Introduction: Rhizosphere microorganisms can effectively promote the stress resistance of plants, and some beneficial rhizosphere microorganisms can significantly promote the growth of crops under salt stress, which has the potential to develop special microbial fertilizers for increasing the yield of saline-alkali land and provides a low-cost and environmentally friendly new strategy for improving the crop yield of saline-alkali cultivated land by using agricultural microbial technology.Methods: In May 2022, a field study in a completely randomized block design was conducted at the Heilongjiang Academy of Agricultural Sciences to explore the correlation between plant rhizosphere microorganisms and soybean growth in saline-alkali soil. Two soybean cultivars (Hening 531, a salt-tolerant variety, and 20_1846, a salt-sensitive variety) were planted at two experimental sites [Daqing (normal condition) and Harbin (saline-alkali conditions)], aiming to investigate the performance of soybean in saline-alkali environments.Results: Soybeans grown in saline-alkali soil showed substantial reductions in key traits: plant height (25%), pod number (26.6%), seed yield (33%), and 100 seed weight (13%). This underscores the unsuitability of this soil type for soybean cultivation. Additionally, microbial analysis revealed 43 depleted and 56 enriched operational taxonomic units (OTUs) in the saline-alkali soil compared to normal soil. Furthermore, an analysis of ion-associated microbes identified 85 mOTUs with significant correlations with various ions. A co-occurrence network analysis revealed strong relationships between specific mOTUs and ions, such as Proteobacteria with multiple ions. In addition, the study investigated the differences in rhizosphere species between salt-tolerant and salt-sensitive soybean varieties under saline-alkali soil conditions. Redundancy analysis (RDA) indicated that mOTUs in saline-alkali soil were associated with pH and ions, while mOTUs in normal soil were correlated with Ca²⁺ and K⁺. Comparative analyses identified significant differences in mOTUs between salt-tolerant and salt-sensitive varieties under both saline-alkali and normal soil conditions. Planctomycetes, Proteobacteria, and Actinobacteria were dominant in the bacterial community of saline-alkali soil, with significant enrichment compared to normal soil. The study explored the functioning of the soybean rhizosphere key microbiome by comparing metagenomic data to four databases related to the carbon, nitrogen, phosphorus, and sulfur cycles. A total of 141 KOs (KEGG orthologues) were identified, with 66 KOs related to the carbon cycle, 16 KOs related to the nitrogen cycle, 48 KOs associated with the phosphorus cycle, and 11 KOs linked to the sulfur cycle. Significant correlations were found between specific mOTUs, functional genes, and phenotypic traits, including per mu yield (PMY), grain weight, and effective pod number per plant.Conclusion: Overall, this study provides comprehensive insights into the structure, function, and salt-related species of soil microorganisms in saline-alkali soil and their associations with salt tolerance and soybean phenotype. The identification of key microbial species and functional categories offers valuable information for understanding the mechanisms underlying plant-microbe interactions in challenging soil conditions.

Background: Microbial communities associated with roots play a crucial role in the growth and health of plants and are constantly influenced by plant development and alterations in the soil environment. Despite extensive rhizosphere microbiome research, studies examining multi-kingdom microbial variation across large-scale agricultural gradients remain limited. Results: This study investigates the rhizosphere microbial communities associated with soybean across 13 diverse geographical locations in China. Using high-throughput shotgun metagenomic sequencing on the BGISEQ T7 platform with 10 GB per sample, we identified a total of 43,337 microbial species encompassing bacteria, archaea, fungi, and viruses. Our analysis revealed significant site-specific variations in microbial diversity and community composition, underscoring the influence of local environmental factors on microbial ecology. Principal coordinate analysis (PCoA) indicated distinct clustering patterns of microbial communities, reflecting the unique environmental conditions and agricultural practices of each location. Network analysis identified 556 hub microbial taxa significantly correlated with soybean yield traits, with bacteria showing the strongest associations. These key microorganisms were found to be involved in critical nutrient cycling pathways, particularly in carbon oxidation, nitrogen fixation, phosphorus solubilization, and sulfur metabolism. Our findings demonstrate the pivotal roles of specific microbial taxa in enhancing nutrient cycling, promoting plant health, and improving soybean yield, with significant positive correlations (r = 0.5, p = 0.039) between microbial diversity and seed yield. Conclusion: This study provides a comprehensive understanding of the diversity and functional potential of rhizosphere microbiota in enhancing soybean productivity. The findings underscore the importance of integrating microbial community dynamics into crop management strategies to optimize nutrient cycling, plant health, and yield. While this study identifies key microbial taxa with potential functional roles, future research should focus on isolating and validating these microorganisms for their bioremediation and biofertilization activities under field conditions. This will provide actionable insights for developing microbial-based agricultural interventions to improve crop resilience and sustainability.

