Massively parallel kinetic profiling of natural and engineered CRISPR nucleases

Abstract

Engineered SpCas9s and AsCas12a cleave fewer off-target genomic sites than wild-type (wt) Cas9. However, understanding their fidelity, mechanisms and cleavage outcomes requires systematic profiling across mispaired target DNAs. Here we describe NucleaSeq—nuclease digestion and deep sequencing—a massively parallel platform that measures the cleavage kinetics and time-resolved cleavage products for over 10,000 targets containing mismatches, insertions and deletions relative to the guide RNA. Combining cleavage rates and binding specificities on the same target libraries, we benchmarked five SpCas9 variants and AsCas12a. A biophysical model built from these data sets revealed mechanistic insights into off-target cleavage. Engineered Cas9s, especially Cas9-HF1, dramatically increased cleavage specificity but not binding specificity compared to wtCas9. Surprisingly, AsCas12a cleavage specificity differed little from that of wtCas9. Initial DNA cleavage sites and end trimming varied by nuclease, guide RNA and the positions of mispaired nucleotides. More broadly, NucleaSeq enables rapid, quantitative and systematic comparisons of specificity and cleavage outcomes across engineered and natural nucleases.

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Fig. 1: Overview of the integrated NucleaSeq and CHAMP platform.
Fig. 2: Comprehensive analysis of off-target wtCas9 DNA binding and cleavage.
Fig. 3: Comparison of engineered Cas9 nucleases.
Fig. 4: Comprehensive analysis of off-target Cas12a cleavage.
Fig. 5: Statistical modeling of CRISPR–Cas nuclease cleavage.

Data availability

Analyzed data are available at https://github.com/finkelsteinlab/. NucleaSeq sequencing data are available through the National Center for Biotechnology Information Sequence Read Archive database (PRJNA623618). All other relevant raw data are available from the corresponding authors upon reasonable request. Source data are provided with this paper.

Code availability

Custom software (CHAMP, NucleaSeq and freebarcodes repositories) used for data analysis are written in Python 2.7 and are available at https://github.com/finkelsteinlab/. Scripting for figure preparation is available from the corresponding authors upon reasonable request.

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Acknowledgements

We thank I. Strohkendl, R. Russell and members of the University of Texas at Austin Genomic Sequencing and Analysis Facility staff for valuable insights. We are grateful to members of the Finkelstein laboratory for carefully reading the manuscript and for additional contributions by K. Dillard, F. Saifuddin, G. Nguyen and J. Kula. This work was supported by a College of Natural Sciences Catalyst award, the Welch Foundation (F-1808 to I.J.F.) and the National Institutes of Health (R01GM124141 to I.J.F. and F32 AG053051 to S.K.J.).

Author information

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Authors

Contributions

S.K.J., J.A.H., C.J., J.R.R., W.H.P. and I.J.F. designed the research. S.K.J., N.V.H., K.H., C.J. and J.S.C. performed the experiments. J.A.H., J.R.R., K.H. and W.H.P. wrote the software. J.A.H., S.K.J. and K.H. analyzed the data. J.A.H. performed the modeling. S.K.J., J.A.H. and I.J.F. wrote the paper with editorial assistance from all co-authors.

Corresponding authors

Correspondence to Stephen K. Jones Jr or John A. Hawkins or Ilya J. Finkelstein.

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Competing interests

The authors declare competing financial interests. The authors have filed patent applications on the CHAMP platform. The Regents of the University of California have patents issued and pending for CRISPR technologies on which J.A.D. is an inventor. J.A.D. is a co-founder of Caribou Biosciences, Editas Medicine, Intellia Therapeutics, Scribe Therapeutics and Mammoth Biosciences. J.A.D. is a scientific advisory board member of Caribou Biosciences, Intellia Therapeutics, eFFECTOR Therapeutics, Scribe Therapeutics, Synthego, Mammoth Biosciences and Inari. J.A.D. is a member of the board of directors at Driver and Johnson & Johnson and has sponsored research projects by Roche Biopharma and Biogen. J.A.C. is a co-founder of Mammoth Biosciences. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare no competing non-financial interests.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–9, Supplementary Tables 1–3 and Supplementary File 1–3 descriptions

Reporting Summary

Supplementary File 1

Complete DNA sequences as synthesized for DNA libraries used with CHAMP and NucleaSeq methods. From 5′ to 3′: primer-binding region for library amplification, first barcode for identifying a cleaved DNA fragment, constant region for uniform target sequence context, 5′ Cas12a PAM, target sequence, 3′ Cas9 PAM, constant region for uniform target sequence context and length, second barcode for identifying a cleaved DNA fragment, primer-binding region for library amplification (Supplementary Fig. 1b and Online Methods).

Supplementary File 2

Cleavage rates and normalized changes in apparent binding affinity (ΔABA) for all measured DNAs with the indicated RNPs. Sequence: The DNA sequence related to the PAM and guide RNA for the tested RNP. Descriptor: Relationship between the tested DNA sequence and the intended DNA target matching the guide RNA and PAM. ndABA: The change in apparent binding affinity (as measured using CHAMP) for the indicated DNA sequence compared to that of a matched DNA, normalized to the matched DNA (0) and an unmatched negative control DNA (1). ndABA_unc: s.d. of the normalized change in apparent binding affinity as measured by bootstrap analysis. cleavage_rate_log: The log-transformed cleavage rate as measured by NucleaSeq for the indicated DNA sequence. cleavage_rate_log_unc: s.d. of the log-transformed cleavage rate as measured by bootstrap analysis.

Supplementary File 3

Cleavage rates and average cleavage sites for all measured DNAs treated with the indicated RNPs. Sequence: The DNA sequence related to the PAM and guide RNA for the tested RNP. Descriptor: Relationship between the tested DNA sequence and the intended DNA target matching the guide RNA and PAM. cleavage_rate_log: The log-transformed cleavage rate as measured by NucleaSeq for the indicated DNA sequence. cleavage_rate_log_unc: s.d. of the log-transformed cleavage rate as measured by bootstrap analysis. L_## or R_##: Average left and right side (5′→3′NTS) cleavage sites for the indicated DNA sequence with the indicated RNP at the indicated time. None: Less than 33% of DNAs with the indicated sequence were cleaved in the overall reaction; no average cleavage site available.

Source data

Source Data Fig. 1

Unprocessed chromatograms in gel representation.

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Jones, S.K., Hawkins, J.A., Johnson, N.V. et al. Massively parallel kinetic profiling of natural and engineered CRISPR nucleases. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0646-5

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