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Using genomic data to improve the estimation of general combining ability based on sparse partial diallel cross designs in maize
| Creador: | Xin Wang |
| Creador: | Zhenliang Zhang |
| Creador: | Yang Xu |
| Creador: | Pengchen Li |
| Creador: | Xuecai Zhang |
| Creador: | Chenwu Xu |
| Año: | 2020 |
| URI: | https://hdl.handle.net/10883/21016 |
| Lenguaje: | English |
| Editor: | Elsevier |
| Copyright: | CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose |
| Tipo: | Article |
| Lugar de publicación: | Netherlands |
| Páginas: | 819-829 |
| Número: | 5 |
| Volumen: | 8 |
| DOI: | 10.1016/j.cj.2020.04.012 |
| Descripción: | Evaluation of general combining ability (GCA) is crucial to hybrid breeding in maize. Although the complete diallel cross design can provide an efficient estimation, sparse partial diallel cross (SPDC) is more flexible in breeding practice. Using real and simulated data sets of partial diallel crosses between 266 maize inbred lines, this study investigated the performance of SPDC designs for estimating the GCA. With different distributions of parental lines involved in crossing (called random, balanced and unbalanced samplings), different numbers of hybrids were sampled as the training sets to estimate the GCA of the 266 inbred lines. In this process, three statistical approaches were applied. One obtained estimations through the ordinary least square (OLS) method, and the other two utilized genomic prediction (GP) to estimate the GCA. It was found that the coefficient of determination of each approach was always higher than the heritability of a target trait, showing that the GCA for maize inbred lines could be accurately predicted with SPDC designs. Both the GP approaches were more accurate than the OLS, particularly in the scenario for a low-heritability trait with a small sample size. Additionally, prediction results demonstrated that a big sample of hybrids could greatly help improve the accuracy. The random sampling of parental lines had little influence on the average accuracy. However, the prediction for lines that never or seldom involved in crossing might suffer from much lower accuracy. |
| Agrovoc: | COMBINING ABILITY |
| Agrovoc: | MAIZE |
| Agrovoc: | GENOMICS |
| Agrovoc: | DIALLEL ANALYSIS |
| ISSN: | 2214-5141 |
| Revista: | The Crop Journal |
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Maize
Maize breeding, phytopathology, entomology, physiology, quality, and biotech