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

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. Sontheimer, Scot A. Wolfe () and Wen Xue ()
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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
Jonathan K. Watts: University of Massachusetts Medical School
Erik J. Sontheimer: University of Massachusetts Medical School
Scot A. Wolfe: University of Massachusetts Medical School
Wen Xue: University of Massachusetts Medical School

Nature Communications, 2022, vol. 13, issue 1, 1-14

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41467-022-28135-9

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