrays

> **NIH NIH F32** · UNIVERSITY OF WISCONSIN-MADISON · 2021 · $65,610

## Abstract

Project Summary
Alternative splicing of precursor messenger RNA (pre-mRNA) greatly expands protein diversity and is a crucial
determinant of cellular activity in eukaryotes. Each splicing event begins with the binding of the U1 small nuclear
ribonucleoprotein (snRNP) to a 5' splice site (5'SS) at an exon-intron boundary. Mutations in both the 5'SS
sequence or the U1 snRNA can cause aberrant splicing and are associated with numerous human diseases
including cancer and neuromuscular disorders. Strikingly, our understanding of how a 5'SS is selected by U1
snRNP remains poorly understood. The proposed work aims to adapt and develop new in vitro techniques to
perform high throughput biochemistry and uncover the physical rules of 5'SS selection by U1 snRNP. In Aim 1,
the recently developed RNA on a massively parallel array (RNA-MaP) method will be applied to measure the
thermodynamics and kinetics of U1 snRNP binding to thousands of unique 5'SS sequences simultaneously.
These experiments will lead to the first predictive model of 5'SS sequence on U1 recognition grounded in
biochemical understanding and reveal how pathogenic 5'SS mutations alter these interactions. In Aim 2,
mutations in the 5'SS binding region of the U1 snRNA that are pathogenic or therapeutic will be investigated
using RNA-MaP. These results will reveal the affinity landscape driving 5'SS selection by each mutant and will
aid the design of splicing-corrective therapeutics. Technical Aim 1 will extend the RNA-MaP technique to
generate a new biochemical assay that measures both protein-RNA interactions and splicing kinetics across
thousands of sequences diverse RNAs. This technique will be used to investigate the relationships between
5'SS sequences, intron selection, and intron removal during splicing. Overall, these aims will address long-
standing questions in the field and enable new measurements that will be vital for future studies of pre-mRNA
splicing and its alteration in disease. In addition, these aims provide an entry point for developing expertise in
RNA biochemistry and next-generation sequencing which will help the applicant successfully transition into an
independent position to study the biophysical basis of gene expression.

## Key facts

- **NIH application ID:** 10311645
- **Project number:** 1F32GM143780-01
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** David S White
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $65,610
- **Award type:** 1
- **Project period:** 2021-08-01 → 2024-07-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10311645

## Citation

> US National Institutes of Health, RePORTER application 10311645, Quantitative and Predictive Analysis of 5' Splice Site Recognition by U1 snRNP using Massively Parallel Arrays (1F32GM143780-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10311645. Licensed CC0.

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