DNA Targeting Specificity of the RNA-guided Cas9 Nuclease

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Patrick David Hsu, David Arthur Scott, Fei Ann Ran, Ophir Shalem, Feng Zhang

Broad Institute of MIT and Harvard, United States

One of the major applications of synthetic biology is the engineering of biological systems into useful organismic platforms. A fundamental requirement is the ability to manipulate genomes and functional genetics for applications such as designer in vivo circuits, gene-based therapeutics, or transgenic disease models. Programmable sequence-specific endonucleases that facilitate precise editing or regulation of the genome are now enabling systematic interrogation of cellular function from molecules to behavior. The CRISPR (clustered regularly interspaced short palindromic repeats) system is a form of microbial adaptive immunity used to defend against invading phages or plasmids. We and others recently engineered the RNA-guided Cas9 nuclease from the type II CRISPR locus of Streptococcus pyogenes for genome editing in mammalian cells. The ability to program the cleavage specificity of Cas9 using a guide RNA provides a significant design and accessibility advantage over existing genome engineering technologies such as TALENs and zinc finger nucleases, which require involved molecular cloning or protein engineering. Although this unique RNA-programmable nuclease system has enormous potential for advancing genome engineering, the cleavage activity and target recognition fidelity of CRISPR/Cas have yet to be well characterized. We systematically generated a set of chimeric guide RNA truncations and identified an optimal architecture for maximal cleavage activity, achieving up to 50% target modification of 2 different loci. We then used next-generation sequencing to study the ability of single mutations and multiple combinations of mismatches within 15 different Cas9 guide RNAs to mediate target locus modification within the endogenous human EMX1 gene. Based on our analysis of permissive guide RNA mutations that exhibit on-target activity, we propose a set of guide RNA design rules and design a computational algorithm for predicting Cas9 off-target sites throughout the genome.