Systematic decomposition of sequence determinants governing CRISPR/Cas9 specificity

Rongjie Fu, Wei He, Jinzhuang Dou, Oscar D. Villarreal, Ella Bedford, Helen Wang, Connie Hou, Liang Zhang, Yalong Wang, Dacheng Ma, Yiwen Chen, Xue Gao, Martin Depken and Han Xu ()
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Rongjie Fu: The University of Texas MD Anderson Cancer Center
Wei He: The University of Texas MD Anderson Cancer Center
Jinzhuang Dou: The University of Texas MD Anderson Cancer Center
Oscar D. Villarreal: The University of Texas MD Anderson Cancer Center
Ella Bedford: The University of Texas MD Anderson Cancer Center
Helen Wang: The University of Texas MD Anderson Cancer Center
Connie Hou: The University of Texas MD Anderson Cancer Center
Liang Zhang: The University of Texas MD Anderson Cancer Center
Yalong Wang: The University of Texas MD Anderson Cancer Center
Dacheng Ma: Rice University
Yiwen Chen: The University of Texas MD Anderson Cancer Center
Xue Gao: Rice University
Martin Depken: Delft University of Technology
Han Xu: The University of Texas MD Anderson Cancer Center

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract The specificity of CRISPR/Cas9 genome editing is largely determined by the sequences of guide RNA (gRNA) and the targeted DNA, yet the sequence-dependent rules underlying off-target effects are not fully understood. To systematically explore the sequence determinants governing CRISPR/Cas9 specificity, here we describe a dual-target system to measure the relative cleavage rate between off- and on-target sequences (off-on ratios) of 1902 gRNAs on 13,314 synthetic target sequences, and reveal a set of sequence rules involving 2 factors in off-targeting: 1) a guide-intrinsic mismatch tolerance (GMT) independent of the mismatch context; 2) an “epistasis-like” combinatorial effect of multiple mismatches, which are associated with the free-energy landscape in R-loop formation and are explainable by a multi-state kinetic model. These sequence rules lead to the development of MOFF, a model-based predictor of Cas9-mediated off-target effects. Moreover, the “epistasis-like” combinatorial effect suggests a strategy of allele-specific genome editing using mismatched guides. With the aid of MOFF prediction, this strategy significantly improves the selectivity and expands the application domain of Cas9-based allele-specific editing, as tested in a high-throughput allele-editing screen on 18 cancer hotspot mutations.

Date: 2022
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DOI: 10.1038/s41467-022-28028-x

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