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

NIH RePORTER · NIH · R35 · $385,000 · view on reporter.nih.gov ↗

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
UNIVERSITY OF ROCHESTER
Principal Investigator
Mitchell O'Connell
Activity code
R35
Funding institute
NIH
Fiscal year
2020
Award amount
$385,000
Award type
5
Project period
2019-08-01 → 2024-05-31