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Genome-wide association study and genomic prediction analyses of drought stress tolerance in China in a collection of off-PVP maize inbred lines

文献类型： 外文期刊

作者： Wang, Nan 1 ; Liu, Bojuan 1 ; Liang, Xiaoling 3 ; Zhou, Yueheng 1 ; Song, Jie 1 ; Yang, Jie 3 ; Yong, Hongjun 1 ; Weng, J 1 ;

作者机构： 1.Chinese Acad Agr Sci, Inst Crop Sci, Beijing, Peoples R China

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

3.Xinjiang Acad Agr Sci, Inst Food Crops, Urumqi, Peoples R China

4.Int Maize & Wheat Improvement Ctr CIMMYT, Patancheru, Greater Hyderab, India

关键词： Maize; Off-PVP inbred lines; Drought tolerance; GWAS; Genomic prediction

期刊名称：MOLECULAR BREEDING （ 影响因子：2.589； 五年影响因子：2.75 ）

ISSN： 1380-3743

年卷期： 2019 年 39 卷 8 期

页码：

收录情况： SCI

摘要： Phenotypic evaluation of the drought-tolerant traits and identification of the genetic markers associated with these traits in diverse germplasms are essential for developing drought-tolerant germplasm through molecular breeding. A collection of 210 off-PVP (no longer subject to Plant Variety Protection) maize inbred lines introduced from the USA (ALs) were genotyped using a low-coverage sequencing method and phenotyped in eight environments (location x year x treatment) in China. The CV of phenotypic data for six target traits varied from 5.34 to 20.69% under well-watered (WW) conditions and from 5.46 to 35.98% under drought-stressed (WS) conditions. ALs exhibited higher grain yield per plot (GY) under the WS conditions and premature characteristic compared with the local checks, which are important breeding targets in drought tolerance. Two subgroups, SS and NSS, were identified in this collection based on population structure analysis, PCA, and an NJ tree. A total of 413 trait-associated SNPs under the WW conditions and 696 SNPs under the WS conditions were detected in a GWAS (genome-wide association study) analysis, with the phenotypic variation explained by each SNP to the target traits varied from 10.02 to 25.40%. In the genomic prediction (GP) analysis, the prediction models incorporating trait-marker associations showed higher prediction accuracies than the prediction models using an equivalent number of randomly selected SNPs for all the six traits evaluated under both the WW and WS conditions. The results observed in this study provide valuable information for understanding the genetic variation of drought stress tolerance in maize, and show great potential to improve drought stress tolerance in maize via genomic selection.

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