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Genome-wide detection of CRISPR editing in vivo using GUIDE-tag

Author

Listed:
  • Shun-Qing Liang

    (University of Massachusetts Medical School)

  • Pengpeng Liu

    (University of Massachusetts Medical School)

  • Jordan L. Smith

    (University of Massachusetts Medical School)

  • Esther Mintzer

    (University of Massachusetts Medical School)

  • Stacy Maitland

    (University of Massachusetts Medical School)

  • Xiaolong Dong

    (University of Massachusetts Medical School)

  • Qiyuan Yang

    (University of Massachusetts Medical School)

  • Jonathan Lee

    (University of Massachusetts Medical School)

  • Cole M. Haynes

    (University of Massachusetts Medical School)

  • Lihua Julie Zhu

    (University of Massachusetts Medical School
    University of Massachusetts Medical School
    University of Massachusetts Medical School)

  • Jonathan K. Watts

    (University of Massachusetts Medical School)

  • Erik J. Sontheimer

    (University of Massachusetts Medical School
    University of Massachusetts Medical School
    University of Massachusetts Medical School)

  • Scot A. Wolfe

    (University of Massachusetts Medical School
    University of Massachusetts Medical School)

  • Wen Xue

    (University of Massachusetts Medical School
    University of Massachusetts Medical School
    University of Massachusetts Medical School
    University of Massachusetts Medical School)

Abstract

Analysis of off-target editing is an important aspect of the development of safe nuclease-based genome editing therapeutics. in vivo assessment of nuclease off-target activity has primarily been indirect (based on discovery in vitro, in cells or via computational prediction) or through ChIP-based detection of double-strand break (DSB) DNA repair factors, which can be cumbersome. Herein we describe GUIDE-tag, which enables one-step, off-target genome editing analysis in mouse liver and lung. The GUIDE-tag system utilizes tethering between the Cas9 nuclease and the DNA donor to increase the capture rate of nuclease-mediated DSBs and UMI incorporation via Tn5 tagmentation to avoid PCR bias. These components can be delivered as SpyCas9-mSA ribonucleoprotein complexes and biotin-dsDNA donor for in vivo editing analysis. GUIDE-tag enables detection of off-target sites where editing rates are ≥ 0.2%. UDiTaS analysis utilizing the same tagmented genomic DNA detects low frequency translocation events with off-target sites and large deletions in vivo. The SpyCas9-mSA and biotin-dsDNA system provides a method to capture DSB loci in vivo in a variety of tissues with a workflow that is amenable to analysis of gross genomic alterations that are associated with genome editing.

Suggested Citation

  • Shun-Qing Liang & Pengpeng Liu & Jordan L. Smith & Esther Mintzer & Stacy Maitland & Xiaolong Dong & Qiyuan Yang & Jonathan Lee & Cole M. Haynes & Lihua Julie Zhu & Jonathan K. Watts & Erik J. Sonthei, 2022. "Genome-wide detection of CRISPR editing in vivo using GUIDE-tag," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28135-9
    DOI: 10.1038/s41467-022-28135-9
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    References listed on IDEAS

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    1. Johnny H. Hu & Shannon M. Miller & Maarten H. Geurts & Weixin Tang & Liwei Chen & Ning Sun & Christina M. Zeina & Xue Gao & Holly A. Rees & Zhi Lin & David R. Liu, 2018. "Evolved Cas9 variants with broad PAM compatibility and high DNA specificity," Nature, Nature, vol. 556(7699), pages 57-63, April.
    2. Janice S. Chen & Yavuz S. Dagdas & Benjamin P. Kleinstiver & Moira M. Welch & Alexander A. Sousa & Lucas B. Harrington & Samuel H. Sternberg & J. Keith Joung & Ahmet Yildiz & Jennifer A. Doudna, 2017. "Enhanced proofreading governs CRISPR–Cas9 targeting accuracy," Nature, Nature, vol. 550(7676), pages 407-410, October.
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    Cited by:

    1. Jianli Tao & Daniel E. Bauer & Roberto Chiarle, 2023. "Assessing and advancing the safety of CRISPR-Cas tools: from DNA to RNA editing," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Jeonghun Kwon & Minyoung Kim & Seungmin Bae & Anna Jo & Youngho Kim & Jungjoon K. Lee, 2022. "TAPE-seq is a cell-based method for predicting genome-wide off-target effects of prime editor," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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