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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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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. |
format | Online Article Text |
id | pubmed-9271118 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
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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