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

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 germin...

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Autores principales: Tiozon, Rhowell Jr. N., Sreenivasulu, Nese, Alseekh, Saleh, Sartagoda, Kristel June D., Usadel, Björn, Fernie, Alisdair R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545681/
https://www.ncbi.nlm.nih.gov/pubmed/37783812
http://dx.doi.org/10.1038/s42003-023-05379-9
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author Tiozon, Rhowell Jr. N.
Sreenivasulu, Nese
Alseekh, Saleh
Sartagoda, Kristel June D.
Usadel, Björn
Fernie, Alisdair R.
author_facet Tiozon, Rhowell Jr. N.
Sreenivasulu, Nese
Alseekh, Saleh
Sartagoda, Kristel June D.
Usadel, Björn
Fernie, Alisdair R.
author_sort Tiozon, Rhowell Jr. N.
collection PubMed
description 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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spelling pubmed-105456812023-10-04 Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice Tiozon, Rhowell Jr. N. Sreenivasulu, Nese Alseekh, Saleh Sartagoda, Kristel June D. Usadel, Björn Fernie, Alisdair R. Commun Biol Article 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. Nature Publishing Group UK 2023-10-02 /pmc/articles/PMC10545681/ /pubmed/37783812 http://dx.doi.org/10.1038/s42003-023-05379-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Tiozon, Rhowell Jr. N.
Sreenivasulu, Nese
Alseekh, Saleh
Sartagoda, Kristel June D.
Usadel, Björn
Fernie, Alisdair R.
Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
title Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
title_full Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
title_fullStr Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
title_full_unstemmed Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
title_short Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
title_sort metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545681/
https://www.ncbi.nlm.nih.gov/pubmed/37783812
http://dx.doi.org/10.1038/s42003-023-05379-9
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