Low temperatures greatly restrict the development, growth, and productivity of soybeans, with their effects differing across various cultivars. The present work investigated the transcriptome and physiological reactions of two soybean cultivars, namely “KD52” exhibiting cold tolerance and “DS17” displaying cold sensitivity, to cold stress across a precisely defined period. The soybean plants were subjected to cold treatment at 6 °C for durations of 0, 2, 4, and 8 h. A comparative physiological marker study revealed distinct reactions to cold stress in the two cultivars. The findings showed that increased malondialdehyde levels provided evidence of DS17’s heightened vulnerability to lipid peroxidation and membrane degradation. In contrast, the KD52 cultivar exhibited increased activities of antioxidant enzymes, including peroxidase and superoxide dismutase, in response to cold exposure, suggesting a strong antioxidant defense system against oxidative stress. The transcriptomic analysis revealed dynamic responses, mapping 54,532 genes. Within this group, a total of 234 differentially expressed genes (DEGs) were found to be consistently changed at several time intervals, showing unique expression patterns across the two cultivars. Analysis of the association between these important DEGs and the physiological indicators revealed candidate genes that may be involved in controlling oxidative damage and antioxidant defenses. Some key genes showed a progressive rise in expression over time in both cultivars, with a more significant acceleration in KD52, and are probably involved in promoting adaptation processes during extended periods of cold exposure. The identification of improved defense mechanisms in KD52, together with the identification of crucial genes, offers great prospects for enhancing the cold stress resilience of soybean.

Optimizing soybean yield remains a crucial challenge in meeting global food security demands. In this study, we report a comprehensive genetic analysis of yield-related traits in soybeans using a recombinant inbred line (RIL) population derived from crosses between ‘Qihuang 34’ (GH34) and ‘Dongsheng 16′ (DS16). Phenotypic analysis across two years (2023–2024) revealed significant variations between parental lines. Through high-density genetic mapping with 6297 SLAF markers spanning 2945.26 cM across 20 chromosomes, we constructed a genetic map with an average marker distance of 0.47 cM and 99.17% of gaps under 5 cM. QTL analysis identified ten significant loci across both years: in 2023, we detected six QTLs, including a major main stem node number (MSNN) QTL on chromosome 19 (LOD = 22.59, PVE = 24.57%), two seed number (SN) QTLs on chromosomes 14 and 18 (LOD = 2.52–2.85, PVE = 7.35% combined), and one pod number (PN) QTL on chromosome 20 (LOD = 4.68, PVE = 5.85%). The 2024 analysis revealed four major QTLs, notably a cluster on chromosome 19 harboring significant loci for MSNN (LOD = 37.92, PVE = 43.59%), PN (LOD = 18.16, PVE = 23.02%), and SN (LOD = 15.24, PVE = 19.59%). Within the stable chromosome 19 region, we identified seventeen candidate genes involved in crucial developmental processes. Gene expression analysis revealed distinct temporal patterns between parental lines during vegetative and reproductive stages, with GH34 showing dramatically higher expression of key reproductive genes Glyma.19G201300 and Glyma.19G201400 during the R1 stage. Our findings provide new insights into the genetic architecture of soybean stem node development and yield components, offering multiple promising targets for molecular breeding programs aimed at crop improvement.

Soybean is an important food crop that contains high amounts of isoflavones. However, due to the expression of multiple genes, different soybean seeds have different isoflavone compositions. The underlying mechanisms for this complexity remain unknown. In this study, we identified potential differentially expressed genes (DEGs) in two wild soybean cultivars, ZYD7068 (high isoflavone) and ZYD7194 (low isoflavone), at different seed developmental stages using RNA-seq technology and compared their differences in isoflavone content. A total of 1067 and 6479 differentially metabolized genes were identified at R6 and R8 stages, respectively. Subsequent analysis of the KEGG pathway revealed that three of these differential metabolized genes were involved in the Isoflavonoid biosynthesis and Flavone and flavonol biosynthesis at the R6 stage. A total of 80 TF genes encoding differential expression of MYB, bZIP, and WRKY were identified in A1 vs. B1 and A3 vs. B3. Eight differentially expressed genes were identified in duplicates at both stages, and three genes showed the same expression trend at both stages. To confirm the results of RNA-seq, qRT-PCR was performed to analyze the expression of the six identified differentially expressed genes (DEGs). The results of qRT-PCR were consistent with the results of RNA-seq. We found that four genes (Glyma.13G173300, Glyma.13G173600, Glyma.14G103100, and Glyma.17G158900) may be involved in the positive regulation of isoflavone synthesis, while two genes (Glyma.04G036700 and Glyma.19G030500) may be involved in the negative regulation of isoflavone synthesis. These findings suggest that the observed difference in isoflavone levels between the two cultivars may be attributable to the differential expression of these six genes at later stages of seed development.

Vegetative soybean (maodou or edamame) serves as a nutrient-rich food source with significant potential for mitigating global nutritional deficiencies. This study undertook a thorough examination of the nutritional profiles and transcriptomic landscapes of six soybean cultivars, including three common cultivars (Heinong551, Heinong562, and Heinong63) and three fresh maodou cultivars (Heinong527, HeinongXS4, and HeinongXS5). Nutrient analysis of the seeds disclosed notable differences in the levels of protein, fat, soluble sugars, vitamin E, calcium, potassium, magnesium, manganese, iron, and zinc across the cultivars. Through comparative transcriptome profiling and RNA sequencing, distinct variations in differentially expressed genes (DEGs) were identified between fresh and traditional maodou cultivars. Functional enrichment analyses underscored the involvement of DEGs in critical biological processes, such as nutrient biosynthesis, seed development, and stress responses. Additionally, association studies demonstrated robust correlations between specific DEG expression patterns and seed nutrient compositions across the different cultivars. Sankey diagrams illustrated that DEGs are strongly linked with seed quality traits, revealing potential molecular determinants that govern variations in nutritional content. The identified DEGs and their relationships with nutritional profiles offer valuable insights for breeding programs focused on developing cultivars with improved nutritional quality, tailored to specific dietary needs or industrial applications.