Prediction of synonymous corrections by the BE-FF computational tool expands the targeting scope of base editing

ABSTRACTBase editing is a genome-editing approach that employs the CRISPR/Cas system to precisely install point mutations within the genome. A cytidine or adenosine deaminase enzyme is fused to a deactivated Cas and converts C to T or A to G, respectively. The diversified repertoire of base editors, varied in their Cas and deaminase proteins, provides a wide range of functionality. However, existing base-editors can only induce transition substitutions in a specified region determined by the base editor, thus, they are incompatible for many point mutations. Here, we present BE-FF (Base Editors Functional Finder), a novel computational tool that identifies suitable base editors to correct the translated sequence erred by a given single nucleotide variation. Even if a perfect correction of the single nucleotide variation is not possible, BE-FF detects synonymous corrections to produce the reference protein. To assess the potential of BE-FF, we analysed a database of human pathogenic point mutations and found suitable base editors for 60.9% of the transition mutations. Importantly, 19.4% of them were made possible only by synonymous corrections. Moreover, we detected 298 cases in which pathogenic mutations caused by transversions were potentially repairable by base editing via synonymous corrections, although it had been thought impractical. The BE-FF tool and the database are available at https://www.danioffenlab.com/be-ff.GRAPHICAL ABSTRACT

Lighting up single-nucleotide variation in situ in single cells and tissues

In situ single-nucleotide variation (SNV) imaging technologies are summarized for depicting detailed pictures of SNVs in single cells or tissues.