Extended Data Fig. 8: Computational prediction of preferred small Cas9s at targets with diverse PAM sequences.
a, Heatmap showing the most efficient Cas9 out of eight highly active small Cas9s, which include sRGN3.1, SlugCas9, SaCas9, SauriCas9, Sa-SlugCas9, SaCas9-KKH, eSaCas9, and efSaCas9, at target sequences with a given PAM sequence. To compare the activities of the small Cas9s at sites with 4,096 (= 46) PAMs (all possible NNNNNN sequences for the 1st–6th nucleotides of the PAM), 204,800 target sequences were generated by combining 50 randomly designed protospacer sequences and 4,096 PAM sequences and used as input data for the prediction of the activities (i.e., the induced indel frequencies) using DeepSmallCas9. The color-coded squares represent the small Cas9 that is predicted to be the most efficient, in cases in which the average indel frequency is higher than 10%, at a given PAM sequence. When the predicted average indel frequencies of the most efficient small Cas9s at given target sequences are lower than 10%, the squares representing those PAM sequences are shown in white. The color-code for each Cas9 is shown in b. b, Pie chart showing the number of PAM sequences that could be most efficiently targeted with each Cas9 with an average activity higher than 10%. c, Bar graph showing the number of efficiently targetable PAM sequences out of 4,096 (= 46) PAMs for each Cas9 with an average activity higher than 10%.
