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Analysis of gene repair tracts from Cas9/gRNA double-stranded breaks in the human CFTR gene

Overview of attention for article published in Scientific Reports, August 2016
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Analysis of gene repair tracts from Cas9/gRNA double-stranded breaks in the human CFTR gene
Published in
Scientific Reports, August 2016
DOI 10.1038/srep32230
Pubmed ID

Jennifer A. Hollywood, Ciaran M. Lee, Martina F. Scallan, Patrick T. Harrison


To maximise the efficiency of template-dependent gene editing, most studies describe programmable and/or RNA-guided endonucleases that make a double-stranded break at, or close to, the target sequence to be modified. The rationale for this design strategy is that most gene repair tracts will be very short. Here, we describe a CRISPR Cas9/gRNA selection-free strategy which uses deep sequencing to characterise repair tracts from a donor plasmid containing seven nucleotide differences across a 216 bp target region in the human CFTR gene. We found that 90% of the template-dependent repair tracts were >100 bp in length with equal numbers of uni-directional and bi-directional repair tracts. The occurrence of long repair tracts suggests that a single gRNA could be used with variants of the same template to create or correct specific mutations within a 200 bp range, the size of ~80% of human exons. The selection-free strategy used here also allowed detection of non-homologous end joining events in many of the homology-directed repair tracts. This indicates a need to modify the donor, possibly by silent changes in the PAM sequence, to prevent creation of a second double-stranded break in an allele that has already been correctly edited by homology-directed repair.

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 63 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 20%
Student > Master 11 17%
Student > Bachelor 10 16%
Student > Ph. D. Student 10 16%
Other 4 6%
Other 7 11%
Unknown 9 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 36%
Agricultural and Biological Sciences 21 33%
Medicine and Dentistry 4 6%
Philosophy 1 2%
Immunology and Microbiology 1 2%
Other 3 5%
Unknown 11 17%