Publication

Comprehensive analysis and accurate quantification of unintended large gene modifications induced by CRISPR-Cas9 gene editing

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Last modified
  • 06/25/2025
Type of Material
Authors
    So Hyun Park, Rice UniversityMingming Cao, Rice UniversityYidan Pan, Rice UniversityTimothy H Davis, Rice UniversityLavanya Saxena, Rice UniversityHarshavardhan Deshmukh, Rice UniversityYilei Fu, Rice UniversityTodd Treangen, Rice UniversityVivien Sheehan, Emory UniversityGang Bao, Emory University
Language
  • English
Date
  • 2022-10-21
Publisher
  • AMER ASSOC ADVANCEMENT SCIENCE
Publication Version
Copyright Statement
  • © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).
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Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 8
Issue
  • 42
Start Page
  • eabo7676
End Page
  • eabo7676
Grant/Funding Information
  • This work was supported by the National Institutes of Health (R01HL152314 and OT2HL154977 to G.B.).
Supplemental Material (URL)
Abstract
  • Most genome editing analyses to date are based on quantifying small insertions and deletions. Here, we show that CRISPR-Cas9 genome editing can induce large gene modifications, such as deletions, insertions, and complex local rearrangements in different primary cells and cell lines. We analyzed large deletion events in hematopoietic stem and progenitor cells (HSPCs) using different methods, including clonal genotyping, droplet digital polymerase chain reaction, single-molecule real-time sequencing with unique molecular identifier, and long-amplicon sequencing assay. Our results show that large deletions of up to several thousand bases occur with high frequencies at the Cas9 on-target cut sites on the HBB (11.7 to 35.4%), HBG (14.3%), and BCL11A (13.2%) genes in HSPCs and the PD-1 (15.2%) gene in T cells. Our findings have important implications to advancing genome editing technologies for treating human diseases, because unintended large gene modifications may persist, thus altering the biological functions and reducing the available therapeutic alleles.
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Keywords
Research Categories
  • Computer Science
  • Health Sciences, Medicine and Surgery

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