Systematic decomposition of sequence determinants governing CRISPR/Cas9 specificity

被引:0
作者
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
Han Xu
机构
[1] The University of Texas MD Anderson Cancer Center,Department of Epigenetics and Molecular Carcinogenesis
[2] Rice University,Department of Chemical and Biomolecular Engineering
[3] The University of Texas MD Anderson Cancer Center,Department of Bioinformatics and Computational Biology
[4] Rice University,Department of Chemistry
[5] Rice University,Department of Bioengineering
[6] Delft University of Technology,Kavli Institute of NanoScience and Department of BionanoScience
[7] The University of Texas MD Anderson Cancer Center,The Center for Cancer Epigenetics
来源
Nature Communications | / 13卷
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摘要
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.
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