ena-STUDY-SC-16-11-2018-13:32:36:488-34
Predicting the mutations generated by repair of Cas9-induced double-strand breaks
The DNA mutation produced by cellular repair of a CRISPR/Cas9-generated double-strand break determines its phenotypic effect. It is known that the mutational outcomes are not random, and depend on DNA sequence at the targeted location. Here we systematically study the influence of flanking DNA sequence on repair outcome by measuring the edits generated by >40,000 guide RNAs in synthetic constructs. We performed the experiments in a range of genetic backgrounds and using alternative CRISPR/Cas9 reagents. In total, we gathered data for >1,000,000,000 mutational outcomes. The majority of reproducible mutations are insertions of a single base, short deletions, or longer microhomology-mediated deletions. Each gRNA has an individual cell-line dependent bias toward particular outcomes. We uncover sequence determinants of the produced mutations, and use these to derive a predictor of Cas9 editing outcomes. Improved understanding of sequence repair will allow better design of gene editing experiments.
The DNA mutation produced by cellular repair of a CRISPR/Cas9-generated double-strand break determines its phenotypic effect. It is known that the mutational outcomes are not random, and depend on DNA sequence at the targeted location. Here we systematically study the influence of flanking DNA sequence on repair outcome by measuring the edits generated by >40,000 guide RNAs in synthetic constructs. We performed the experiments in a range of genetic backgrounds and using alternative CRISPR/Cas9 reagents. In total, we gathered data for >1,000,000,000 mutational outcomes. The majority of reproducible mutations are insertions of a single base, short deletions, or longer microhomology-mediated deletions. Each gRNA has an individual cell-line dependent bias toward particular outcomes. We uncover sequence determinants of the produced mutations, and use these to derive a predictor of Cas9 editing outcomes. Improved understanding of sequence repair will allow better design of gene editing experiments.