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.

The Northwest soybean production region (covering Shanxi, Shaanxi, Gansu, Ningxia, Xinjiang, central and western Inner Mongolia and northern parts of Hebei) possesses vast cultivated land resources and advantageous light–temperature conditions, endowing soybean with substantial yield potential. In this study, two natural soybean populations originating from this region were used to systematically investigate the phenotypic variation in two important agronomic traits, plant height (PH) and main stem node number (NN). The results showed abundant genetic variation for both traits. Through genome-wide association analysis (GWAS) and employing a joint detection across multi-environments (control false positives), 5 SNPs significantly associated with PH and 18 SNPs significantly associated with NN were identified, among which four SNPs were detected associated with both traits. Candidate genes were further screened within the ±100 kb intervals flanking lead SNPs at association peaks. By integrating gene expression levels of different soybean tissues and their correlations with the phenotypes, two candidate genes associated with both PH and NN were determined. These findings provide a theoretical basis for the identification and utilization of soybean germplasm resources in Northwest China, and lay a solid foundation for breeding high-yield and high-quality soybean varieties through molecular breeding.