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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-y | DOI Listing |
Insect Biochem Mol Biol
September 2025
Jiangxi Provincial Key Laboratory of Pest and Disease Control of Featured Horticultural Plants, College of Life Sciences, Gannan Normal University, Ganzhou 341000, China. Electronic address:
The diamondback moth (Plutella xylostella), a globally destructive pest, has Brassicaceae as its long-term co-evolved host and can also utilize Fabaceae as an alternative field host. The primary differential factor between these plant families is glucosinolates (GLs). Conventional transcriptome data revealed high midgut expression of glucosinolate sulfatases (GSSs) in response to glucosinolates.
View Article and Find Full Text PDFTheor Appl Genet
September 2025
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
The German Federal Ex Situ Genebank for Agricultural and Horticultural Crops (IPK) harbours over 3000 pea plant genetic resources (PGRs), backed up by corresponding information across 16 key agronomic and economical traits. The unbalanced structure and inconsistent format of this historical data has precluded effective leverage of genebank accessions, despite the opportunities contained in its genetic diversity. Therefore, a three-step statistical approach founded in linear mixed models was implemented to enable a rigorous and targeted data curation.
View Article and Find Full Text PDFGlob Chang Biol
September 2025
Department of Agronomy, Purdue University, West Lafayette, Indiana, USA.
Understanding how interactive management practices and climatic behavior influence soybean [Glycine max (L.) Merr.] productivity is imperative to inform future production systems under changing climate.
View Article and Find Full Text PDFPlant Mol Biol
September 2025
Institute of Biological Chemistry, The Washington State University, Pullman, WA, 99164, USA.
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.
View Article and Find Full Text PDFMol Biol Rep
September 2025
Department of Agronomy, Faculty of Agriculture and Environment, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan.
Chitinases, enzymes responsible for hydrolyzing chitin, a significant component of fungal cell walls, play a crucial role in plant defense mechanisms, growth, symbiotic relationships, and stress resistance. In this study, we identified 27 chitinase genes in chickpeas (CaChi) and classified them into five classes based on phylogenetic analysis. Overall, chitinase genes are clustered on eight chromosomes.
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