Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits
Genomic selection methods are particularly useful for traits that are difcult or expensive to measure. We investigated the impact of using predictor growth traits and/or genomic information to increase the breeding value (BV) predictive accuracies for target scarcely recorded wood quality traits in...
| Main Authors: | , , , , , |
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| Format: | Artículo |
| Language: | Inglés |
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Springer
2023
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| Online Access: | http://hdl.handle.net/20.500.12123/15254 https://link.springer.com/article/10.1007/s11295-023-01611-z https://doi.org/10.1007/s11295-023-01611-z |
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| author | Jurcic, Esteban Javier Villalba, Pamela Victoria Dutour, Joaquín Centurión, Carmelo Munilla, Sebastián Cappa, Eduardo Pablo |
| author_browse | Cappa, Eduardo Pablo Centurión, Carmelo Dutour, Joaquín Jurcic, Esteban Javier Munilla, Sebastián Villalba, Pamela Victoria |
| author_facet | Jurcic, Esteban Javier Villalba, Pamela Victoria Dutour, Joaquín Centurión, Carmelo Munilla, Sebastián Cappa, Eduardo Pablo |
| author_sort | Jurcic, Esteban Javier |
| collection | INTA Digital |
| description | Genomic selection methods are particularly useful for traits that are difcult or expensive to measure. We investigated the impact of using predictor growth traits and/or genomic information to increase the breeding value (BV) predictive accuracies for target scarcely recorded wood quality traits in an open-pollinated Eucalyptus grandis population. The performance of single- and multiple-trait single-step genomic best linear unbiased prediction and conventional pedigree-based models were compared in terms of the predictive accuracies (PA) of estimated BV for the target traits. We also derived the contributions of the BV for candidate trees to better understand our results. The inclusion of predictor traits in both, the training and the validation sets, together with genomic information, improved the PA (up to 17.7%) for pulp yield and cellulose. However, signifcant improvements in PA were not observed when predictor traits were recorded only in the training set or when the impact of genomic information alone was assessed. Changes in the PA were explained by the variations in the maternal contributions, contribution/s from all the predictor/s trait/s, and from genotyped trees. We conclude that there is not a “uni versal” rule regarding the use of genomic information and records on predictor traits. However, assessing the contributions to the BV of validation trees may help to better design how to beneft from predictor traits in forest tree breeding. |
| format | Artículo |
| id | INTA15254 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | INTA152542023-09-19T18:40:00Z Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits Jurcic, Esteban Javier Villalba, Pamela Victoria Dutour, Joaquín Centurión, Carmelo Munilla, Sebastián Cappa, Eduardo Pablo Calidad de la Madera Fitomejoramiento Wood Quality Plant Breeding Eucalyptus Multiple-trait Individual Tree Model Step GBLUP Scarcely Recorded Traits Individuo de Rasgos Múltiples Modelo de Arbol Paso GBLUP Rasgos Apenas Registrados Genomic selection methods are particularly useful for traits that are difcult or expensive to measure. We investigated the impact of using predictor growth traits and/or genomic information to increase the breeding value (BV) predictive accuracies for target scarcely recorded wood quality traits in an open-pollinated Eucalyptus grandis population. The performance of single- and multiple-trait single-step genomic best linear unbiased prediction and conventional pedigree-based models were compared in terms of the predictive accuracies (PA) of estimated BV for the target traits. We also derived the contributions of the BV for candidate trees to better understand our results. The inclusion of predictor traits in both, the training and the validation sets, together with genomic information, improved the PA (up to 17.7%) for pulp yield and cellulose. However, signifcant improvements in PA were not observed when predictor traits were recorded only in the training set or when the impact of genomic information alone was assessed. Changes in the PA were explained by the variations in the maternal contributions, contribution/s from all the predictor/s trait/s, and from genotyped trees. We conclude that there is not a “uni versal” rule regarding the use of genomic information and records on predictor traits. However, assessing the contributions to the BV of validation trees may help to better design how to beneft from predictor traits in forest tree breeding. Fil: Jurcic, Esteban J. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Villalba, Pamela Victoria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Dutour, Joaquín. Forestal Oriental, UPM, Paysandú, Uruguay Fil: Centurión, Carmelo. Forestal Oriental, UPM, Paysandú, Uruguay Fil: Munilla, Sebastián. Universidad de Buenos Aires, Facultad de Agronomía, Departamento de Producción Animal, Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina 2023-09-19T18:23:33Z 2023-09-19T18:23:33Z 2023-07-18 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/15254 https://link.springer.com/article/10.1007/s11295-023-01611-z 1614-2950 https://doi.org/10.1007/s11295-023-01611-z eng info:eu-repograntAgreement/INTA/2019-PE-E6-I146-001, Mejoramiento genético de especies forestales cultivadas de rápido crecimiento: un desarrollo clave para el fortalecimiento de la foresto industria nacional. info:eu-repo/semantics/restrictedAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Springer Tree Geneties & Genomes 19 (4) : Article number: 35 (July 2023) |
| spellingShingle | Calidad de la Madera Fitomejoramiento Wood Quality Plant Breeding Eucalyptus Multiple-trait Individual Tree Model Step GBLUP Scarcely Recorded Traits Individuo de Rasgos Múltiples Modelo de Arbol Paso GBLUP Rasgos Apenas Registrados Jurcic, Esteban Javier Villalba, Pamela Victoria Dutour, Joaquín Centurión, Carmelo Munilla, Sebastián Cappa, Eduardo Pablo Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits |
| title | Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits |
| title_full | Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits |
| title_fullStr | Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits |
| title_full_unstemmed | Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits |
| title_short | Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits |
| title_sort | breeding value predictive accuracy for scarcely recorded traits in a eucalyptus grandis breeding population using genomic selection and data on predictor traits |
| topic | Calidad de la Madera Fitomejoramiento Wood Quality Plant Breeding Eucalyptus Multiple-trait Individual Tree Model Step GBLUP Scarcely Recorded Traits Individuo de Rasgos Múltiples Modelo de Arbol Paso GBLUP Rasgos Apenas Registrados |
| url | http://hdl.handle.net/20.500.12123/15254 https://link.springer.com/article/10.1007/s11295-023-01611-z https://doi.org/10.1007/s11295-023-01611-z |
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