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Article Abstract

Legumes are essential for agriculture and food security. Biotic and abiotic stresses pose significant challenges to legume production, lowering productivity levels. Most legumes must be genetically improved by introducing alleles that give pest and disease resistance, abiotic stress adaptability, and high yield potential. The quickest way to develop high-yielding elite legume varieties with long-lasting resistance is to tap into potential resistance alleles present in landraces and wild relatives and exploit them in legume resistance breeding programs using next-generation molecular breeding methods. Most of the reviews focus on the advancements made by genome editing technologies in generating climate-tolerant legumes for breeding. This review discusses the challenges of genome-based editing tools and how the integration of other popular breeding methodologies, such as QTLs and GWAS, as well as computational techniques, can aid in the development of climate-tolerant legume crops. This review highlights genomics-based methodologies and recent advances that make it easier to assess genetic diversity and uncover adaptive genes in legumes. Computational approaches, such as machine learning, are important in mining the breeding-related genes identified by CRISPR and other genomic tools, as well as detecting the key elements and factors that regulate the expression of these genes, which addresses the challenge of developing climate-resilient legume crops.

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http://dx.doi.org/10.1007/s11103-025-01637-yDOI Listing

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