Predictable and precise template-free CRISPR editing of pathogenic variants
Author(s)
Shen, Max Walt; Arbab, Mandana; Hsu, Jonathan Yee-Ting; Worstell, Daniel; Culbertson, Sannie J.; Krabbe, Olga; Cassa, Christopher A.; Liu, David R.; Gifford, David K.; Sherwood, Richard I.; ... Show more Show less
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Following Cas9 cleavage, DNA repair without a donor template is generally considered stochastic, heterogeneous and impractical beyond gene disruption. Here, we show that template-free Cas9 editing is predictable and capable of precise repair to a predicted genotype, enabling correction of disease-associated mutations in humans. We constructed a library of 2,000 Cas9 guide RNAs paired with DNA target sites and trained inDelphi, a machine learning model that predicts genotypes and frequencies of 1- to 60-base-pair deletions and 1-base-pair insertions with high accuracy (r = 0.87) in five human and mouse cell lines. inDelphi predicts that 5–11% of Cas9 guide RNAs targeting the human genome are ‘precise-50’, yielding a single genotype comprising greater than or equal to 50% of all major editing products. We experimentally confirmed precise-50 insertions and deletions in 195 human disease-relevant alleles, including correction in primary patient-derived fibroblasts of pathogenic alleles to wild-type genotype for Hermansky–Pudlak syndrome and Menkes disease. This study establishes an approach for precise, template-free genome editing. Keywords: Functional genomics; Genome informatics
Date issued
2018-11Department
Massachusetts Institute of Technology. Computational and Systems Biology Program; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Broad Institute of MIT and Harvard; Massachusetts Institute of Technology. Department of Biological Engineering; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer ScienceJournal
Nature
Publisher
Springer Nature
Citation
Shen, Max W. et al "Predictable and precise template-free CRISPR editing of pathogenic variants." Nature 563, 7733 (November 2018): 646–651 ©2018, Springer Nature Limited.
Version: Author's final manuscript
ISSN
0028-0836
1476-4687