Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize
The two most important activities in maize breeding are the development of inbred lines with high values of general combining ability (GCA) and specific combining ability (SCA), and the identification of hybrids with high yield potentials. Genomic selection (GS) is a promising genomic tool to perfor...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Elsevier
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/126428 |
| _version_ | 1855515592341061632 |
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| author | Ao Zhang Pérez Rodriguez, Paulino San Vicente, Felix M. Palacios Rojas, Natalia Dhliwayo, Thanda Yubo Liu Zhenhai Cui Yuan Guan Hui Wang Hongjian Zheng Olsen, Michael Boddupalli, P.M. Yanye Ruan Crossa, José Xuecai Zhang |
| author_browse | Ao Zhang Boddupalli, P.M. Crossa, José Dhliwayo, Thanda Hongjian Zheng Hui Wang Olsen, Michael Palacios Rojas, Natalia Pérez Rodriguez, Paulino San Vicente, Felix M. Xuecai Zhang Yanye Ruan Yuan Guan Yubo Liu Zhenhai Cui |
| author_facet | Ao Zhang Pérez Rodriguez, Paulino San Vicente, Felix M. Palacios Rojas, Natalia Dhliwayo, Thanda Yubo Liu Zhenhai Cui Yuan Guan Hui Wang Hongjian Zheng Olsen, Michael Boddupalli, P.M. Yanye Ruan Crossa, José Xuecai Zhang |
| author_sort | Ao Zhang |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The two most important activities in maize breeding are the development of inbred lines with high values of general combining ability (GCA) and specific combining ability (SCA), and the identification of hybrids with high yield potentials. Genomic selection (GS) is a promising genomic tool to perform selection on the untested breeding material based on the genomic estimated breeding values estimated from the genomic prediction (GP). In this study, GP analyses were carried out to estimate the performance of hybrids, GCA, and SCA for grain yield (GY) in three maize line-by-tester trials, where all the material was phenotyped in 10 to 11 multiple-location trials and genotyped with a mid-density molecular marker platform. Results showed that the prediction abilities for the performance of hybrids ranged from 0.59 to 0.81 across all trials in the model including the additive effect of lines and testers. In the model including both additive and non-additive effects, the prediction abilities for the performance of hybrids were improved and ranged from 0.64 to 0.86 across all trials. The prediction abilities of the GCA for GY were low, ranging between − 0.14 and 0.13 across all trials in the model including only inbred lines; the prediction abilities of the GCA for GY were improved and ranged from 0.49 to 0.55 across all trials in the model including both inbred lines and testers, while the prediction abilities of the SCA for GY were negative across all trials. The prediction abilities for GY between testers varied from − 0.66 to 0.82; the performance of hybrids between testers is difficult to predict. GS offers the opportunity to predict the performance of new hybrids and the GCA of new inbred lines based on the molecular marker information, the total breeding cost could be reduced dramatically by phenotyping fewer multiple-location trials. |
| format | Journal Article |
| id | CGSpace126428 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1264282025-11-06T13:03:07Z Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize Ao Zhang Pérez Rodriguez, Paulino San Vicente, Felix M. Palacios Rojas, Natalia Dhliwayo, Thanda Yubo Liu Zhenhai Cui Yuan Guan Hui Wang Hongjian Zheng Olsen, Michael Boddupalli, P.M. Yanye Ruan Crossa, José Xuecai Zhang maize marker-assisted selection combining ability The two most important activities in maize breeding are the development of inbred lines with high values of general combining ability (GCA) and specific combining ability (SCA), and the identification of hybrids with high yield potentials. Genomic selection (GS) is a promising genomic tool to perform selection on the untested breeding material based on the genomic estimated breeding values estimated from the genomic prediction (GP). In this study, GP analyses were carried out to estimate the performance of hybrids, GCA, and SCA for grain yield (GY) in three maize line-by-tester trials, where all the material was phenotyped in 10 to 11 multiple-location trials and genotyped with a mid-density molecular marker platform. Results showed that the prediction abilities for the performance of hybrids ranged from 0.59 to 0.81 across all trials in the model including the additive effect of lines and testers. In the model including both additive and non-additive effects, the prediction abilities for the performance of hybrids were improved and ranged from 0.64 to 0.86 across all trials. The prediction abilities of the GCA for GY were low, ranging between − 0.14 and 0.13 across all trials in the model including only inbred lines; the prediction abilities of the GCA for GY were improved and ranged from 0.49 to 0.55 across all trials in the model including both inbred lines and testers, while the prediction abilities of the SCA for GY were negative across all trials. The prediction abilities for GY between testers varied from − 0.66 to 0.82; the performance of hybrids between testers is difficult to predict. GS offers the opportunity to predict the performance of new hybrids and the GCA of new inbred lines based on the molecular marker information, the total breeding cost could be reduced dramatically by phenotyping fewer multiple-location trials. 2022-02 2023-01-01T16:03:43Z 2023-01-01T16:03:43Z Journal Article https://hdl.handle.net/10568/126428 en Open Access application/pdf Elsevier Zhang, A., Pérez-Rodríguez, P., San Vicente, F., Palacios-Rojas, N., Dhliwayo, T., Liu, Y., Cui, Z., Guan, Y., Wang, H., Zheng, H., Olsen, M., Prasanna, B. M., Ruan, Y., Crossa, J., & Zhang, X. (2022). Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize. The Crop Journal, 10(1), 109–116. https://doi.org/10.1016/j.cj.2021.04.007 |
| spellingShingle | maize marker-assisted selection combining ability Ao Zhang Pérez Rodriguez, Paulino San Vicente, Felix M. Palacios Rojas, Natalia Dhliwayo, Thanda Yubo Liu Zhenhai Cui Yuan Guan Hui Wang Hongjian Zheng Olsen, Michael Boddupalli, P.M. Yanye Ruan Crossa, José Xuecai Zhang Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize |
| title | Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize |
| title_full | Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize |
| title_fullStr | Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize |
| title_full_unstemmed | Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize |
| title_short | Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize |
| title_sort | genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize |
| topic | maize marker-assisted selection combining ability |
| url | https://hdl.handle.net/10568/126428 |
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