Genomic Prediction: Progress and Perspectives for Rice Improvement
Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding strategy. In rice as in other crops, the interest in genomic prediction is very strong with a number of studies addressing multiple aspects of its use,...
| Autores principales: | , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/128168 |
| _version_ | 1855535001740771328 |
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| author | Bartholomé, Jérôme Thathapalli Prakash, Parthiban Cobb, Joshua N. |
| author_browse | Bartholomé, Jérôme Cobb, Joshua N. Thathapalli Prakash, Parthiban |
| author_facet | Bartholomé, Jérôme Thathapalli Prakash, Parthiban Cobb, Joshua N. |
| author_sort | Bartholomé, Jérôme |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding strategy. In rice as in other crops, the interest in genomic prediction is very strong with a number of studies addressing multiple aspects of its use, ranging from the more conceptual to the more practical. In this chapter, we review the literature on rice (<jats:italic>Oryza sativa</jats:italic>) and summarize important considerations for the integration of genomic prediction in breeding programs. The irrigated breeding program at the International Rice Research Institute is used as a concrete example on which we provide data and R scripts to reproduce the analysis but also to highlight practical challenges regarding the use of predictions. The adage “<jats:italic>To someone with a hammer, everything looks like a nail</jats:italic>” describes a common psychological pitfall that sometimes plagues the integration and application of new technologies to a discipline. We have designed this chapter to help rice breeders avoid that pitfall and appreciate the benefits and limitations of applying genomic prediction, as it is not always the best approach nor the first step to increasing the rate of genetic gain in every context. |
| format | Book Chapter |
| id | CGSpace128168 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1281682025-01-27T15:00:52Z Genomic Prediction: Progress and Perspectives for Rice Improvement Bartholomé, Jérôme Thathapalli Prakash, Parthiban Cobb, Joshua N. genomics oryza sativa rice breeding programmes Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding strategy. In rice as in other crops, the interest in genomic prediction is very strong with a number of studies addressing multiple aspects of its use, ranging from the more conceptual to the more practical. In this chapter, we review the literature on rice (<jats:italic>Oryza sativa</jats:italic>) and summarize important considerations for the integration of genomic prediction in breeding programs. The irrigated breeding program at the International Rice Research Institute is used as a concrete example on which we provide data and R scripts to reproduce the analysis but also to highlight practical challenges regarding the use of predictions. The adage “<jats:italic>To someone with a hammer, everything looks like a nail</jats:italic>” describes a common psychological pitfall that sometimes plagues the integration and application of new technologies to a discipline. We have designed this chapter to help rice breeders avoid that pitfall and appreciate the benefits and limitations of applying genomic prediction, as it is not always the best approach nor the first step to increasing the rate of genetic gain in every context. 2022 2023-01-25T08:27:02Z 2023-01-25T08:27:02Z Book Chapter https://hdl.handle.net/10568/128168 en Open Access application/pdf Springer Bartholomé, J., Prakash, P.T. and Cobb, J.N. 2022. Genomic Prediction: Progress and Perspectives for Rice Improvement. IN: Ahmadi, N., Bartholomé, J. (eds) Genomic Prediction of Complex Traits. Methods in Molecular Biology 2467:569–617. Humana, New York, NY. |
| spellingShingle | genomics oryza sativa rice breeding programmes Bartholomé, Jérôme Thathapalli Prakash, Parthiban Cobb, Joshua N. Genomic Prediction: Progress and Perspectives for Rice Improvement |
| title | Genomic Prediction: Progress and Perspectives for Rice Improvement |
| title_full | Genomic Prediction: Progress and Perspectives for Rice Improvement |
| title_fullStr | Genomic Prediction: Progress and Perspectives for Rice Improvement |
| title_full_unstemmed | Genomic Prediction: Progress and Perspectives for Rice Improvement |
| title_short | Genomic Prediction: Progress and Perspectives for Rice Improvement |
| title_sort | genomic prediction progress and perspectives for rice improvement |
| topic | genomics oryza sativa rice breeding programmes |
| url | https://hdl.handle.net/10568/128168 |
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