AI-designed OpenCRISPR-1 enables efficient targeted mutagenesis and prime editing in rice

Recent advances in generative artificial intelligence (AI) have enabled the de novo design of genome editing nucleases, exampled by OpenCRISPR-1, offering an open-source alternative to naturally evolved CRISPR systems and expanding "freedom to operate" (FTO). Here, we report the development and systematic validation of a monocot-optimized OpenCRISPR-1-based genome editing ecosystem in rice ( Oryza sativa ). By targeting the OsSWEET susceptibility gene family, we demonstrate that OpenCRISPR-1 supports robust multiplexed editing in both rice calli and stable T0 plants, with mutation frequencies reaching up to 100%. Deep sequencing revealed that the OpenCRISPR-1 mutational landscape mirrors that of Streptococcus pyogenes Cas9 (SpCas9), facilitating predictable loss-of-function alleles that confer broad-spectrum resistance to bacterial blight. To enable a fully open-source platform, we integrated an AI-designed Open sgRNA scaffold (OpsgRNA), which maintained high editing efficacy across multiple target loci. Furthermore, we expanded the toolkit by engineering OpenPE6c, an OpenCRISPR-1-based prime editing system. In rice protoplasts, OpenPE6c exhibited precise editing rates comparable to canonical SpCas9-PE6c while significantly reducing imprecise byproducts, suggesting enhanced fidelity inherent to the AI-designed nuclease. Our results establish OpenCRISPR-1 as a versatile, high-performance, and public-access platform for advanced plant genome engineering, offering a transparent framework for the global democratization of precision crop breeding.