Soybean mosaic virus (SMV) is one of the main pathogens that can negatively affect soybean production and quality. To study the gene regulatory network of soybeans in response to SMV SC15, the resistant line X149 and susceptible line X97 were subjected to transcriptome analysis at 0, 2, 8, 12, 24, and 48 h post-inoculation (hpi). Differential expression analysis revealed that 10,190 differentially expressed genes (DEGs) responded to SC15 infection. Weighted gene co-expression network analysis (WGCNA) was performed to identify highly related resistance gene modules; in total, eight modules, including 2256 DEGs, were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of 2256 DEGs revealed that the genes significantly clustered into resistance-related pathways, such as the plant–pathogen interaction pathway, mitogen-activated protein kinases (MAPK) signaling pathway, and plant hormone signal transduction pathway. Among these pathways, we found that the flg22, Ca²⁺, hydrogen peroxide (H₂O₂), and abscisic acid (ABA) regulatory pathways were fully covered by 36 DEGs. Among the 36 DEGs, the gene Glyma.01G225100 (protein phosphatase 2C, PP2C) in the ABA regulatory pathway, the gene Glyma.16G031900 (WRKY transcription factor 22, WRKY22) in Ca²⁺ and H₂O₂ regulatory pathways, and the gene Glyma.04G175300 (calcium-dependent protein kinase, CDPK) in Ca²⁺ regulatory pathways were highly connected hub genes. These results indicate that the resistance of X149 to SC15 may depend on the positive regulation of flg22, Ca²⁺, H₂O₂, and ABA regulatory pathways. Our study further showed that superoxide dismutase (SOD) activity, H₂O₂ content, and catalase (CAT) and peroxidase (POD) activities were significantly up-regulated in the resistant line X149 compared with those in 0 hpi. This finding indicates that the H₂O₂ regulatory pathway might be dependent on flg22- and Ca²⁺-pathway-induced ROS generation. In addition, two hub genes, Glyma.07G190100 (encoding F-box protein) and Glyma.12G185400 (encoding calmodulin-like proteins, CMLs), were also identified and they could positively regulate X149 resistance. This study provides pathways for further investigation of SMV resistance mechanisms in soybean.

Nodulation is the most efficient nitrate assimilation system in the ecosystem, while excessive fertilization has an increased nitrate inhibition effect; deciphering the nitrate signal transduction mechanism in the process is of the utmost importance. In this study, genome-wide analyses of the GmCEP genes were applied to identify nodulation-related CEP genes; 22 GmCEP family members were identified, while GmCEP6 was mainly expressed in nodules and significantly responded to nitrate treatment and rhizobium infection, especially in later stages. Overexpression and CRISPR-Cas9 were used to validate its role in nodulation. We found that GmCEP6 overexpression significantly increased the nodule number, while GmCEP6 knock-out significantly decreased the nodule number, which suggests that GmCEP6 functions as a positive regulator in soybean nodulation. qRT-PCR showed that alterations in the expression of GmCEP6 affected the expression of marker genes in the Nod factor signaling pathway. Lastly, the function of GmCEP6 in nitrate inhibition of nodulation was analyzed; nodule numbers in the GmCEP6-overexpressed roots significantly increased under nitrogen treatments, which suggests that GmCEP6 functions in the resistance to nitrate inhibition. The study helps us understand that GmCEP6 promotes nodulation and participates in the regulation of nitrate inhibition of nodulation, which is of great significance for high efficiency utilization of nitrogen in soybeans.

Soluble sugars are essential components in the physiology and metabolism of soybeans (Glycine max), playing a critical role in regulating key processes such as development, germination, and flavor formation. The soluble sugar content in soybean seeds is primarily composed of stachyose, raffinose, sucrose, and glucose. This study aims to elucidate the genetic mechanisms underlying variation in the composition of soluble sugars in soybean seeds. A 128 recombinant inbred line (RIL) population was used, and concentrations of these four sugars were quantified across three years (2015, 2016, and 2017 in Shanxi). The analysis revealed that Jin Da 53 exhibited significantly higher sucrose and total sugar contents compared to Ping Nan, while stachyose levels were notably elevated in Ping Nan. Except for glucose content in 2017 and 2019, the RIL population’s traits all exhibited a normal distribution, making it suitable for QTL analyses. A total of twenty QTLs were identified for the four sugar components: five for glucose, four for raffinose, four for sucrose, three for stachyose, and four for total sugar, all with LOD > 2.5. Notably, three QTLs located on chromosome 10 (S10_37101443-S10_38298307, S10_38681635-S10_39134900, and S10_36697685-S10_36697916) were found to be associated with stachyose content, identifying one candidate gene, Glyma.10g154400, which was implicated in carbohydrate metabolic processes; a QTL located on chromosome 11 (96.881–105.5 cM) was identified in 2019 as a significant locus influencing sucrose content, identifying another candidate gene, Glyma.11g136200, which was linked to sugar/inositol transporter activity. Expression analysis of these candidate genes demonstrated the Glyma.10g154400 gene exhibited higher expression levels in varieties with lower stachyose content, whereas Glyma.11g136200 showed increased expression in lines with elevated sucrose levels. This study provides an important genetic basis for the breeding of soybean varieties with increased sugar content.