Soluble sugar is a major indicator of the intrinsic quality of vegetable soybean [Glycine max (L.) Merr. ]. The improvement of soluble sugar content in soybean is very important due to its healthcare functions for humans. The genetic mechanism of soluble sugar in soybean is unclear. In this study, 278 diverse soybean accessions were utilized to identify the quantitative trait nucleotides (QTNs) for total soluble sugar content in soybean seeds based on a genome-wide association study (GWAS). A total of 25,921 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected for GWAS. Totally, thirteen QTNs associated with total soluble sugar content were identified, which were distributed on ten chromosomes. One hundred and fifteen genes near the 200-kb flanking region of these identified QTNs were considered candidate genes associated with total soluble sugar content in soybean seed. Gene-based association analysis and haplotype analysis were utilized to further identify the effect of candidate genes on total soluble sugar content. Totally, 84 SNPs from seventeen genes across four chromosomes were significantly associated with the total soluble sugar content. Among them, three SNPs from Glyma.02G292900 were identified at two locations, and other eighty-one SNPs from sixteen genes were detected at three locations. Furthermore, expression level analysis of candidate genes revealed that Glyma.02G293200 and Glyma.02G294900 were significantly positively associated with soluble sugar content and Glyma.02G294000 was significantly negatively associated with soluble sugar content. Six genes (i.e., Glyma.02G292600, Glyma.02G292700, Glyma.02G294000, Glyma.02G294300, Glyma.02G294400, and Glyma.15G264200) identified by GWAS were also detected by the analysis of differential expression genes based on soybean germplasms with higher and lower soluble sugar content. Among them, Glyma.02G294000 is the only gene that was identified by gene-based association analysis with total soluble sugar content and was considered an important candidate gene for soluble sugar content. These candidate genes and beneficial alleles would be useful for improving the soluble sugar content of soybean.

The sucrose concentration in soybean seed significantly affects the flavor of soybean-derived products. In this study, an association panel of 178 elite accessions and 33,149 single-nucleotide polymorphisms (SNPs) was utilized to identify quantitative trait nucleotides (QTNs) of sucrose concentration in soybean seeds by genome-wide association study (GWAS). Five QTNs (rs2688589, rs29026218, rs5926884, rs6886889, and rs10299216) distributed across five genomic regions in five chromosomes were identified in two or more locations by GWAS. A total of 60 candidate genes near the 200-kb flanking region of these five identified loci were identified. Three of these genes (Glyma.04G032600, Glyma.04G034600, and Glyma.11G092100) have been reported to be involved in the process of sugar biosynthesis. Based on gene-based association and haplotype analyses, a total of 35 SNPs from 10 genes associated with sucrose concentration were identified. Of them, Glyma.04G032600 was the only gene that has been reported to be related to sucrose content; the other nine genes were novel and may be associated with sucrose content. These beneficial alleles and candidate genes may be of great value in improving sucrose content in soybean seeds.

Tocopherol (Toc) occurs in soybean seeds and is extracted together with the soybean oil. Toc is utilized as an antioxidant in food and an additive in animal feed. A total of 180 representative accessions and 144 recombinant inbred lines (RILs) from the cross of ‘Hefeng 25’ and ‘OAC Bayfield’ were selected to evaluate individuals and total Toc concentrations in soybean seeds. The 180 soybean samples were sequenced by the approach of Specific Locus Amplified Fragment Sequencing (SLAF-seq). A total of 22,611 single nucleotide polymorphisms (SNPs) were developed. Nineteen quantitative trait nucleotides (QTNs) were identified associated with individual or total-Toc based on genome-wide association analysis (GWAS). Among them, three QTNs located near known QTLs, and 16 were novel. Eighteen QTLs and nine eQTLs were also detected by linkage mapping. The QTN rs9337368 on Chr.02 was colocalized according to the linkage mapping of the RILs and genome-wide association analysis and regarded as a stable locus for mining the candidate genes in association with Toc. A total of 42 candidate genes near the 200 kbp flanking region of this identified locus were found. Upon a gene-based association, 11 SNPs from five genes out of the 42 candidates were detected. Expression level analysis of five candidate genes revealed that two genes were significantly related to Toc content. The identified loci, along with the candidate genes, might be valuable for increasing the Toc concentration in soybean seeds and improving the nutritional value of soybean oil.

Seed shape (SS) affects the yield and appearance of soybean seeds significantly. However, little detailed information has been reported about the quantitative trait loci (QTL) affecting SS, especially SS components such as seed length (SL), seed width (SW) and seed thickness (ST), and their mutual ratios of length-to-weight (SLW), length-to-thickness (SLT) and weight-to-thickness (SWT). The aim of the present study was to identify QTL underlying SS components using 129 recombinant inbred lines derived from a cross between Dongnong46 and L-100. Phenotypic data were collected from this population after it was grown across nine environments. A total of 213 simple sequence repeat markers were used to construct the genetic linkage map, which covered approximately 3623·39 cM, with an average distance of 17·01 cM between markers. Five QTL were identified as being associated with SL, five with SW, three with ST, four with SLW, two with SLT and three with SWT. These QTL could explain 1·46–22·16% of the phenotypic variation in SS component traits. Three QTL were identified in more than six tested environments three for SL, two for SW, one for ST, two for SLW and one for SLT. These QTL have great potential value for marker-assistant selection of SS in soybean seeds.

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