Abstract
Targeting protein domain-encoding exons in CRISPR–Cas9 screens can reveal genetic dependencies.
Major finding: Targeting protein domain-encoding exons in CRISPR–Cas9 screens can reveal genetic dependencies.
Concept: Protein domain functional importance may be inferred from negative selection in a CRISPR–Cas9 screen.
Impact: The identification of protein domains required for cancer cell survival may guide drug target discovery.
CRISPR–Cas9-mediated genome editing has emerged as a useful tool to generate gene-specific knockouts. Genetic screens using the CRISPR–Cas9 technology can be performed using a library of single guide RNAs (sgRNA) that target the Cas9 endonuclease to specific loci, but sgRNA libraries typically target only 5′ coding exons and may not always cause a phenotype, particularly if functional in-frame variants are produced. In their efforts to use CRISPR–Cas9-induced mutagenesis to identify essential genes in a murine acute myeloid leukemia (AML) cell line, Shi and colleagues observed that the degree of negative selection varied greatly among sgRNAs targeting the same gene. For example, severe negative-selection phenotypes were restricted to sgRNAs targeting the sequence within Brd4 that encodes the bromodomains or the sequence within Smarca4 that encodes the ATPase domain. Targeting catalytic domains of other essential genes also led to greater negative selection than targeting 5′ coding exons. Hypothesizing that a negative-selection CRISPR–Cas9 screening strategy exclusively targeting sequences encoding protein domains could identify those required for AML cell growth and survival, the authors designed an sgRNA library that specifically targeted sequences encoding chromatin regulatory domains. Of 192 domains targeted, strong negative selection was observed for 25 domains, many of which had not previously been identified as essential in leukemic cells. A negative-selection screening strategy using sgRNA libraries designed to target potentially druggable protein domains may thus help guide identification and prioritization of drug discovery efforts.
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