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Background: Soybean mosaic virus (SMV) is a globally prevalent and detrimental virus that belongs to the Potyvirus genus. Pathogenic viruses of this genus are typically linear in shape, with dimensions ranging between 630 and 750 nm, and are composed of single-stranded RNA and proteins. We have developed an SMV-resistant soybean line, Dongnong 93-046, which has no significant changes in disease resistance identification in the adult plants and has neat grains with no obvious brown or black markings. To explore the defense mechanisms of soybean against SMV, we performed comparative transcriptomic sequencing of the leaves between the Dongnong 93-046 inoculated with SMV at 8 h (T) and the non-inoculated control (C) on the HiSeq2000 platform. In addition, we performed non-targeted metabolomic sequencing of leaves from the treatment and control groups. Results: We identified a total of 41,189 differentially expressed genes (DEGs). A total of 9809 differentially expressed genes (DEGs) met the criteria of |Log2FC (Fold Change)| ≥ 1 and adjusted p-value ≤ 0.001. Among the 41,189 DEGs identified, 9196 exhibited FPKM values greater than 10. KEGG pathway enrichment analysis of the 9809 DEGs revealed significant enrichment of genes involved in resistance-related pathways such as plant–pathogen interaction, linoleic acid metabolism, mitogen-activated protein kinase (MAPK) signaling pathway, and plant hormone signaling transduction. Functional analysis using MapMan software identified multiple DEGs that were associated with pathways such as jasmonate synthesis and phenylpropanoid biosynthesis. Weighted gene co-expression network analysis (WGCNA) using the differential metabolites and the 9196 DEGs revealed a strong correlation between gene clusters within the Turquoise module and the content of jasmonate-related metabolites. Further functional enrichment analysis of the 894 genes within the gene clusters showed a significant and repeated enrichment of pathways related to plant–pathogen interaction, linoleic acid metabolism, and plant hormone signaling transduction. Subsequent focused pathway analysis identified key genes involved in plant hormone signaling transduction pathways, such as the jasmonate ZIM domain protein Glyma.16G010000, the gene Glyma.01G235600 encoding the essential diterpene reductase required for jasmonate synthesis in the jasmonate biosynthesis pathway, and the transcription factor Glyma.02G232600 involved in the plant–pathogen interaction pathway, among others. This study provides a theoretical framework for understanding the resistance mechanism of soybean cultivar Dongnong 93-046 against the SMV N1 strain, offers potential gene resources for breeding soybean varieties with resistance to SMV, and paves the way for new strategies to control SMV infection, enhance resistance, and improve crop yield and quality.

Soybean (Glycine max (L.) Merr.) is an important crop for both food and feed, playing a significant role in agricultural production and the human diet. During long-term storage, soybean seeds often exhibit reduced quality, decreased germination, and lower seedling vigor, ultimately leading to significant yield reductions in soybean crops. Seed storage tolerance is a complex quantitative trait controlled by multiple genes and is also influenced by environmental factors during seed formation, harvest, and storage. This study aimed to evaluate soybean germplasms for their storage tolerance, identify quantitative trait nucleotides (QTNs) associated with seed storage tolerance traits, and screen for candidate genes. The storage tolerance of 168 soybean germplasms was evaluated, and 23,156 high-quality single nucleotide polymorphism (SNP) markers were screened and analyzed through a genome-wide association study (GWAS). Ultimately, 14 QTNs were identified as being associated with seed storage tolerance and were distributed across the eight chromosomes of soybean, with five QTNs (rs25887810, rs27941858, rs33981296, rs44713950, and rs18610980) being newly reported loci in this study. In the linkage disequilibrium regions of these SNPs, 256 genes were identified. By combining GWAS and weighted gene co-expression network analysis (WGCNA), eight hub genes (Glyma.03G058300, Glyma.04G1921100, Glyma.04G192600, Glyma.04G192900, Glyma.07G002000, Glyma.08G329400, Glyma.16G074600, Glyma.16G091400) were jointly identified. Through the analysis of expression patterns, two candidate genes (Glyma.03G058300, Glyma.16G074600) potentially involved in seed storage tolerance were ultimately identified. Additionally, haplotype analysis revealed that natural variations in Glyma.03G058300 could affect seed storage tolerance. The findings of this research provide a theoretical foundation for understanding the regulatory mechanism underlying soybean storage.

