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Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements

Author

Listed:
  • Josh Tycko

    (Stanford University)

  • Michael Wainberg

    (Stanford University)

  • Georgi K. Marinov

    (Stanford University)

  • Oana Ursu

    (Stanford University)

  • Gaelen T. Hess

    (Stanford University)

  • Braeden K. Ego

    (Stanford University)

  • Aradhana

    (Stanford University)

  • Amy Li

    (Stanford University)

  • Alisa Truong

    (Stanford University)

  • Alexandro E. Trevino

    (Stanford University
    Stanford University)

  • Kaitlyn Spees

    (Stanford University)

  • David Yao

    (Stanford University)

  • Irene M. Kaplow

    (Stanford University
    Stanford University)

  • Peyton G. Greenside

    (Stanford University
    Stanford University School of Medicine)

  • David W. Morgens

    (Stanford University)

  • Douglas H. Phanstiel

    (Stanford University
    University of North Carolina
    University of North Carolina)

  • Michael P. Snyder

    (Stanford University)

  • Lacramioara Bintu

    (Stanford University)

  • William J. Greenleaf

    (Stanford University
    Stanford University
    Chan Zuckerberg Biohub)

  • Anshul Kundaje

    (Stanford University
    Stanford University)

  • Michael C. Bassik

    (Stanford University
    Stanford University)

Abstract

Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements.

Suggested Citation

  • Josh Tycko & Michael Wainberg & Georgi K. Marinov & Oana Ursu & Gaelen T. Hess & Braeden K. Ego & Aradhana & Amy Li & Alisa Truong & Alexandro E. Trevino & Kaitlyn Spees & David Yao & Irene M. Kaplow , 2019. "Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11955-7
    DOI: 10.1038/s41467-019-11955-7
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    Cited by:

    1. Alexendar R. Perez & Laura Sala & Richard K. Perez & Joana A. Vidigal, 2021. "CSC software corrects off-target mediated gRNA depletion in CRISPR-Cas9 essentiality screens," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    2. Annabel K. Sangree & Audrey L. Griffith & Zsofia M. Szegletes & Priyanka Roy & Peter C. DeWeirdt & Mudra Hegde & Abby V. McGee & Ruth E. Hanna & John G. Doench, 2022. "Benchmarking of SpCas9 variants enables deeper base editor screens of BRCA1 and BCL2," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    3. 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.
    4. Chenrui Qin & Yanhui Xiang & Jie Liu & Ruilin Zhang & Ziming Liu & Tingting Li & Zhi Sun & Xiaoyi Ouyang & Yeqing Zong & Haoqian M. Zhang & Qi Ouyang & Long Qian & Chunbo Lou, 2023. "Precise programming of multigene expression stoichiometry in mammalian cells by a modular and programmable transcriptional system," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

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