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Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens

Author

Listed:
  • David W. Morgens

    (Stanford University)

  • Michael Wainberg

    (Stanford University)

  • Evan A. Boyle

    (Stanford University)

  • Oana Ursu

    (Stanford University)

  • Carlos L. Araya

    (Stanford University)

  • C. Kimberly Tsui

    (Stanford University)

  • Michael S. Haney

    (Stanford University)

  • Gaelen T. Hess

    (Stanford University)

  • Kyuho Han

    (Stanford University)

  • Edwin E. Jeng

    (Stanford University
    Program in Cancer Biology, Stanford University)

  • Amy Li

    (Stanford University)

  • Michael P. Snyder

    (Stanford University)

  • William J. Greenleaf

    (Stanford University)

  • Anshul Kundaje

    (Stanford University
    Stanford University)

  • Michael C. Bassik

    (Stanford University
    Stanford University Chemistry, Engineering, and Medicine for Human Health (ChEM-H))

Abstract

CRISPR-Cas9 screens are powerful tools for high-throughput interrogation of genome function, but can be confounded by nuclease-induced toxicity at both on- and off-target sites, likely due to DNA damage. Here, to test potential solutions to this issue, we design and analyse a CRISPR-Cas9 library with 10 variable-length guides per gene and thousands of negative controls targeting non-functional, non-genic regions (termed safe-targeting guides), in addition to non-targeting controls. We find this library has excellent performance in identifying genes affecting growth and sensitivity to the ricin toxin. The safe-targeting guides allow for proper control of toxicity from on-target DNA damage. Using this toxicity as a proxy to measure off-target cutting, we demonstrate with tens of thousands of guides both the nucleotide position-dependent sensitivity to single mismatches and the reduction of off-target cutting using truncated guides. Our results demonstrate a simple strategy for high-throughput evaluation of target specificity and nuclease toxicity in Cas9 screens.

Suggested Citation

  • David W. Morgens & Michael Wainberg & Evan A. Boyle & Oana Ursu & Carlos L. Araya & C. Kimberly Tsui & Michael S. Haney & Gaelen T. Hess & Kyuho Han & Edwin E. Jeng & Amy Li & Michael P. Snyder & Will, 2017. "Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens," Nature Communications, Nature, vol. 8(1), pages 1-8, August.
  • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15178
    DOI: 10.1038/ncomms15178
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    Cited by:

    1. Gemma Noviello & Rutger A. F. Gjaltema & Edda G. Schulz, 2023. "CasTuner is a degron and CRISPR/Cas-based toolkit for analog tuning of endogenous gene expression," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. Malgorzata J. Latallo & Shaopeng Wang & Daoyuan Dong & Blake Nelson & Nathan M. Livingston & Rong Wu & Ning Zhao & Timothy J. Stasevich & Michael C. Bassik & Shuying Sun & Bin Wu, 2023. "Single-molecule imaging reveals distinct elongation and frameshifting dynamics between frames of expanded RNA repeats in C9ORF72-ALS/FTD," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    3. Anna S. Dickson & Tekle Pauzaite & Esther Arnaiz & Brian M. Ortmann & James A. West & Norbert Volkmar & Anthony W. Martinelli & Zhaoqi Li & Niek Wit & Dennis Vitkup & Arthur Kaser & Paul J. Lehner & J, 2023. "A HIF independent oxygen-sensitive pathway for controlling cholesterol synthesis," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    4. Xiaolong Cheng & Zexu Li & Ruocheng Shan & Zihan Li & Shengnan Wang & Wenchang Zhao & Han Zhang & Lumen Chao & Jian Peng & Teng Fei & Wei Li, 2023. "Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    5. Marsha M. Wheeler & Adrienne M. Stilp & Shuquan Rao & Bjarni V. Halldórsson & Doruk Beyter & Jia Wen & Anna V. Mihkaylova & Caitlin P. McHugh & John Lane & Min-Zhi Jiang & Laura M. Raffield & Goo Jun , 2022. "Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    6. Miguel M. Álvarez & Josep Biayna & Fran Supek, 2022. "TP53-dependent toxicity of CRISPR/Cas9 cuts is differential across genomic loci and can confound genetic screening," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

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