Identification of major genomic regions for soybean seed weight by genome-wide association study

被引:0
作者
Yongce Cao
Shihao Jia
Liuxing Chen
Shunan Zeng
Tuanjie Zhao
Benjamin Karikari
机构
[1] Yan’an University,Shaanxi Key Laboratory of Chinese Jujube, College of Life Science
[2] Soybean Research Institute of Nanjing Agricultural University,Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, National Center for Soybean Improvement, National Key Laboratory for Crop Genetics and Germplasm Enhancemen
[3] University for Development Studies,Department of Crop Science, Faculty of Agriculture, Food and Consumer Sciences
来源
Molecular Breeding | 2022年 / 42卷
关键词
Hundred-seed weight; Association analysis; SNPs; LD block regions; Stable loci; Candidate genes;
D O I
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中图分类号
学科分类号
摘要
The hundred-seed weight (HSW) is an important yield component and one of the principal breeding traits in soybean. More than 250 quantitative trait loci (QTL) for soybean HSW have been identified. However, most of them have a large genomic region or are environmentally sensitive, which provide limited information for improving the phenotype in marker-assisted selection (MAS) and identifying the candidate genes. Here, we utilized 281 soybean accessions with 58,112 single nucleotide polymorphisms (SNPs) to dissect the genetic basis of HSW in across years in the northern Shaanxi province of China through one single-locus (SL) and three multi-locus (ML) genome-wide association study (GWAS) models. As a result, one hundred and fifty-four SNPs were detected to be significantly associated with HSW in at least one environment via SL-GWAS model, and 27 of these 154 SNPs were detected in all (three) environments and located within 7 linkage disequilibrium (LD) block regions with the distance of each block ranged from 40 to 610 Kb. A total of 15 quantitative trait nucleotides (QTNs) were identified by three ML-GWAS models. Combined with the results of different GWAS models, the 7 LD block regions associated with HSW detected by SL-GWAS model could be verified directly or indirectly by the results of ML-GWAS models. Eleven candidate genes underlying the stable loci that may regulate seed weight in soybean were predicted. The significantly associated SNPs and the stable loci as well as predicted candidate genes may be of great importance for marker-assisted breeding, polymerization breeding, and gene discovery for HSW in soybean.
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