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.
Despite major advances in sequencing DNA and identifying variation associated with disease, it has remained challenging to understand how such variation causes disease, in part because we lack tools to efficiently study the direct products of DNA, RNA. We propose to develop a suite of tools that can address this gap in a robust, cost-effective manner by repurposing naturally occurring microbial enzymes that can be precisely guided to a specific RNA sequence. These tools will provide researchers with methods to fine-tune and detect gene expression events in a dynamic, flexible way, dramatically accelerating the study of the complex genetic and epigenetic circuits that underlie specific phenotypes, including disease.
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| Gootenberg, Jonathan S; Abudayyeh, Omar O; Kellner, Max J et al. (2018) Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6. Science 360:439-444 |
| Tekin, Halil; Simmons, Sean; Cummings, Beryl et al. (2018) Effects of 3D culturing conditions on the transcriptomic profile of stem-cell-derived neurons. Nat Biomed Eng 2:540-554 |
| Abudayyeh, Omar O; Gootenberg, Jonathan S; Essletzbichler, Patrick et al. (2017) RNA targeting with CRISPR-Cas13. Nature 550:280-284 |
| Cox, David B T; Gootenberg, Jonathan S; Abudayyeh, Omar O et al. (2017) RNA editing with CRISPR-Cas13. Science 358:1019-1027 |
