Genome-Wide Identification of Candidate Genes Underlying Soluble Sugar Content in Vegetable Soybean (Glycine max L.) via Association and Expression Analysis.

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.

Genome-wide association studies reveal novel QTLs, QTL-by-environment interactions and their candidate genes for tocopherol content in soybean seed.

Genome-wide association studies (GWAS) is an efficient method to detect quantitative trait locus (QTL), and has dissected many complex traits in soybean [Glycine max (L.) Merr.]. Although these results have undoubtedly played a far-reaching role in the study of soybean biology, environmental interactions for complex traits in traditional GWAS models are frequently overlooked. Recently, a new GWAS model, 3VmrMLM, was established to identify QTLs and QTL-by-environment interactions (QEIs) for complex traits. In this study, the GLM, MLM, CMLM, FarmCPU, BLINK, and 3VmrMLM models were used to identify QTLs and QEIs for tocopherol (Toc) content in soybean seed, including δ-Tocotrienol (δ-Toc) content, γ-Tocotrienol (γ-Toc) content, α-Tocopherol (α-Toc) content, and total Tocopherol (T-Toc) content. As a result, 101 QTLs were detected by the above methods in single-environment analysis, and 57 QTLs and 13 QEIs were detected by 3VmrMLM in multi-environment analysis. Among these QTLs, some QTLs (Group I) were repeatedly detected three times or by at least two models, and some QTLs (Group II) were repeatedly detected only by 3VmrMLM. In the two Groups, 3VmrMLM was able to correctly detect all known QTLs in group I, while good results were achieved in Group II, for example, 8 novel QTLs were detected in Group II. In addition, comparative genomic analysis revealed that the proportion of Glyma_max specific genes near QEIs was higher, in other words, these QEIs nearby genes are more susceptible to environmental influences. Finally, around the 8 novel QTLs, 11 important candidate genes were identified using haplotype, and validated by RNA-Seq data and qRT-PCR analysis. In summary, we used phenotypic data of Toc content in soybean, and tested the accuracy and reliability of 3VmrMLM, and then revealed novel QTLs, QEIs and candidate genes for these traits. Hence, the 3VmrMLM model has broad prospects and potential for analyzing the genetic structure of complex quantitative traits in soybean.

Identification of Loci and Candidate Genes Analyses for Tocopherol Concentration of Soybean Seed.

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.

Genome-wide association analysis of sucrose concentration in soybean (Glycine max L.) seed based on high-throughput sequencing.

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.