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

Abstract

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.

Combined analysis of the metabolome and transcriptome provides insight into seed oil accumulation in soybean

“…To ensure a global supply of soybean products, the development of high-yield and high-oil cultivars has become the primary breeding target in soybean breeding programs [ 2 ]. Soybean is rich in various primary and secondary metabolites, such as flavonoids, lipids, and sugar metabolites [ 3 , 4 ]. Lipid metabolites play an important role in seed metabolism and are the main carrier for the production of soybean oil [ 5 ].…”

Genome-Wide Detection of Quantitative Trait Loci and Prediction of Candidate Genes for Seed Sugar Composition in Early Mature Soybean

“…Because raffinose and stachyose are derived from sucrose, possibly these two SNPs point to the same QTL. The SNP Gm15_49568824 associated with both sucrose and total sugar content was 293 Kb away from the SNP rs49892059 (Gm15_49892059), which was the peak marker of a QTL for soluble sugar content in a previous study [ 28 ].…”

“…Of these genes, one had been reported previously to be associated with sucrose content, while the other nine were considered as novel genes for sucrose content. Lu et al [ 28 ] reported a GWAS on total soluble sugar content in soybean using 278 diverse soybean accessions. They detected 84 SNPs from seventeen genes across four chromosomes to be associated with the total soluble sugar content.…”

GWAS and genomic selection for marker-assisted development of sucrose enriched soybean cultivars

“…To date, 42 QTLs have been reported for soybean seed sucrose contents through linkage analysis of bi-parental mapping populations (https://www.soybase.org/search/qtllist_by_symbol.php, accessed on February 13, 2023). However, only a few studies involving GWAS have been reported in recent years (Sui et al 2020;Ficht et al 2022;Xu et al 2022;Lu et al 2022). This study also followed GWAS approach to pinpoint important genomic regions signi cantly associated with seed sucrose contents.…”