Advances in gene editing for legume improvement: technologies, progress, and prospects

Legumes are among the most important protein-rich crops in global agri-food systems. To meet the rising protein demand of a growing population, significant efforts are underway to enhance legume yield, nutritional quality, and resilience to environmental stresses through the manipulation of key genetic traits. Advanced technologies-including genetic engineering, gene editing, genomic selection, next-generation sequencing, single-cell genomics, and multi-omics-are accelerating legume improvement due to their high precision and efficiency. This review focuses on major gene-editing technologies, namely, CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9), TALENs (Transcription Activator-Like Effector Nucleases), ZFNs (Zinc Finger Nucleases), base editing (BE), and prime editing (PE), and their applications in key legume crops such as soybean ( Glycine max ), cowpea ( Vigna unguiculata ), chickpea ( Cicer arietinum ), groundnut ( Arachis hypogaea ), pea ( Pisum sativum ), barrel clover ( Medicago truncatula ), alfalfa ( Medicago sativa ), and Lotus japonicus . Among these platforms, CRISPR/Cas9 is the most widely adopted in legumes, largely due to its simplicity, versatility, and dependence on accurate genome sequence information and guide RNA (gRNA) design. Advances in next-generation sequencing and the growing availability of intuitive online gRNA design tools have streamlined CRISPR workflows, improving accessibility and precision. The present review indicates that CRISPR-P is the most used gRNA design tool in legume research, likely due to its early development for plant systems and integrated off-target prediction features. Therefore, alongside reviewing gene-editing applications, we emphasized the critical role of robust gRNA design tools as a foundation for successful genome editing. Future integration of artificial intelligence and large language models is expected to further enhance target prediction accuracy, minimize off-target effects, and enable more precise genome-editing strategies in legumes.