Multi-Omics Discovery of Yield and Disease-Resistance Traits in Rapeseed Improvement
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Abstract
Rapeseed is a globally significant oilseed crop, providing essential edible oils for human consumption, high-protein meal for livestock, and renewable raw materials for biofuel production. As the global population expands and climate change introduces unprecedented environmental stresses, enhancing the yield and disease resistance of rapeseed has become a paramount objective for agricultural researchers. Traditional breeding programs, which rely predominantly on phenotypic selection and single-marker assisted breeding, have achieved substantial historical gains but are increasingly constrained by the narrow genetic base of modern cultivars and the complex, polygenic nature of key agronomic traits. This paper provides a comprehensive analysis of how the paradigm of crop improvement has shifted toward systems biology, specifically through the integration of multi-omics technologies. By combining genomics, transcriptomics, proteomics, and metabolomics, researchers can now delineate the complex regulatory networks that govern plant architecture, seed development, lipid biosynthesis, and basal immunity. This review critically examines the methodologies employed in multi-omics integration, highlighting both computational frameworks and empirical validation strategies. Furthermore, the discussion elucidates the molecular mechanisms underpinning yield determination and defense responses against devastating fungal pathogens such as Sclerotinia sclerotiorum. The synthesis of multi-omics data not only accelerates the discovery of novel quantitative trait loci but also facilitates the design of next-generation ideotypes via targeted genome editing. Ultimately, this comprehensive approach bridges the genotype-to-phenotype gap, ensuring sustainable rapeseed production in an era of global agricultural volatility.
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