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, 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.
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Subjects: | Oryza sativa, génotype, banque de gènes, variation génétique, riz, marqueur génétique, grain, génome, zinc, essai de variété, variété, amélioration génétique, http://aims.fao.org/aos/agrovoc/c_5438, http://aims.fao.org/aos/agrovoc/c_3225, http://aims.fao.org/aos/agrovoc/c_11116, http://aims.fao.org/aos/agrovoc/c_15975, http://aims.fao.org/aos/agrovoc/c_6599, http://aims.fao.org/aos/agrovoc/c_24030, http://aims.fao.org/aos/agrovoc/c_3346, http://aims.fao.org/aos/agrovoc/c_3224, http://aims.fao.org/aos/agrovoc/c_8517, http://aims.fao.org/aos/agrovoc/c_26833, http://aims.fao.org/aos/agrovoc/c_8157, http://aims.fao.org/aos/agrovoc/c_49902, http://aims.fao.org/aos/agrovoc/c_4510, |
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dig-cirad-fr-6033172024-12-18T13:17:19Z http://agritrop.cirad.fr/603317/ http://agritrop.cirad.fr/603317/ Genomic prediction of zinc-biofortification potential in rice gene bank accessions. Rakotondramanana Mbolatantely, Tanaka Ryokei, Pariasca-Tanaka Juan, Stangoulis James, Grenier Cécile, Wissuwa Matthias. 2022. Theoretical and Applied Genetics, 135 : 2265-2278.https://doi.org/10.1007/s00122-022-04110-2 <https://doi.org/10.1007/s00122-022-04110-2> Genomic prediction of zinc-biofortification potential in rice gene bank accessions Rakotondramanana, Mbolatantely Tanaka, Ryokei Pariasca-Tanaka, Juan Stangoulis, James Grenier, Cécile Wissuwa, Matthias eng 2022 Springer Theoretical and Applied Genetics Oryza sativa génotype banque de gènes variation génétique riz marqueur génétique grain génome zinc essai de variété variété amélioration génétique http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_11116 http://aims.fao.org/aos/agrovoc/c_15975 http://aims.fao.org/aos/agrovoc/c_6599 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_3346 http://aims.fao.org/aos/agrovoc/c_3224 http://aims.fao.org/aos/agrovoc/c_8517 http://aims.fao.org/aos/agrovoc/c_26833 http://aims.fao.org/aos/agrovoc/c_8157 http://aims.fao.org/aos/agrovoc/c_49902 Madagascar http://aims.fao.org/aos/agrovoc/c_4510 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. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/603317/7/603317.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1007/s00122-022-04110-2 10.1007/s00122-022-04110-2 info:eu-repo/semantics/altIdentifier/doi/10.1007/s00122-022-04110-2 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1007/s00122-022-04110-2 |
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Oryza sativa génotype banque de gènes variation génétique riz marqueur génétique grain génome zinc essai de variété variété amélioration génétique http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_11116 http://aims.fao.org/aos/agrovoc/c_15975 http://aims.fao.org/aos/agrovoc/c_6599 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_3346 http://aims.fao.org/aos/agrovoc/c_3224 http://aims.fao.org/aos/agrovoc/c_8517 http://aims.fao.org/aos/agrovoc/c_26833 http://aims.fao.org/aos/agrovoc/c_8157 http://aims.fao.org/aos/agrovoc/c_49902 http://aims.fao.org/aos/agrovoc/c_4510 Oryza sativa génotype banque de gènes variation génétique riz marqueur génétique grain génome zinc essai de variété variété amélioration génétique http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_11116 http://aims.fao.org/aos/agrovoc/c_15975 http://aims.fao.org/aos/agrovoc/c_6599 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_3346 http://aims.fao.org/aos/agrovoc/c_3224 http://aims.fao.org/aos/agrovoc/c_8517 http://aims.fao.org/aos/agrovoc/c_26833 http://aims.fao.org/aos/agrovoc/c_8157 http://aims.fao.org/aos/agrovoc/c_49902 http://aims.fao.org/aos/agrovoc/c_4510 |
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Oryza sativa génotype banque de gènes variation génétique riz marqueur génétique grain génome zinc essai de variété variété amélioration génétique http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_11116 http://aims.fao.org/aos/agrovoc/c_15975 http://aims.fao.org/aos/agrovoc/c_6599 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_3346 http://aims.fao.org/aos/agrovoc/c_3224 http://aims.fao.org/aos/agrovoc/c_8517 http://aims.fao.org/aos/agrovoc/c_26833 http://aims.fao.org/aos/agrovoc/c_8157 http://aims.fao.org/aos/agrovoc/c_49902 http://aims.fao.org/aos/agrovoc/c_4510 Oryza sativa génotype banque de gènes variation génétique riz marqueur génétique grain génome zinc essai de variété variété amélioration génétique http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_11116 http://aims.fao.org/aos/agrovoc/c_15975 http://aims.fao.org/aos/agrovoc/c_6599 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_3346 http://aims.fao.org/aos/agrovoc/c_3224 http://aims.fao.org/aos/agrovoc/c_8517 http://aims.fao.org/aos/agrovoc/c_26833 http://aims.fao.org/aos/agrovoc/c_8157 http://aims.fao.org/aos/agrovoc/c_49902 http://aims.fao.org/aos/agrovoc/c_4510 Rakotondramanana, Mbolatantely Tanaka, Ryokei Pariasca-Tanaka, Juan Stangoulis, James Grenier, Cécile Wissuwa, Matthias Genomic prediction of zinc-biofortification potential in rice gene bank accessions |
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 |
article |
topic_facet |
Oryza sativa génotype banque de gènes variation génétique riz marqueur génétique grain génome zinc essai de variété variété amélioration génétique http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_11116 http://aims.fao.org/aos/agrovoc/c_15975 http://aims.fao.org/aos/agrovoc/c_6599 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_3346 http://aims.fao.org/aos/agrovoc/c_3224 http://aims.fao.org/aos/agrovoc/c_8517 http://aims.fao.org/aos/agrovoc/c_26833 http://aims.fao.org/aos/agrovoc/c_8157 http://aims.fao.org/aos/agrovoc/c_49902 http://aims.fao.org/aos/agrovoc/c_4510 |
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 |
title |
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_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_sort |
genomic prediction of zinc-biofortification potential in rice gene bank accessions |
publisher |
Springer |
url |
http://agritrop.cirad.fr/603317/ http://agritrop.cirad.fr/603317/7/603317.pdf |
work_keys_str_mv |
AT rakotondramananambolatantely genomicpredictionofzincbiofortificationpotentialinricegenebankaccessions AT tanakaryokei genomicpredictionofzincbiofortificationpotentialinricegenebankaccessions AT pariascatanakajuan genomicpredictionofzincbiofortificationpotentialinricegenebankaccessions AT stangoulisjames genomicpredictionofzincbiofortificationpotentialinricegenebankaccessions AT greniercecile genomicpredictionofzincbiofortificationpotentialinricegenebankaccessions AT wissuwamatthias genomicpredictionofzincbiofortificationpotentialinricegenebankaccessions |
_version_ |
1819044735315083264 |