# Therapeutic strategies for microsatellite expansion diseases using RNA-targeting CRISPR/Cas

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $590,464

## Abstract

Project Summary
The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas system has become widely
adopted for DNA recognition, enabling applications such as genome editing and recruiting effector proteins to
DNA to affect transcription or enable imaging. Recently in Nelles et al, Cell, 2016, we showed that with
modifications, catalytically dead Cas9 with a modified oligonucleotide containing the PAM recognition
sequence is able to bind specific mRNAs in living mammalian cells and is able to track their movement,
opening up the potential for many RNA applications of Cas proteins. In this proposal, we aim at developing a
adeno-associated virus (AAV)-based therapeutic strategy for myotonic dystrophy, a microsatellite expansion
disease characterized by expanded CTG repeats, using RNA-targeting CRISPR/Cas9 (RCas9). We will
perform in vivo safety and efficacy studies of our AAV-based therapy and evaluate the hypothesis that
alternative RNA processing biomarkers are reliable for measuring treatment efficacy of RCas9 in myotonic
dystrophy. If successful, we will have taken a significant step forward in developing a treatment for a class of
microsatellite expansion diseases.!

## Key facts

- **NIH application ID:** 10171924
- **Project number:** 5R01NS103172-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** MAURICE SCOTT SWANSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $590,464
- **Award type:** 5
- **Project period:** 2017-09-22 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10171924

## Citation

> US National Institutes of Health, RePORTER application 10171924, Therapeutic strategies for microsatellite expansion diseases using RNA-targeting CRISPR/Cas (5R01NS103172-05). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10171924. Licensed CC0.

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