Extended Data Fig. 6: Genome editing in human cells with PAMmla-predicted enzymes. | Nature

Extended Data Fig. 6: Genome editing in human cells with PAMmla-predicted enzymes.

From: Custom CRISPR–Cas9 PAM variants via scalable engineering and machine learning

Extended Data Fig. 6

(a) PAMmla predicted ks for NGNN PAMs for enzymes targeting seven PAM categories. Hamming distances to the most similar enzyme in the training set are indicated in parentheses for each enzyme. (b) Nuclease-mediated genome editing efficiencies for each of the enzymes in panel a at endogenous target sites in HEK 293T cells harboring the PAMs they are predicted to target by PAMmla. Editing efficiencies were assessed by targeted amplicon sequencing and analyzed using CRISPResso2; data points are the mean of n = 3 biological replicates for enzymes from the training set (hamming distance = 0, shown with blue dots), enzymes predicted by PAMmla (shown in pink), SpG (gray), and wild-type (WT) SpCas9 (white); 3 to 10 genomic target sites were selected for characterization, where the black line represents median editing across all target sites for that enzyme; results at individual loci are shown in Supplementary Fig. 12a–g. (c,d) Base editing efficiencies for one PAMmla enzyme compared to SpG and SpRY, in the context of ABE8e and TadCBEd architectures (panels c and d, respectively). Base editing efficiencies were assessed by targeted amplicon sequencing for each enzyme at 3 endogenous target sites in HEK 293T cells; all edits at bases where any enzyme was observed to edit >5% efficiency are shown; Box minima, center and maxima represent data 25th, 50th, and 75th percentiles respectively; whiskers represent the range of the data. A-to-G and C-to-T base editing results at individual loci are shown in Supplementary Figs. 13a–g and 14a–g, respectively.

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