Genomic prediction of zinc-biofortification potential in rice gene bank accessions
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, ric...
| Autores principales: | , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
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Springer
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/171493 |
| _version_ | 1855538738228101120 |
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| author | Rakotondramanana, Mbolatantely Tanaka, Ryokei Pariasca-Tanaka, Juan Stangoulis, James Grenier, Cécile Wissuwa, Matthias |
| author_browse | Grenier, Cécile Pariasca-Tanaka, Juan Rakotondramanana, Mbolatantely Stangoulis, James Tanaka, Ryokei Wissuwa, Matthias |
| author_facet | Rakotondramanana, Mbolatantely Tanaka, Ryokei Pariasca-Tanaka, Juan Stangoulis, James Grenier, Cécile Wissuwa, Matthias |
| author_sort | Rakotondramanana, Mbolatantely |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace171493 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1714932025-02-19T14:31:32Z Genomic prediction of zinc-biofortification potential in rice gene bank accessions Rakotondramanana, Mbolatantely Tanaka, Ryokei Pariasca-Tanaka, Juan Stangoulis, James Grenier, Cécile Wissuwa, Matthias biofortification zinc grain farms genomics models rice nutrition trace elements yields gene banks 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. 2022-07 2025-01-29T12:58:15Z 2025-01-29T12:58:15Z Journal Article https://hdl.handle.net/10568/171493 en Open Access Springer Rakotondramanana, Mbolatantely; Tanaka, Ryokei; Pariasca-Tanaka, Juan; Stangoulis, James; Grenier, Cécile; and Wissuwa, Matthias. 2022. Genomic prediction of zinc-biofortification potential in rice gene bank accessions. Theoretical and Applied Genetics 135: 2265-2278. https://doi.org/10.1007/s00122-022-04110-2 |
| spellingShingle | biofortification zinc grain farms genomics models rice nutrition trace elements yields gene banks 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 | biofortification zinc grain farms genomics models rice nutrition trace elements yields gene banks |
| url | https://hdl.handle.net/10568/171493 |
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