PrimeDesign software for rapid and simplified design of prime editing guide RNAs

Abstract

Prime editing (PE) is a versatile genome editing technology, but design of the required guide RNAs is more complex than for standard CRISPR-based nucleases or base editors. Here we describe PrimeDesign, a user-friendly, end-to-end web application and command-line tool for the design of PE experiments. PrimeDesign can be used for single and combination editing applications, as well as genome-wide and saturation mutagenesis screens. Using PrimeDesign, we construct PrimeVar, a comprehensive and searchable database that includes candidate prime editing guide RNA (pegRNA) and nicking sgRNA (ngRNA) combinations for installing or correcting >68,500 pathogenic human genetic variants from the ClinVar database. Finally, we use PrimeDesign to design pegRNAs/ngRNAs to install a variety of human pathogenic variants in human cells.

Precise genome engineering in Drosophila using prime editing

“…We deliberately selected pegRNA spacer sequences based on previously validated sgRNAs (Methods), but this might have led to better than average editing efficiency. The recent introduction of software tools has made pegRNA design easier (49)(50)(51)(52). When possible, we recommend testing editing efficiency in cultured cells before proceeding in vivo.…”

Easy-Prime: a machine learning–based prime editor design tool

“…We selected 23 PE-related features in five categories (Fig. 1a , Additional file 2 : Table S1): (1) the spCas9 activity feature predicted by DeepSpCas9 [ 19 ]); (2) oligo features, which include the length and GC content of the PBS and RTT; (3) target mutation features, which include mutation types such as single-nucleotide mutations or indels, and whether a target mutation disrupts the PAM sequence or the protospacer of the ngRNA (i.e., PE3b); (4) position features, which are the relative distances from the pegRNA nick site to the target mutation (Target_pos), from the pegRNA nick site to the ngRNA nick site (ngRNA_pos or nick position [ 8 ]), and from the target mutation to the end of the RTT (Target_end_flank or minimal homology downstream of the edit [ 12 ]); and (5) RNA folding features, which calculate the probability of different positions (i.e., the first 10 positions) on the RTT sequence disrupting the secondary structure of the RNA scaffold (i.e., the RNA-folding disruption score, see Methods).

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“…1c ). We further assessed the performance of our model using an independent dataset consisting of 33 PE3 data [ 12 ]. The correlation coefficient is 0.5 (Fig.…”

“…3a ). To further compare the performance between the machine learning based Easy-Prime and the heuristic rules-based programs, we edited 5 loci using pegRNA and ngRNA recommended by PrimeDesign [ 12 ]. The sgRNA sequences are exactly the same between Easy-Prime and PrimeDesign.…”

“…However, one major issue in the current PE system is the pegRNA/ngRNA design, which is much more complicated than the design process associated with other precise editing methods. Several programs (PrimeDesign [ 12 ], PegFinder [ 13 ], primeedit.nygenome [ 14 ], PnB Designer [ 15 ], PINE-CONE [ 16 ], DeepPE [ 17 ], and PE-Designer [ 18 ]) have been developed to simplify the search for pegRNAs and ngRNAs for prime editing by following general design guidance proposed in the original prime editing paper [ 8 ]. However, how to unbiasedly optimize the combination of all of these features and identifying the most suitable sequence from a list of candidates remains problematic.…”