Genetic variation and marker-trait association affect the genomic selection prediction accuracy of soybean protein and oil content

被引：0

作者：

Sun, Bo ^{[1
,2
]}

Guo, Rui ^{[1
]}

Liu, Zhi ^{[1
]}

Shi, Xiaolei ^{[1
]}

Yang, Qing ^{[1
]}

Shi, Jiayao ^{[1
]}

Zhang, Mengchen ^{[1
]}

Yang, Chunyan ^{[1
]}

Zhao, Shugang ^{[2
]}

Zhang, Jie ^{[2
]}

He, Jianhan ^{[1
]}

Zhang, Jiaoping ^{[3
,4
]}

Su, Jianhui ^{[5
]}

Song, Qijian ^{[6
]}

Yan, Long ^{[1
]}

机构：

[1] Hebei Acad Agr & Forestry Sci, Inst Cereal & Oil Crops, Key Lab Crop Genet & Breeding, Shijiazhuang Branch Ctr,Natl Ctr Soybean Improveme, Shijiazhuang, Peoples R China

[2] Hebei Agr Univ, Coll Life Sci, Baoding, Peoples R China

[3] Natl Ctr Soybean Improvement, State Key Lab Crop Genet & Germplasm Enhancement, Nanjing, Peoples R China

[4] Nanjing Agr Univ, Key Lab Biol & Genet Improvement Soybean, Gen, Minist Agr, Nanjing, Peoples R China

[5] Agr Regionalizat Workstn Shijiazhuangs Gaocheng Di, Shijiazhuang, Peoples R China

[6] ARS, Soybean Genom & Improvement Lab, USDA, Beltsville, MD 20705 USA

来源：

FRONTIERS IN PLANT SCIENCE | 2022年 / 13卷

基金：

中国国家自然科学基金;

关键词：

soybean; protein content; oil content; GS; prediction accuracy; ASSISTED SELECTION; RIDGE-REGRESSION; QTL; GERMPLASM; SOFTWARE; YIELD;

D O I：

10.3389/fpls.2022.1064623

中图分类号：

Q94 [植物学];

学科分类号：

071001 ;

摘要：

IntroductionGenomic selection (GS) is a potential breeding approach for soybean improvement. MethodsIn this study, GS was performed on soybean protein and oil content using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) based on 1,007 soybean accessions. The SoySNP50K SNP dataset of the accessions was obtained from the USDA-ARS, Beltsville, MD lab, and the protein and oil content of the accessions were obtained from GRIN. ResultsOur results showed that the prediction accuracy of oil content was higher than that of protein content. When the training population size was 100, the prediction accuracies for protein content and oil content were 0.60 and 0.79, respectively. The prediction accuracy increased with the size of the training population. Training populations with similar phenotype or with close genetic relationships to the prediction population exhibited better prediction accuracy. A greatest prediction accuracy for both protein and oil content was observed when approximately 3,000 markers with -log(10)(P) greater than 1 were included. DiscussionThis information will help improve GS efficiency and facilitate the application of GS.

引用

页数：10

共 22 条

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PLOS ONE, 2022, 17 (10):
[22] Dissecting the Genetic Architecture of Seed Protein and Oil Content in Soybean from the Yangtze and Huaihe River Valleys Using Multi-Locus Genome-Wide Association Studies
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INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2019, 20 (12):

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