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BMC Genet. 2019 Mar 29;20(1):39. doi: 10.1186/s12863-019-0737-9.

Genome-wide association study of four yield-related traits at the R6 stage in soybean.

Author information

1
National Center for Soybean Improvement/National Key laboratory of Crop Genetics and Germplasm enhancement, Key laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
2
The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Lab of Germplasm Utilization (MOA), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, People's Republic of China.
3
National Center for Soybean Improvement/National Key laboratory of Crop Genetics and Germplasm enhancement, Key laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China. jmz3000@126.com.
4
National Center for Soybean Improvement/National Key laboratory of Crop Genetics and Germplasm enhancement, Key laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China. hanx@njau.edu.cn.

Abstract

BACKGROUND:

The 100-pod fresh weight (PFW), 100-seed fresh weight (SFW), 100-seed dry weight (SDW) and moisture content of fresh seeds (MCFS) at the R6 stage are crucial factors for vegetable soybean yield. However, the genetic basis of yield at the R6 stage remains largely ambiguous in soybean.

RESULTS:

To better understand the molecular mechanism underlying yield, we investigated four yield-related traits of 133 soybean landraces in two consecutive years and conducted a genome-wide association study (GWAS) using 82,187 single nucleotide polymorphisms (SNPs). The GWAS results revealed a total of 14, 15, 63 and 48 SNPs for PFW, SFW, SDW and MCFS, respectively. Among these markers, 35 SNPs were repeatedly identified in all evaluated environments (2015, 2016, and the average across the two years), and most co-localized with yield-related QTLs identified in previous studies. AX-90496773 and AX-90460290 were large-effect markers for PFW and MCFS, respectively. The two markers were stably identified in all environments and tagged to linkage disequilibrium (LD) blocks. Six potential candidate genes were predicted in LD blocks; five of them showed significantly different expression levels between the extreme materials with large PFW or MCFS variation at the seed development stage. Therefore, the five genes Glyma.16g018200, Glyma.16g018300, Glyma.05g243400, Glyma.05g244100 and Glyma.05g245300 were regarded as candidate genes associated with PFW and MCFS.

CONCLUSION:

These results provide useful information for the development of functional markers and exploration of candidate genes in vegetable soybean high-yield breeding programs.

KEYWORDS:

GWAS; Quantitative trait locus; R6 stage; Single nucleotide polymorphism (SNP); Soybean [Glycine max (L.) Merr.]; Yield-related traits

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