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Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair

View ORCID ProfileWei Chen, View ORCID ProfileAaron McKenna, Jacob Schreiber, View ORCID ProfileYi Yin, View ORCID ProfileVikram Agarwal, View ORCID ProfileWilliam Stafford Noble, View ORCID ProfileJay Shendure
doi: https://doi.org/10.1101/481069
Wei Chen
1Molecular Engineering and Sciences Institute, University of Washington, Seattle, Washington, 98195
2Department of Genome Sciences, University of Washington, Seattle, Washington, 98195
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  • ORCID record for Wei Chen
Aaron McKenna
2Department of Genome Sciences, University of Washington, Seattle, Washington, 98195
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Jacob Schreiber
3Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, 98195
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Yi Yin
2Department of Genome Sciences, University of Washington, Seattle, Washington, 98195
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Vikram Agarwal
2Department of Genome Sciences, University of Washington, Seattle, Washington, 98195
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William Stafford Noble
2Department of Genome Sciences, University of Washington, Seattle, Washington, 98195
3Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, 98195
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Jay Shendure
2Department of Genome Sciences, University of Washington, Seattle, Washington, 98195
4Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, Washington, 98195
5Howard Hughes Medical Institute, Seattle, Washington, 98195
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  • For correspondence: shendure@uw.edu
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Abstract

Non-homologous end-joining (NHEJ) plays an important role in double-strand break (DSB) repair of DNA. Recent studies have shown that the error patterns of NHEJ are strongly biased by sequence context, but these studies were based on relatively few templates. To investigate this more thoroughly, we systematically profiled ∼1.16 million independent mutational events resulting from CRISPR/Cas9-mediated cleavage and NHEJ-mediated DSB repair of 6,872 synthetic target sequences, introduced into a human cell line via lentiviral infection. We find that: 1) insertions are dominated by 1 bp events templated by sequence immediately upstream of the cleavage site, 2) deletions are predominantly associated with microhomology, and 3) targets exhibit variable but reproducible diversity with respect to the number and relative frequency of the mutational outcomes to which they give rise. From these data, we trained a model that uses local sequence context to predict the distribution of mutational outcomes. Exploiting the bias of NHEJ outcomes towards microhomology mediated events, we demonstrate the programming of deletion patterns by introducing microhomology to specific locations in the vicinity of the DSB site. We anticipate that our results will inform investigations of DSB repair mechanisms as well as the design of CRISPR/Cas9 experiments for diverse applications including genome-wide screens, gene therapy, lineage tracing and molecular recording.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 28, 2018.
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Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair
Wei Chen, Aaron McKenna, Jacob Schreiber, Yi Yin, Vikram Agarwal, William Stafford Noble, Jay Shendure
bioRxiv 481069; doi: https://doi.org/10.1101/481069
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Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair
Wei Chen, Aaron McKenna, Jacob Schreiber, Yi Yin, Vikram Agarwal, William Stafford Noble, Jay Shendure
bioRxiv 481069; doi: https://doi.org/10.1101/481069

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