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Genomic prediction of zinc-biofortification potential in rice gene bank accessions

KEY MESSAGE: A genomic prediction model successfully predicted grain Zn concentrations in 3000 gene bank accessions and this was verified experimentally with selected potential donors having high on-farm grain-Zn in Madagascar. ABSTRACT: Increasing zinc (Zn) concentrations in edible parts of food cr...

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Autores principales: Rakotondramanana, Mbolatantely, Tanaka, Ryokei, Pariasca-Tanaka, Juan, Stangoulis, James, Grenier, Cécile, Wissuwa, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271118/
https://www.ncbi.nlm.nih.gov/pubmed/35618915
http://dx.doi.org/10.1007/s00122-022-04110-2
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author Rakotondramanana, Mbolatantely
Tanaka, Ryokei
Pariasca-Tanaka, Juan
Stangoulis, James
Grenier, Cécile
Wissuwa, Matthias
author_facet Rakotondramanana, Mbolatantely
Tanaka, Ryokei
Pariasca-Tanaka, Juan
Stangoulis, James
Grenier, Cécile
Wissuwa, Matthias
author_sort Rakotondramanana, Mbolatantely
collection PubMed
description KEY MESSAGE: A genomic prediction model successfully predicted grain Zn concentrations in 3000 gene bank accessions and this was verified experimentally with selected potential donors having high on-farm grain-Zn in Madagascar. ABSTRACT: Increasing zinc (Zn) concentrations in edible parts of food crops, an approach termed Zn-biofortification, is a global breeding objective to alleviate micro-nutrient malnutrition. In particular, infants in countries like Madagascar are at risk of Zn deficiency because their dominant food source, rice, contains insufficient Zn. Biofortified rice varieties with increased grain Zn concentrations would offer a solution and our objective is to explore the genotypic variation present among rice gene bank accessions and to possibly identify underlying genetic factors through genomic prediction and genome-wide association studies (GWAS). A training set of 253 rice accessions was grown at two field sites in Madagascar to determine grain Zn concentrations and grain yield. A multi-locus GWAS analysis identified eight loci. Among these, QTN_11.3 had the largest effect and a rare allele increased grain Zn concentrations by 15%. A genomic prediction model was developed from the above training set to predict Zn concentrations of 3000 sequenced rice accessions. Predicted concentrations ranged from 17.1 to 40.2 ppm with a prediction accuracy of 0.51. An independent confirmation with 61 gene bank seed samples provided high correlations (r = 0.74) between measured and predicted values. Accessions from the aus sub-species had the highest predicted grain Zn concentrations and these were confirmed in additional field experiments, with one potential donor having more than twice the grain Zn compared to a local check variety. We conclude utilizing donors from the aus sub-species and employing genomic selection during the breeding process is the most promising approach to raise grain Zn concentrations in rice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-022-04110-2.
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spelling pubmed-92711182022-07-11 Genomic prediction of zinc-biofortification potential in rice gene bank accessions Rakotondramanana, Mbolatantely Tanaka, Ryokei Pariasca-Tanaka, Juan Stangoulis, James Grenier, Cécile Wissuwa, Matthias Theor Appl Genet Original Article KEY MESSAGE: A genomic prediction model successfully predicted grain Zn concentrations in 3000 gene bank accessions and this was verified experimentally with selected potential donors having high on-farm grain-Zn in Madagascar. ABSTRACT: Increasing zinc (Zn) concentrations in edible parts of food crops, an approach termed Zn-biofortification, is a global breeding objective to alleviate micro-nutrient malnutrition. In particular, infants in countries like Madagascar are at risk of Zn deficiency because their dominant food source, rice, contains insufficient Zn. Biofortified rice varieties with increased grain Zn concentrations would offer a solution and our objective is to explore the genotypic variation present among rice gene bank accessions and to possibly identify underlying genetic factors through genomic prediction and genome-wide association studies (GWAS). A training set of 253 rice accessions was grown at two field sites in Madagascar to determine grain Zn concentrations and grain yield. A multi-locus GWAS analysis identified eight loci. Among these, QTN_11.3 had the largest effect and a rare allele increased grain Zn concentrations by 15%. A genomic prediction model was developed from the above training set to predict Zn concentrations of 3000 sequenced rice accessions. Predicted concentrations ranged from 17.1 to 40.2 ppm with a prediction accuracy of 0.51. An independent confirmation with 61 gene bank seed samples provided high correlations (r = 0.74) between measured and predicted values. Accessions from the aus sub-species had the highest predicted grain Zn concentrations and these were confirmed in additional field experiments, with one potential donor having more than twice the grain Zn compared to a local check variety. We conclude utilizing donors from the aus sub-species and employing genomic selection during the breeding process is the most promising approach to raise grain Zn concentrations in rice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-022-04110-2. Springer Berlin Heidelberg 2022-05-26 2022 /pmc/articles/PMC9271118/ /pubmed/35618915 http://dx.doi.org/10.1007/s00122-022-04110-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Original Article
Rakotondramanana, Mbolatantely
Tanaka, Ryokei
Pariasca-Tanaka, Juan
Stangoulis, James
Grenier, Cécile
Wissuwa, Matthias
Genomic prediction of zinc-biofortification potential in rice gene bank accessions
title Genomic prediction of zinc-biofortification potential in rice gene bank accessions
title_full Genomic prediction of zinc-biofortification potential in rice gene bank accessions
title_fullStr Genomic prediction of zinc-biofortification potential in rice gene bank accessions
title_full_unstemmed Genomic prediction of zinc-biofortification potential in rice gene bank accessions
title_short Genomic prediction of zinc-biofortification potential in rice gene bank accessions
title_sort genomic prediction of zinc-biofortification potential in rice gene bank accessions
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271118/
https://www.ncbi.nlm.nih.gov/pubmed/35618915
http://dx.doi.org/10.1007/s00122-022-04110-2
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