# Programmable RNA-targeting CRISPR-Cas tools to study RNA biology

> **NIH NIH R35** · UNIVERSITY OF ROCHESTER · 2020 · $385,000

## Abstract

Summary
Technological advances such as next-generation sequencing and single-cell analysis have opened the flood
gates for RNA analysis, revealing that the transcriptome is significantly more complex than previously thought,
both with respect to the diversity of RNA transcripts, their temporal expression dynamics, and their cellular
location. Moreover, thousands of dysregulated RNAs have been observed in diseases including cancer and
neurodegenerative disorders. These observations underscore the dire need for new molecular tools to precisely
dissect RNA function in health and disease. The goal of my research program is to harness the unprecedented
power of CRISPR-Cas systems to create a versatile range of methods to precisely manipulate virtually any RNA,
and to use these tools to explore fundamental knowledge gaps in RNA biology. This proposal specifically focuses
on addressing the following knowledge gaps: 1) Despite the technological advances in harnessing RNA-targeting
CRISPR-Cas enzymes Cas9 and Cas13 for research and clinical applications, we still do not understand the
principles of gRNA selection for efficient and tunable RNA-targeting. This problem precludes the facile
development of a number of RNA-targeting applications and underscores the need for a thorough interrogation
of gRNA selection. Our goal here is to develop a model to predict highly-active gRNAs for Cas9/Cas13 RNA-
targeting in human cells. We will use a combination of high-throughput RNA:protein interactome methods, flow-
cytometry based gRNA screens and machine learning to precisely define features of highly active RNA-targeting
gRNAs for RNA-binding and knockdown for Cas9 and Cas13. 2) The vast majority of human RNAs are
alternatively spliced, and RNA splicing defects are common in cancers and neurological diseases. However, our
understanding of the downstream functional effects of splicing in a majority of cases is rudimentary. To address
this issue, we will develop a toolbox of robust, multiplexable Cas-based splicing factors to offer an unprecedented
opportunity to study the functional consequences of alternative splicing.
that can determine in a single step both the identity of proteins bound to a
And 3) There is a paucity of methods
specific RNA and their location on that
RNA. The development of such an approach will enable us to determine the spatial arrangement of proteins on
specific RNAs to dissect their dynamic deposition in range of RNA processes such as transcription, 3ʹ-end and
micro-RNA processing, and lncRNA function. To address this issue, we propose to develop a genetically
encodable Cas-based RNA proximity-labeling strategy to precisely identify proteins that bind in close proximity
to a specific RNA sequence. We will then use this approach to identify protein factors involved in regulating
microprocessor (Drosha/DGCR8) activity at specific primary micro-RNA loci. These research goals fully align
with the NIGMS 5 Year Strategic Plan, through the develop...

## Key facts

- **NIH application ID:** 9984455
- **Project number:** 5R35GM133462-02
- **Recipient organization:** UNIVERSITY OF ROCHESTER
- **Principal Investigator:** Mitchell O'Connell
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $385,000
- **Award type:** 5
- **Project period:** 2019-08-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9984455

## Citation

> US National Institutes of Health, RePORTER application 9984455, Programmable RNA-targeting CRISPR-Cas tools to study RNA biology (5R35GM133462-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9984455. Licensed CC0.

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