Extended Data Fig. 9: SlugCas9-, SaCas9-KKH-, SlugCas9-HF, Sa-SlugCas9-, or efSaCas9-directed targeting of dominant single-nucleotide variants with or without using DeepSmallCas9 to select sgRNAs.
Pie charts showing the fraction of the dominant single-nucleotide variants in protein-coding sequences in the ClinVar database (ref. 83,94) that can be edited using SlugCas9 (a), SaCas9-KKH (b), SlugCas9-HF (c), Sa-SlugCas9 (d), or efSaCas9 (e) in an efficient and allele-specific manner (on-target activity higher than 10% and off-target activity lower than 2%). Mutations for which no designed sgRNAs met these criteria were classified as either inefficient or nonspecific and those for which no mutant allele-targeting sgRNAs could be designed due to the lack of a nearby PAM were classified as untargetable. (Left pie charts) The specified small Cas9s were chosen and the most appropriate sgRNAs were designed using DeepSmallCas9 such that both the activity at the mutant allele and the allele-specificity are high. (Right pie charts) The specified small Cas9s were chosen and sgRNAs were designed to target given mutations such that the mutations were located in regions in the target sequence with the following order of preference: i) the PAM, ii) the highly selective protospacer region (within 10 bp from the PAM), and iii) the remaining region in the protospacer. The activities at the mutant and corresponding wild-type alleles were predicted afterwards using DeepSmallCas9. (Box plots) The predicted activities of selected Cas9-sgRNA combinations at mutant and wild-type alleles for the indicated SNVs. Boxes represent the 25th, 50th, and 75th percentiles and whiskers show the 10th and 90th percentiles. The fold differences between the average activities at mutant and wild-type alleles are shown (e.g., 34x).
