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Implications of human genetic variation in CRISPR-based therapeutic genome editing

Nature Medicine volume 23, pages 10951101 (2017) | Download Citation


CRISPR–Cas genome-editing methods hold immense potential as therapeutic tools to fix disease-causing mutations at the level of DNA. In contrast to typical drug development strategies aimed at targets that are highly conserved among individual patients, treatment at the genomic level must contend with substantial inter-individual natural genetic variation. Here we analyze the recently released ExAC and 1000 Genomes data sets to determine how human genetic variation impacts target choice for Cas endonucleases in the context of therapeutic genome editing. We find that this genetic variation confounds the target sites of certain Cas endonucleases more than others, and we provide a compendium of guide RNAs predicted to have high efficacy in diverse patient populations. For further analysis, we focus on 12 therapeutically relevant genes and consider how genetic variation affects off-target candidates for these loci. Our analysis suggests that, in large populations of individuals, most candidate off-target sites will be rare, underscoring the need for prescreening of patients through whole-genome sequencing to ensure safety. This information can be integrated with empirical methods for guide RNA selection into a framework for designing CRISPR-based therapeutics that maximizes efficacy and safety across patient populations.

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We would like to thank R. Macrae, L. Francioli, S. Jones, J. Strecker, D. Cox, I. Slaymaker, and W. Yan for helpful discussions and insights. F.Z. is a New York Stem Cell Foundation–Robertson Investigator. F.Z. is supported by the US National Institutes of Health through the National Institute of Mental Health (5DP1-MH100706 and 1R01-MH110049); the National Science Foundation; the New York Stem Cell Foundation; the Howard Hughes Medical Institute; the Simons Foundation; the Paul G. Allen Family Foundation; the Vallee Foundation; the Skoltech–MIT Next-Generation Program; James and Patricia Poitras; Robert Metcalfe; and David Cheng. The computer code and resources related to this work are available through the Zhang laboratory website ( and GitHub (

Author information


  1. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • David A Scott
    •  & Feng Zhang
  2. McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • David A Scott
    •  & Feng Zhang
  3. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • David A Scott
    •  & Feng Zhang
  4. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • Feng Zhang


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D.A.S. and F.Z. conceived the study; D.A.S. performed all experiments and analyses; D.A.S. and F.Z. wrote the manuscript.

Competing interests

F.Z. is a founder of Editas Medicine and a scientific advisor for Editas Medicine and Horizon Discovery.

Corresponding author

Correspondence to Feng Zhang.

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