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代谢组学和机器学习技术表明,发芽提高了有色稻米的多种营养特性。

Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice.

机构信息

Consumer-driven Grain Quality and Nutrition Center, Strategic Innovation Platform, International Rice Research Institute, Los Baños, 4030, Philippines.

Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany.

出版信息

Commun Biol. 2023 Oct 2;6(1):1000. doi: 10.1038/s42003-023-05379-9.

Abstract

Enhancing the dietary properties of rice is crucial to contribute to alleviating hidden hunger and non-communicable diseases in rice-consuming countries. Germination is a bioprocessing approach to increase the bioavailability of nutrients in rice. However, there is a scarce information on how germination impacts the overall nutritional profile of pigmented rice sprouts (PRS). Herein, we demonstrated that germination resulted to increase levels of certain dietary compounds, such as free phenolics and micronutrients (Ca, Na, Fe, Zn, riboflavin, and biotin). Metabolomic analysis revealed the preferential accumulation of dipeptides, GABA, and flavonoids in the germination process. Genome-wide association studies of the PRS suggested the activation of specific genes such as CHS1 and UGT genes responsible for increasing certain flavonoid compounds. Haplotype analyses showed a significant difference (P < 0.05) between alleles associated with these genes. Genetic markers associated with these flavonoids were incorporated into the random forest model, improving the accuracy of prediction of multi-nutritional properties from 89.7% to 97.7%. Deploying this knowledge to breed rice with multi-nutritional properties will be timely to address double burden nutritional challenges.

摘要

提高大米的食用特性对于缓解大米消费国中隐性饥饿和非传染性疾病至关重要。发芽是一种生物加工方法,可以提高大米中营养物质的生物利用度。然而,关于发芽如何影响有色水稻芽(PR)的整体营养状况的信息却很少。在此,我们证明发芽导致某些膳食化合物(如游离酚类物质和微量营养素(Ca、Na、Fe、Zn、核黄素和生物素)水平升高。代谢组学分析表明,在发芽过程中,二肽、GABA 和类黄酮优先积累。对 PRS 的全基因组关联研究表明,特定基因(如负责增加某些类黄酮化合物的 CHS1 和 UGT 基因)被激活。单倍型分析显示,与这些基因相关的等位基因之间存在显著差异(P<0.05)。与这些类黄酮相关的遗传标记被纳入随机森林模型,将多营养特性预测的准确性从 89.7%提高到 97.7%。利用这方面的知识培育具有多种营养特性的水稻,将及时应对双重营养负担的挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02ba/10545681/925f0c090fca/42003_2023_5379_Fig1_HTML.jpg

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