Genomic prediction of yield performance among single-cross maize hybrids using a partial diallel cross design  

作　　者：Ping Luo Houwen Wang Zhiyong Ni Ruisi Yang Fei Wang Hongjun Yong Lin Zhang Zhiqiang Zhou Wei Song Mingshun Li Jie Yang Jianfeng Weng Zhaodong Meng Degui Zhang Jienan Han Yong Chen Runze Zhang Liwei Wang Meng Zhao Wenwei Gao Xiaoyu Chen Wenjie Li Zhuanfang Hao Junjie Fu Xuecai Zhang Xinhai Li 

机构地区：[1]State Key Laboratory of Crop Gene Resources and Breeding,Institute of Crop Sciences,Chinese Academy of Agricultural Sciences,Beijing 100081,China [2]International Maize and Wheat Improvement Center(CIMMYT),Texcoco 56237,Mexico [3]College of Agronomy,Xinjiang Agricultural University,Urumqi 830091,Xinjiang,China [4]College of Agronomy,Northeast Agricultural University,Harbin 150030,Heilongjiang,China [5]Institute of Cereal and Oil Crops,Hebei Academy of Agriculture and Forestry Sciences,Shijiazhuang 050035,Hebei,China [6]Food Crops Research Institute,Xinjiang Academy of Agricultural Science,Urumqi 830091,Xinjiang,China [7]Maize Research Institute of Shandong Academy of Agricultural Sciences,Jinan 250100,Shandong,China

出　　处：《The Crop Journal》2023年第6期1884-1892,共9页作物学报（英文版）

基　　金：the National Natural Science Foundation of China(32272049,32261143757);Sustainable Development International Cooperation Program from Bill&Melinda Gates Foundation(2022YFAG1002);the National Key Research and Development Program of China(2020YFE0202300);the Agricultural Science&Technology Innovation Program(CAASZDRW202109);the China Scholarship Council.

摘　　要：Genomic prediction(GP)in plant breeding has the potential to predict and identify the best-performing hybrids based on the genotypes of their parental lines.In a GP experiment,34 elite inbred lines were selected to make 285 single-cross hybrids in a partial-diallel cross design.These lines represented a mini-core collection of Chinese maize germplasm and comprised 18 inbred lines from the Stiff Stalk heterotic group and 16 inbred lines from the Non-Stiff Stalk heterotic group.The parents were genotyped by sequencing and the 285 hybrids were phenotyped for nine yield and yield-related traits at two locations in the summer sowing area(SUS)and three locations in the spring sowing area(SPS)in the main maizeproducing regions of China.Multiple GP models were employed to assess the accuracy of trait prediction in the hybrids.By ten-fold cross-validation,the prediction accuracies of yield performance of the hybrids estimated by the genomic best linear unbiased prediction(GBLUP)model in SUS and SPS were 0.51 and 0.46,respectively.The prediction accuracies of the remaining yield-related traits estimated with GBLUP ranged from 0.49 to 0.86 and from 0.53 to 0.89 in SUS and SPS,respectively.When additive,dominance,epistasis effects,genotype-by-environment interaction,and multi-trait effects were incorporated into the prediction model,the prediction accuracy of hybrid yield performance was improved.The ratio of training to testing population and size of training population optimal for yield prediction were determined.Multiple prediction models can improve prediction accuracy in hybrid breeding.

关 键 词：MAIZE Genomic prediction Prediction model Genetic effects Hybrid performance 

分 类 号：S513[农业科学—作物学]