Unbiased prediction of off‐target sites in genome‐edited rice using SITE‐Seq analysis on a web‐based platform.

Genome‐editing using the CRISPR‐Cas9 system has the potential to substantially accelerate crop breeding. Since off‐target editing is one of problems, a reliable method for comprehensively detecting off‐target sites is needed. A number of in silico methods based on homology to on‐target sequence have been developed, however the prediction without false negative is still under discussion. In this study, we performed a SITE‐Seq analysis to predict potential off‐target sites. SITE‐Seq analysis is a comprehensive method that can detect double‐strand breaks in vitro. Furthermore, we developed a systematic method using SITE‐Seq in combination with web‐based Galaxy system (Galaxy for Cut Site Detection), which can perform reproducible analyses without command line operations. We conducted a SITE‐Seq analysis of a rice genome targeted by OsFH15 gRNA‐Cas9 as a model, and found 41 candidate off‐target sites in the annotated regions. Detailed amplicon‐sequencing revealed mutations at one off‐target site in actual genome‐edited rice. Since this off‐target site has an uncommon protospacer adjacent motif, it is difficult to predict using in silico methods alone. Therefore, we propose a novel off‐target assessment scheme for genome‐edited crops that combines the prediction of off‐target candidates by SITE‐Seq and in silico programs and the validation of off‐target sites by amplicon‐sequencing. [ABSTRACT FROM AUTHOR]