Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean Varieties

Soybean, a globally important crop, is a typical short-day and thermophilic plant. Continuous efforts are necessary to elucidate the genetic basis of its essential traits. In this study, we assembled a collection of 203 soybean varieties, all of which are well suited for cultivation in the northeast...

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Main Authors: Qianli Dong, Yuting Cheng, Yiyang Li, Yan Tong, Dazhuang Liu, Jiaxin Yu, Na Zhao, Bao Liu, Xiaoyang Ding, Chunming Xu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Agronomy
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Online Access:https://www.mdpi.com/2073-4395/15/5/1181
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author Qianli Dong
Yuting Cheng
Yiyang Li
Yan Tong
Dazhuang Liu
Jiaxin Yu
Na Zhao
Bao Liu
Xiaoyang Ding
Chunming Xu
author_facet Qianli Dong
Yuting Cheng
Yiyang Li
Yan Tong
Dazhuang Liu
Jiaxin Yu
Na Zhao
Bao Liu
Xiaoyang Ding
Chunming Xu
author_sort Qianli Dong
collection DOAJ
description Soybean, a globally important crop, is a typical short-day and thermophilic plant. Continuous efforts are necessary to elucidate the genetic basis of its essential traits. In this study, we assembled a collection of 203 soybean varieties, all of which are well suited for cultivation in the northeastern region of China. We assessed 15 agronomic traits under three distinct environments, noting substantial phenotypic variations in the panel and stable correlations among traits. The population structure analysis, based on genotyping-by-sequencing (GBS) data, revealed seven subpopulations within the panel and significant gene flows among these subpopulations. Through genome-wide association studies (GWASs), we identified 64 significantly associated loci (SALs) for 15 traits and unveiled the genetic interconnections between yield and related traits. Additionally, we highlighted a few candidate genes within SALs for yield and related traits. Finally, we evaluated the genomic prediction performances of four distinct methods across the three environments, revealing the significant influence of environmental factors on predictive accuracies. We found that rrBLUP is suitable for most traits, though specific traits may benefit from more complex machine learning models. Our findings establish a foundation for the future research of genetic mechanisms of soybean agronomic traits and the application of genomic selection in soybean breeding.
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spelling doaj-art-a64cc1180a334864812da0d4ec0fb0df2025-08-20T01:57:04ZengMDPI AGAgronomy2073-43952025-05-01155118110.3390/agronomy15051181Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean VarietiesQianli Dong0Yuting Cheng1Yiyang Li2Yan Tong3Dazhuang Liu4Jiaxin Yu5Na Zhao6Bao Liu7Xiaoyang Ding8Chunming Xu9Key Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, ChinaKey Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, ChinaKey Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, ChinaKey Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, ChinaKey Laboratory of Hybrid Soybean Breeding of Ministry of Agriculture and Rural Affairs, Soybean Research Institute, Jilin Academy of Agricultural Sciences, Changchun 130033, ChinaKey Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, ChinaDepartment of Agronomy, Jilin Agricultural University, Changchun 130118, ChinaKey Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, ChinaKey Laboratory of Hybrid Soybean Breeding of Ministry of Agriculture and Rural Affairs, Soybean Research Institute, Jilin Academy of Agricultural Sciences, Changchun 130033, ChinaKey Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, ChinaSoybean, a globally important crop, is a typical short-day and thermophilic plant. Continuous efforts are necessary to elucidate the genetic basis of its essential traits. In this study, we assembled a collection of 203 soybean varieties, all of which are well suited for cultivation in the northeastern region of China. We assessed 15 agronomic traits under three distinct environments, noting substantial phenotypic variations in the panel and stable correlations among traits. The population structure analysis, based on genotyping-by-sequencing (GBS) data, revealed seven subpopulations within the panel and significant gene flows among these subpopulations. Through genome-wide association studies (GWASs), we identified 64 significantly associated loci (SALs) for 15 traits and unveiled the genetic interconnections between yield and related traits. Additionally, we highlighted a few candidate genes within SALs for yield and related traits. Finally, we evaluated the genomic prediction performances of four distinct methods across the three environments, revealing the significant influence of environmental factors on predictive accuracies. We found that rrBLUP is suitable for most traits, though specific traits may benefit from more complex machine learning models. Our findings establish a foundation for the future research of genetic mechanisms of soybean agronomic traits and the application of genomic selection in soybean breeding.https://www.mdpi.com/2073-4395/15/5/1181soybeanGWASgenomic selectionyield
spellingShingle Qianli Dong
Yuting Cheng
Yiyang Li
Yan Tong
Dazhuang Liu
Jiaxin Yu
Na Zhao
Bao Liu
Xiaoyang Ding
Chunming Xu
Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean Varieties
Agronomy
soybean
GWAS
genomic selection
yield
title Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean Varieties
title_full Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean Varieties
title_fullStr Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean Varieties
title_full_unstemmed Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean Varieties
title_short Genome-Wide Association Study and Genomic Prediction of Essential Agronomic Traits in Diversity Panel of Soybean Varieties
title_sort genome wide association study and genomic prediction of essential agronomic traits in diversity panel of soybean varieties
topic soybean
GWAS
genomic selection
yield
url https://www.mdpi.com/2073-4395/15/5/1181
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