Journal Article

FZJ-2023-03882

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice

Tiozon, R. J. N. ; Sreenivasulu, N. ; Alseekh, S. ; Sartagoda, K. J. D. ; Usadel, B.FZJ* ; Fernie, A. R. (Corresponding author)

2023
Springer Nature London

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Please use a persistent id in citations: doi:10.1038/s42003-023-05379-9  doi:10.34734/FZJ-2023-03882

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

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Contributing Institute(s):

1. Bioinformatik (IBG-4)

Research Program(s):

1. 2171 - Biological and environmental resources for sustainable use (POF4-217) (POF4-217)

Appears in the scientific report 2023

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