The utilization of saline land is a global challenge, and cultivating salt-tolerant soybean varieties is beneficial for improving the efficiency of saline land utilization. Exploring the genetic basis of salt-tolerant soybean varieties and developing salt-tolerant molecular markers can effectively promote the process of soybean salt-tolerant breeding. In the study, the membership function method was used to evaluate seven traits related to salt tolerance and comprehensive salt tolerance at the soybean seedling stage; genome-wide association analysis (GWAS) was performed in a natural population containing 200 soybean materials; and linkage analysis was performed in 112 recombinant inbred lines (RIL) population to detect quantitative trait loci (QTLs) of salt tolerance. In the GWAS, 147 SNPs were mapped, explaining 5.28–17.16% of phenotypic variation. In the linkage analysis, 10 QTLs were identified, which could explain 6.9–16.16% of phenotypic variation. And it was found that there were two co-located regions between the natural population and the RIL population, containing seven candidate genes of salt tolerance in soybean. In addition, one colocalization interval was found to contain qZJS-15-1, rs47665107, and rs4793412, all of which could explain more than 10% of phenotypic variation rates, making it suitable for molecular marker development. The physical positions of rs47665107 and rs47934112 were included in qZJS-15-1. Therefore, a KASP marker was designed and developed using Chr. 15:47907445, which was closely linked to the qZJS-15-1. This marker could accurately and clearly cluster the materials of salt-tolerant genotypes in the heterozygous population tested. The QTLs and KASP markers found in the study provide a theoretical and technical basis for accelerating the salt-tolerant breeding of soybean.

Soybean vegetable oil is an important source of the human diet. However, the analysis of the genetic mechanism leading to changes in soybean oil content is still incomplete. In this study, a total of 227 soybean materials were applied and analyzed by a genome-wide association study (GWAS). There are 44 quantitative trait nucleotides (QTNs) that were identified as associated with oil content. A total of six, four, and 34 significant QTN loci were identified in Xiangyang, Hulan, and Acheng, respectively. Of those, 26 QTNs overlapped with or were near the known oil content quantitative trait locus (QTL), and 18 new QTNs related to oil content were identified. A total of 594 genes were located near the peak single nucleotide polymorphism (SNP) from three tested environments. These candidate genes exhibited significant enrichment in tropane, piperidine, and pyridine alkaloid biosynthesiss (ko00960), ABC transporters (ko02010), photosynthesis-antenna proteins (ko00196), and betalain biosynthesis (ko00965). Combined with the GWAS and weighted gene co-expression network analysis (WGCNA), four candidate genes (Glyma.18G300100, Glyma.11G221100, Glyma.13G343300, and Glyma.02G166100) that may regulate oil content were identified. In addition, Glyma.18G300100 was divided into two main haplotypes in the studied accessions. The oil content of haplotype 1 is significantly lower than that of haplotype 2. Our research findings provide a theoretical basis for improving the regulatory mechanism of soybean oil content.

Protein content (PC) is crucial to the nutritional quality of soybean [Glycine max (L.) Merrill]. In this study, a total of 266 accessions were used to perform a genome-wide association study (GWAS) in three tested environments. A total of 23,131 high-quality SNP markers (MAF ≥ 0.02, missing data ≤ 10%) were identified. A total of 40 association signals were significantly associated with PC. Among them, five novel quantitative trait nucleotides (QTNs) were discovered, and another 32 QTNs were found to be overlapping with the genomic regions of known quantitative trait loci (QTL) related to soybean PC. Combined with GWAS, metabolome and transcriptome sequencing, 59 differentially expressed genes (DEGs) that might control the change in protein content were identified. Meantime, four commonly upregulated differentially abundant metabolites (DAMs) and 29 commonly downregulated DAMs were found. Remarkably, the soybean gene Glyma.08G136900, which is homologous with Arabidopsis hydroxyproline-rich glycoproteins (HRGPs), may play an important role in improving the PC. Additionally, Glyma.08G136900 was divided into two main haplotype in the tested accessions. The PC of haplotype 1 was significantly lower than that of haplotype 2. The results of this study provided insights into the genetic mechanisms regulating protein content in soybean.