# Programmable RNA-targeting tools

> **NIH NIH R01** · BROAD INSTITUTE, INC. · 2020 · $1,124,060

## Abstract

Project Summary
Functional understanding of the genetic circuits underlying complex phenotypes, including disease, will require
robust, scalable tools for modulating and tracking transcriptional events. Currently, RNAi using shRNAs is the
only high-throughput approach available, and this is largely limited to transcript knockdown. This project aims
to develop a suite of broadly applicable tools for the interrogation of RNA based on CRISPR-Cas
enzymes that target RNA in a programmable manner. Tools for transcript knockdown, translation
upregulation, and transcript sensing will be developed, which, together, will enable dissection of genetic circuits
in a dynamic, high-throughput manner, accelerating nearly all areas of biomedical science.
The proposal is focused on four key goals:
1. Functionally and biochemically characterize RNA-targeting Cas enzymes, and then harness these
 enzymes for transcript editing in eukaryotic cells. Novel RNA-targeting CRISPR-Cas enzymes will be
 developed as platforms for transcript knockdown and translational upregulation. The availability of
 programmable tools for transcriptome editing in mammalian cells will provide new avenues for analyzing
 the effect of gene expression events and will greatly advance our ability to study specific mRNA isoforms,
 which is particularly important for understanding the brain.
2. Improve RNA knockdown screens. The current state-of-the-art for forward genetic screens in
 mammalian systems uses shRNAs, but these have significant off-target effects. RNAi screens based on
 programmable RNA-targeting enzymes will afford more robust, reliable data, boosting forward genetic
approaches.
3. Create programmable reporter systems for transcript sensing. Catalytically inactive RNA-targeting
 Cas enzymes will be engineered to serve as programmable RNA-binding scaffolds that can be fused to
 various functional moieties (e.g., fluorophores) to develop transcript sensors. These sensors will enable
 dynamic, efficient tracking of transcriptional changes over extended periods of time and provide a means
 for isolating transcriptionally defined cell populations for further study.
4. Develop genome-wide screens to dissect genetic regulatory circuits. Genome-wide Cas9 knockout
 and activation screening will be combined with RNA-targeting sensors to develop high-throughput systems
 to identify genomic regions (coding and non-coding) that influence the expression of a target gene.
These tools, which will be openly shared, will be broadly applicable across species and systems and will serve
as a general framework for the expansion of the RNA-targeting toolbox. They will radically transform existing
approaches for studying gene expression dynamics and exploring the significance of isoforms and non-coding
transcripts.

## Key facts

- **NIH application ID:** 9951080
- **Project number:** 5R01HG009761-04
- **Recipient organization:** BROAD INSTITUTE, INC.
- **Principal Investigator:** Feng Zhang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,124,060
- **Award type:** 5
- **Project period:** 2017-08-17 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9951080

## Citation

> US National Institutes of Health, RePORTER application 9951080, Programmable RNA-targeting tools (5R01HG009761-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9951080. Licensed CC0.

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