This work provides a foundation for developing rice varieties with enhanced lipid content, supporting the growing global demand for high-quality rice.
Abstract
Rice bran oil (RBO) is highly valued for its beneficial fatty acid profile and wide applications in the food, pharmaceutical and skincare industries. It offers numerous health benefits, including reduced bad cholesterol and antioxidant activity, due to its high levels of vitamin E and γ-oryzanol. Enhancing oil composition and understanding the complex genetic architecture underlying lipid metabolism are, therefore, critical for improving RBO quality. The complexity of quantitative trait loci (QTL) and their environmental interactions has constrained their application in rice breeding. However, Meta-QTL (M-QTL) analysis can streamline this QTL information, identifying stable QTL and candidate genes for introgression. In this study, a M-QTL approach was employed to identify stable QTLs influencing RBO quality. Fourteen independent linkage mapping studies were integrated to construct a high-density consensus map spanning 3029.6 cM with 1523 markers. The analysis identified 19 stable M-QTLs and 133 putative candidate genes associated with lipid metabolism. KEGG pathway analysis highlighted 20 key genes essential for lipid biosynthesis, while haplotype analysis and gene–metabolite interaction mapping provided further insight into the regulation of lipid content in RBO. This work provides a foundation for developing rice varieties with enhanced lipid content, supporting the growing global demand for high-quality rice.
This study bridges the gap between high-resolution genetic dissection and predictive breeding, providing a practical framework to accelerate oil yield improvement in rapeseed.
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