Development of potent and predictable Cas9 gene activation tools through high-throughput screening

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Project Summary The ability to manipulate the expression of genes in cells and organisms is foundational to the study of genetics. The CRISPR-Cas9 genome editing toolkit has revolutionized our ability to modify the genome and epigenome precisely. While CRISPR tools have been optimized to allow for robust, tunable, and predictable repression and inactivation of gene expression, approaches to induce gene expression (CRISPR activation, or CRISPRa) are less robust and reproducible. Through a combination of innovative high-throughput screens and cutting-edge computational modeling, we will develop a cohort of simple, robust, tunable, and predictable CRISPR-based tools to increase the expression of any mouse or human gene. We have developed a high-throughput sequencing-based assay system, Self-sustaining Peptide Activator Reporter-seq (SPARq), which enables quantitative screening of thousands of candidate gene activating peptides and combinations thereof to monitor and optimize their gene activation strength. In Aim 1, we will iteratively employ SPARq to systematically evaluate and optimize multiple features of gene activating peptides, including activation peptide identity, combination, linker, and CRISPRa method. We will perform SPARq screens in distinct cell types and with distinct promoter architectures to identify tools that work consistently, designing a set of CRISPRa tools that are significantly more potent and consistent than the current state-of-the-art. In Aim 2, we will improve the predictability and consequently the utility of CRISPRa through a novel high-throughput reporter assay and a computational effort to model the features associated with CRISPRa potency. We have designed an approach, CRISPR Outcome and Phenotype screening, that combines a sensitive reporter assay with a native genomic phenotypic measurement to profile the activity of a CRISPRa tool at thousands of target sites. Using data collected through this pipeline, we will develop an algorithm that takes as input one of the CRISPRa tools developed in Aim 1, a cell type, gene, and CRISPR guide RNA and outputs an accurate estimate of the expression of that gene following CRISPRa treatment. We will validate the accuracy of this algorithm to enable tunable gene activation over an extensive dynamic range in human HepG2 and K562 cells, providing it to the genetics community as a webtool. Altogether, the efforts described in this proposal will pioneer a next generation toolkit to enable more robust gain-of-function genetic manipulation and screening.