4.8 Article

In silico abstraction of zinc finger nuclease cleavage profiles reveals an expanded landscape of off-target sites

期刊

NUCLEIC ACIDS RESEARCH
卷 41, 期 19, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkt716

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资金

  1. National Institutes of Health (NIH) [DP1 GM105378, NIH P50 HG005550]
  2. Defense Advanced Research Projects Agency (DARPA) [W911NF-11-2-0056]
  3. Jim and Ann Orr Massachusetts General Hospital (MGH) Research Scholar Award
  4. NIH [DP1 GM105378, T32 CA009216]
  5. National Science Foundation Graduate Research Fellowship
  6. Ford Foundation Predoctoral Fellowship
  7. National Science Foundation (NSF) [DBI-0923827]
  8. DARPA [HR0011-11-2-0003, N66001-12-C-4207]
  9. Howard Hughes Medical Institute
  10. National Institute of General Medical Sciences [T32GM007753]
  11. National Human Genome Research Institute [U54 HG004570]

向作者/读者索取更多资源

Gene-editing nucleases enable targeted modification of DNA sequences in living cells, thereby facilitating efficient knockout and precise editing of endogenous loci. Engineered nucleases also have the potential to introduce mutations at off-target sites of action. Such unintended alterations can confound interpretation of experiments and can have implications for development of therapeutic applications. Recently, two improved methods for identifying the off-target effects of zinc finger nucleases (ZFNs) were described-one using an in vitro cleavage site selection method and the other exploiting the insertion of integration-defective lentiviruses into nuclease-induced double-stranded DNA breaks. However, application of these two methods to a ZFN pair targeted to the human CCR5 gene led to identification of largely non-overlapping off-target sites, raising the possibility that additional off-target sites might exist. Here, we show that in silico abstraction of ZFN cleavage profiles obtained from in vitro cleavage site selections can greatly enhance the ability to identify potential off-target sites in human cells. Our improved method should enable more comprehensive profiling of ZFN specificities.

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