Abstract
Prime editing is a versatile genome-editing technique that shows great promise for the generation and repair of patient mutations. However, some genomic sites are difficult to edit and optimal design of prime-editing tools remains elusive. Here we present a fluorescent prime editing and enrichment reporter (fluoPEER), which can be tailored to any genomic target site. This system rapidly and faithfully ranks the efficiency of prime edit guide RNAs (pegRNAs) combined with any prime editor variant. We apply fluoPEER to instruct correction of pathogenic variants in patient cells and find that plasmid editing enriches for genomic editing up to 3-fold compared to conventional enrichment strategies. DNA repair and cell cycle-related genes are enriched in the transcriptome of edited cells. Stalling cells in the G1/S boundary increases prime editing efficiency up to 30%. Together, our results show that fluoPEER can be employed for rapid and efficient correction of patient cells, selection of gene-edited cells, and elucidation of cellular mechanisms needed for successful prime editing.
Highlights
Prime editing is a versatile genome-editing technique that shows great promise for the generation and repair of patient mutations
If the genomic target mutation results in a premature stop codon or a frameshift, the unmodified genomic target site can be inserted into the fluoPEER plasmid, resulting in a construct that only expresses GFP
This system allows targeting of the reporter and the corresponding genomic locus with the same prime edit guide RNAs (pegRNAs) design
Summary
Prime editing is a versatile genome-editing technique that shows great promise for the generation and repair of patient mutations. We present a fluorescent prime editing and enrichment reporter (fluoPEER), which can be tailored to any genomic target site This system rapidly and faithfully ranks the efficiency of prime edit guide RNAs (pegRNAs) combined with any prime editor variant. The spacer region of the pegRNA is homologous to the genomic target region and guides the prime editor to create a single-strand DNA break (nick) at the specified location. The pathogenic mutations described in the ClinVar database have only one nearby NGG-PAM (Supplementary Fig. 1) This limits pegRNA design to often suboptimal spacers and PBSs and thereby reduces gene-editing efficiency. Prime editor variants with flexible PAM recognition[6–8] provide at least nine additional PAM sites to target the pathogenic mutations described within the ClinVar database and thereby greatly improve gene-editing potential (Supplementary Fig. 1). This deep learning algorithm failed to predict a pegRNA efficiency score for
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