A method for characterizing Cas9 variants via a one-million target sequence library of self-targeting sgRNAs

Detailed target-selectivity information and experiment-based efficacy prediction tools are primarily available for Streptococcus pyogenes Cas9 (SpCas9). One obstacle to develop such tools is the rarity of accurate data. Here, we report a method termed 'Self-targeting sgRNA Library Screen' (SLS) for assaying the activity of Cas9 nucleases in bacteria using random target/sgRNA libraries of self-targeting sgRNAs. Exploiting more than a million different sequences, we demonstrate the use of the method with the SpCas9-HF1 variant to analyse its activity and reveal motifs that influence its target-selectivity. We have also developed an algorithm for predicting the activity of SpCas9-HF1 with an accuracy matching those of existing tools. SLS is a facile alternative to the much more expensive and laborious approaches used currently and has the capability of delivering sufficient amount of data for most of the orthologs and variants of SpCas9.