The Post-CRISPR Toolkit: Prime Editing, RNA Editing, and Programmable Integration
Keywords:
prime editing, RNA editing, programmable integration, post-CRISPR technologies, genome engineering, transcriptome editing, PASTE, gene therapyAbstract
The rapid evolution of genome engineering has extended the field beyond conventional CRISPR-Cas9 nucleases toward a broader set of precision editing platforms. Although CRISPR-Cas9 transformed modern molecular biology by enabling programmable DNA cleavage, its reliance on double-strand breaks and endogenous repair pathways can produce undesired insertions, deletions, chromosomal rearrangements, and inconsistent editing outcomes (Lee et al., 2025; Chen et al., 2024). In response, new editing modalities have emerged to improve precision, flexibility, and safety in both experimental and therapeutic settings. Among these, prime editing offers a search-and-replace strategy capable of introducing precise substitutions, small insertions, and deletions without requiring donor DNA templates or double-strand DNA cleavage (Lee et al., 2025). In parallel, RNA editing platforms, including ADAR-based systems and CRISPR-Cas13-derived approaches, provide reversible correction at the transcript level and may reduce the long-term risks associated with permanent genome modification (Booth et al., 2023; Lo et al., 2022; Yang & Patel, 2024). Complementing these tools, programmable integration systems such as PASTE and CRISPR-associated transposon platforms are designed to overcome a major limitation of classic editing methods: the efficient, site-specific insertion of larger genetic payloads (Yarnall et al., 2023; Wang et al., 2023). Together, these technologies represent a conceptual shift from DNA cutting alone toward precise rewriting, reversible transcript correction, and targeted genomic installation. This article introduces the major components of the post-CRISPR toolkit and outlines their significance for the future of precision medicine, functional genomics, and next-generation gene therapy (Anzalone et al., 2019; Chen & Liu, 2023; Booth et al., 2023; Yarnall et al., 2023).
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