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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.
In vivo assessment of nuclease off-target activity has primarily been indirect or through ChIP-based detection of double-strand break DNA repair factors, which can be cumbersome. Here, the authors show that GUIDE-tag, enables one-step off-target genome editing analysis in mouse liver and lung.
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1 University of Massachusetts Medical School, RNA Therapeutics Institute, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364)
2 University of Massachusetts Medical School, Department of Molecular, Cell and Cancer Biology, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364)
3 University of Massachusetts Medical School, Department of Molecular, Cell and Cancer Biology, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Department of Molecular Medicine, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364)
4 University of Massachusetts Medical School, RNA Therapeutics Institute, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Department of Molecular Medicine, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Li Weibo Institute for Rare Diseases Research, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364)
5 University of Massachusetts Medical School, Department of Molecular, Cell and Cancer Biology, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Li Weibo Institute for Rare Diseases Research, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364)
6 University of Massachusetts Medical School, RNA Therapeutics Institute, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Department of Molecular, Cell and Cancer Biology, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Department of Molecular Medicine, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364); University of Massachusetts Medical School, Li Weibo Institute for Rare Diseases Research, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364)