Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress
In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption o...
| Autores principales: | , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
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Frontiers Media
2020
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/110330 |
| _version_ | 1855527296457244672 |
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| author | Keller, Beat Ariza-Suárez, Daniel Hoz, Juan Fernando de la Aparicio, Johan Steven Portilla, Benavides Ana Elisabeth Buendia, Hector Fabio Mayor, Victor Manuel Studer, Bruno Raatz, Bodo |
| author_browse | Aparicio, Johan Steven Ariza-Suárez, Daniel Buendia, Hector Fabio Hoz, Juan Fernando de la Keller, Beat Mayor, Victor Manuel Portilla, Benavides Ana Elisabeth Raatz, Bodo Studer, Bruno |
| author_facet | Keller, Beat Ariza-Suárez, Daniel Hoz, Juan Fernando de la Aparicio, Johan Steven Portilla, Benavides Ana Elisabeth Buendia, Hector Fabio Mayor, Victor Manuel Studer, Bruno Raatz, Bodo |
| author_sort | Keller, Beat |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50–80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions. |
| format | Journal Article |
| id | CGSpace110330 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Frontiers Media |
| publisherStr | Frontiers Media |
| record_format | dspace |
| spelling | CGSpace1103302025-11-12T05:55:53Z Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress Keller, Beat Ariza-Suárez, Daniel Hoz, Juan Fernando de la Aparicio, Johan Steven Portilla, Benavides Ana Elisabeth Buendia, Hector Fabio Mayor, Victor Manuel Studer, Bruno Raatz, Bodo agrobiodiversity marker-assisted selection plant breeding drought phosphorus beans agrobiodiversidad selección asistida por marcadores mejoramiento de plantas In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50–80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions. 2020-11 2020-11-26T16:00:09Z 2020-11-26T16:00:09Z Journal Article https://hdl.handle.net/10568/110330 en Open Access application/pdf Frontiers Media Keller, B.; Ariza Suarez, D.; de la Hoz, J.; Aparicio, J.S.; Portilla, B.A.E.; Buendia, H.F.; Mayor, V.M.; Studer, B.; Raatz, B. (2020) Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress. Frontiers in Plant Science 11:1001 15 p. ISSN: 1664-462X |
| spellingShingle | agrobiodiversity marker-assisted selection plant breeding drought phosphorus beans agrobiodiversidad selección asistida por marcadores mejoramiento de plantas Keller, Beat Ariza-Suárez, Daniel Hoz, Juan Fernando de la Aparicio, Johan Steven Portilla, Benavides Ana Elisabeth Buendia, Hector Fabio Mayor, Victor Manuel Studer, Bruno Raatz, Bodo Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress |
| title | Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress |
| title_full | Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress |
| title_fullStr | Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress |
| title_full_unstemmed | Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress |
| title_short | Genomic prediction of agronomic traits in common bean (Phaseolus vulgaris L.) under environmental stress |
| title_sort | genomic prediction of agronomic traits in common bean phaseolus vulgaris l under environmental stress |
| topic | agrobiodiversity marker-assisted selection plant breeding drought phosphorus beans agrobiodiversidad selección asistida por marcadores mejoramiento de plantas |
| url | https://hdl.handle.net/10568/110330 |
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