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Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize

文献类型： 外文期刊

作者： Zhang, Ao 1 ; Perez-Rodriguez, Paulino 4 ; San Vicente, Felix 2 ; Palacios-Rojas, Natalia 2 ; Dhliwayo, Thanda 2 ; Liu, Yubo 3 ; Cui, Zhenhai 1 ; Guan, Yuan 3 ; Wang, Hui 3 ; Zheng, Hongjian 3 ; Olsen, Michael 6 ; Prasanna, Boddupalli M. 6 ; Ruan, Yanye 1 ; Crossa, Jose 2 ; Zhang, Xuecai 2 ;

作者机构： 1.Shenyang Agr Univ, Coll Biol Sci & Technol, Shenyang 110866, Liaoning, Peoples R China

2.Int Maize & Wheat Improvement Ctr CIMMYT, El Batan 56237, Texcoco, Mexico

3.Shanghai Acad Agr Sci, CIMMYT China Specialty Maize Res Ctr, Shanghai 200063, Peoples R China

4.Colegio Postgrad, Montecillo, Estado De Mexic, Mexico

5.Shanghai Acad Agr Sci, Crop Breeding & Cultivat Res Inst, Shanghai 200063, Peoples R China

6.Int Maize & Wheat Improvement Ctr CIMMYT, POB 1041, Nairobi 00621, Kenya

关键词： Maize; Genomic selection; Line-By-Tester; General combining ability; Specific combining ability

期刊名称：CROP JOURNAL （ 影响因子：4.647； 五年影响因子：5.781 ）

ISSN： 2095-5421

年卷期： 2022 年 10 卷 1 期

页码：

收录情况： SCI

摘要： 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. (C) 2021 Crop Science Society of China and Institute of Crop Science, CAAS. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd.

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