Genomic prediction from multi-environment trials of wheat breeding
Genomic prediction relates a set of markers to variability in observed phenotypes of cultivars and allows for the prediction of phenotypes or breeding values of genotypes on unobserved individuals. Most genomic prediction approaches predict breeding values based solely on additive effects. However,...
| Autores principales: | , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
MDPI
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/162527 |
| _version_ | 1855542174680088576 |
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| author | Garcia Barrios, Guillermo Crespo Herrera, Leonardo A. Cruz-Izquierdo, Serafín Vitale, Paolo Sandoval-Islas, José Sergio Gerard, Guillermo Sebastián Aguilar Rincón, Víctor Heber Corona-Torres, Tarsicio Crossa, José Pacheco Gil, Rosa Angela |
| author_browse | Aguilar Rincón, Víctor Heber Corona-Torres, Tarsicio Crespo Herrera, Leonardo A. Crossa, José Cruz-Izquierdo, Serafín Garcia Barrios, Guillermo Gerard, Guillermo Sebastián Pacheco Gil, Rosa Angela Sandoval-Islas, José Sergio Vitale, Paolo |
| author_facet | Garcia Barrios, Guillermo Crespo Herrera, Leonardo A. Cruz-Izquierdo, Serafín Vitale, Paolo Sandoval-Islas, José Sergio Gerard, Guillermo Sebastián Aguilar Rincón, Víctor Heber Corona-Torres, Tarsicio Crossa, José Pacheco Gil, Rosa Angela |
| author_sort | Garcia Barrios, Guillermo |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Genomic prediction relates a set of markers to variability in observed phenotypes of cultivars and allows for the prediction of phenotypes or breeding values of genotypes on unobserved individuals. Most genomic prediction approaches predict breeding values based solely on additive effects. However, the economic value of wheat lines is not only influenced by their additive component but also encompasses a non-additive part (e.g., additive x additive epistasis interaction). In this study, genomic prediction models were implemented in three target populations of environments (TPE) in South Asia. Four models that incorporate genotype x environment interaction (G x E) and genotype x genotype (GG) were tested: Factor Analytic (FA), FA with genomic relationship matrix (FA + G), FA with epistatic relationship matrix (FA + GG), and FA with both genomic and epistatic relationship matrices (FA + G + GG). Results show that the FA + G and FA + G + GG models displayed the best and a similar performance across all tests, leading us to infer that the FA + G model effectively captures certain epistatic effects. The wheat lines tested in sites in different TPE were predicted with different precisions depending on the cross-validation employed. In general, the best prediction accuracy was obtained when some lines were observed in some sites of particular TPEs and the worse genomic prediction was observed when wheat lines were never observed in any site of one TPE. |
| format | Journal Article |
| id | CGSpace162527 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace1625272025-12-08T10:29:22Z Genomic prediction from multi-environment trials of wheat breeding Garcia Barrios, Guillermo Crespo Herrera, Leonardo A. Cruz-Izquierdo, Serafín Vitale, Paolo Sandoval-Islas, José Sergio Gerard, Guillermo Sebastián Aguilar Rincón, Víctor Heber Corona-Torres, Tarsicio Crossa, José Pacheco Gil, Rosa Angela soft wheat marker-assisted selection factor analysis gene interaction Genomic prediction relates a set of markers to variability in observed phenotypes of cultivars and allows for the prediction of phenotypes or breeding values of genotypes on unobserved individuals. Most genomic prediction approaches predict breeding values based solely on additive effects. However, the economic value of wheat lines is not only influenced by their additive component but also encompasses a non-additive part (e.g., additive x additive epistasis interaction). In this study, genomic prediction models were implemented in three target populations of environments (TPE) in South Asia. Four models that incorporate genotype x environment interaction (G x E) and genotype x genotype (GG) were tested: Factor Analytic (FA), FA with genomic relationship matrix (FA + G), FA with epistatic relationship matrix (FA + GG), and FA with both genomic and epistatic relationship matrices (FA + G + GG). Results show that the FA + G and FA + G + GG models displayed the best and a similar performance across all tests, leading us to infer that the FA + G model effectively captures certain epistatic effects. The wheat lines tested in sites in different TPE were predicted with different precisions depending on the cross-validation employed. In general, the best prediction accuracy was obtained when some lines were observed in some sites of particular TPEs and the worse genomic prediction was observed when wheat lines were never observed in any site of one TPE. 2024 2024-11-21T15:29:04Z 2024-11-21T15:29:04Z Journal Article https://hdl.handle.net/10568/162527 en Open Access application/pdf MDPI García-Barrios, G., Crespo-Herrera, L. A., Cruz-Izquierdo, S., Vitale, P., Sandoval-Islas, J. S., Gerard, G. S., Aguilar-Rincón, V. H., Corona-Torres, T., Crossa, J., & Pacheco-Gil, R. A. (2024). Genomic prediction from multi-environment trials of wheat breeding. Genes, 15(4), 417. https://doi.org/10.3390/genes15040417 |
| spellingShingle | soft wheat marker-assisted selection factor analysis gene interaction Garcia Barrios, Guillermo Crespo Herrera, Leonardo A. Cruz-Izquierdo, Serafín Vitale, Paolo Sandoval-Islas, José Sergio Gerard, Guillermo Sebastián Aguilar Rincón, Víctor Heber Corona-Torres, Tarsicio Crossa, José Pacheco Gil, Rosa Angela Genomic prediction from multi-environment trials of wheat breeding |
| title | Genomic prediction from multi-environment trials of wheat breeding |
| title_full | Genomic prediction from multi-environment trials of wheat breeding |
| title_fullStr | Genomic prediction from multi-environment trials of wheat breeding |
| title_full_unstemmed | Genomic prediction from multi-environment trials of wheat breeding |
| title_short | Genomic prediction from multi-environment trials of wheat breeding |
| title_sort | genomic prediction from multi environment trials of wheat breeding |
| topic | soft wheat marker-assisted selection factor analysis gene interaction |
| url | https://hdl.handle.net/10568/162527 |
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