Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice

Over half of the world’s arable land is acidic, which constrains cereal production. In South America, different rice-growing regions (Cerrado in Brazil and Llanos in Colombia and Venezuela) are particularly affected due to high aluminum toxicity levels. For this reason, efforts have been made to bre...

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Autores principales: Bartholomé, Jerome, Ospina, José Omar, Sandoval, Mario, Espinosa, Natalia, Arcos, Jairo, Ospina, Yolima, Frouin, Julien, Beartschi, Cédric, Ghneim, Thaura, Grenier, Cecile
Formato: Journal Article
Lenguaje:Inglés
Publicado: 2024
Materias:
Acceso en línea:https://hdl.handle.net/10568/168939
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author Bartholomé, Jerome
Ospina, José Omar
Sandoval, Mario
Espinosa, Natalia
Arcos, Jairo
Ospina, Yolima
Frouin, Julien
Beartschi, Cédric
Ghneim, Thaura
Grenier, Cecile
author_browse Arcos, Jairo
Bartholomé, Jerome
Beartschi, Cédric
Espinosa, Natalia
Frouin, Julien
Ghneim, Thaura
Grenier, Cecile
Ospina, José Omar
Ospina, Yolima
Sandoval, Mario
author_facet Bartholomé, Jerome
Ospina, José Omar
Sandoval, Mario
Espinosa, Natalia
Arcos, Jairo
Ospina, Yolima
Frouin, Julien
Beartschi, Cédric
Ghneim, Thaura
Grenier, Cecile
author_sort Bartholomé, Jerome
collection Repository of Agricultural Research Outputs (CGSpace)
description Over half of the world’s arable land is acidic, which constrains cereal production. In South America, different rice-growing regions (Cerrado in Brazil and Llanos in Colombia and Venezuela) are particularly affected due to high aluminum toxicity levels. For this reason, efforts have been made to breed for tolerance to aluminum toxicity using synthetic populations. The breeding program of CIAT-CIRAD is a good example of the use of recurrent selection to increase productivity for the Llanos in Colombia. In this study, we evaluated the performance of genomic prediction models to optimize the breeding scheme by hastening the development of an improved synthetic population and elite lines. We characterized 334 families at the S 0:4 generation in two conditions. One condition was the control, managed with liming, while the other had high aluminum toxicity. Four traits were considered: days to flowering (FL), plant height (PH), grain yield (YLD), and zinc concentration in the polished grain (ZN). The population presented a high tolerance to aluminum toxicity, with more than 72% of the families showing a higher yield under aluminum conditions. The performance of the families under the aluminum toxicity condition was predicted using four different models: a single-environment model and three multi-environment models. The multi-environment models differed in the way they integrated genotype-by-environment interactions. The best predictive abilities were achieved using multi-environment models: 0.67 for FL, 0.60 for PH, 0.53 for YLD, and 0.65 for ZN. The gain of multi-environment over single-environment models ranged from 71% for YLD to 430% for FL. The selection of the best-performing families based on multi-trait indices, including the four traits mentioned above, facilitated the identification of suitable families for recombination. This information will be used to develop a new cycle of recurrent selection through genomic selection.
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spelling CGSpace1689392025-12-08T10:06:44Z Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice Bartholomé, Jerome Ospina, José Omar Sandoval, Mario Espinosa, Natalia Arcos, Jairo Ospina, Yolima Frouin, Julien Beartschi, Cédric Ghneim, Thaura Grenier, Cecile genomics rice toxicity Over half of the world’s arable land is acidic, which constrains cereal production. In South America, different rice-growing regions (Cerrado in Brazil and Llanos in Colombia and Venezuela) are particularly affected due to high aluminum toxicity levels. For this reason, efforts have been made to breed for tolerance to aluminum toxicity using synthetic populations. The breeding program of CIAT-CIRAD is a good example of the use of recurrent selection to increase productivity for the Llanos in Colombia. In this study, we evaluated the performance of genomic prediction models to optimize the breeding scheme by hastening the development of an improved synthetic population and elite lines. We characterized 334 families at the S 0:4 generation in two conditions. One condition was the control, managed with liming, while the other had high aluminum toxicity. Four traits were considered: days to flowering (FL), plant height (PH), grain yield (YLD), and zinc concentration in the polished grain (ZN). The population presented a high tolerance to aluminum toxicity, with more than 72% of the families showing a higher yield under aluminum conditions. The performance of the families under the aluminum toxicity condition was predicted using four different models: a single-environment model and three multi-environment models. The multi-environment models differed in the way they integrated genotype-by-environment interactions. The best predictive abilities were achieved using multi-environment models: 0.67 for FL, 0.60 for PH, 0.53 for YLD, and 0.65 for ZN. The gain of multi-environment over single-environment models ranged from 71% for YLD to 430% for FL. The selection of the best-performing families based on multi-trait indices, including the four traits mentioned above, facilitated the identification of suitable families for recombination. This information will be used to develop a new cycle of recurrent selection through genomic selection. 2024-08-22 2025-01-13T23:55:57Z 2025-01-13T23:55:57Z Journal Article https://hdl.handle.net/10568/168939 en Open Access application/pdf Bartholomé, J.; Ospina, J.O.; Sandoval, M.; Espinosa, N.; Arcos, J.; Ospina, Y.; Frouin, J.; Beartschi, C.; Ghneim, T.; Grenier, C. (2024) Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice. PLoS ONE 19(8): e0307009. ISSN: 1932-6203
spellingShingle genomics
rice
toxicity
Bartholomé, Jerome
Ospina, José Omar
Sandoval, Mario
Espinosa, Natalia
Arcos, Jairo
Ospina, Yolima
Frouin, Julien
Beartschi, Cédric
Ghneim, Thaura
Grenier, Cecile
Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice
title Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice
title_full Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice
title_fullStr Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice
title_full_unstemmed Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice
title_short Genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice
title_sort genomic selection for tolerance to aluminum toxicity in a synthetic population of upland rice
topic genomics
rice
toxicity
url https://hdl.handle.net/10568/168939
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