Systematic pegRNA design with PRIDICT2.0 and ePRIDICT for efficient prime editing.

ABSTRACT: Prime editing is a versatile genome editing technology that enables precise genetic modifications without inducing DNA double-strand breaks. Owing to numerous variables in the prime editing guide RNA (pegRNA) design, experimentally identifying the most efficient pegRNA for a specific locus and edit is laborious. Therefore, we have developed computational tools to streamline this process. Here we present a comprehensive protocol detailing how to use PRIDICT2.0 and ePRIDICT, machine-learning models that assess the influence of the pegRNA design and chromatin context on prime editing. PRIDICT2.0 is an ensemble of attention-based bidirectional recurrent neural networks that predicts pegRNA efficiencies for replacements, insertions or deletions in different cellular contexts. Compared with othe

SUBMITTER: Mathis N 

PROVIDER: S-EPMC7619000 | biostudies-literature | 2026 Apr

REPOSITORIES: biostudies-literature