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, 3?-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 development of essential research tools to study and RNA function for biomedical research.

Public Health Relevance

RNA-targeting CRISPR-Cas proteins offer an unprecedented opportunity to precisely manipulate RNA biology in ways not currently possible. We propose several innovative approaches to address critical knowledge gaps in CRISPR-Cas tool development and chart a path to use these tools to interrogate several fundamental questions in RNA biology. Our approaches will help us define the gRNA design rules for RNA-targeting Cas proteins, and develop robust new RNA-targeting Cas tools to manipulate RNA splicing and dissect protein- RNA interaction networks, and ultimately, the tools developed here will transform the way we study RNA and will broadly impact the fields of molecular and cell biology.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
1R35GM133462-01
Application #
9796943
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Bender, Michael T
Project Start
2019-08-01
Project End
2024-05-31
Budget Start
2019-08-01
Budget End
2020-05-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Rochester
Department
Biochemistry
Type
School of Medicine & Dentistry
DUNS #
041294109
City
Rochester
State
NY
Country
United States
Zip Code
14627