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.

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.

Soybean plant architecture has a significant impact on yield potential, but the genetic underpinnings of key architectural traits remain elusive. The primary objective of this study was to explore the genetic foundations underlying main stem node number (MSN) in soybeans. Recombinant inbred lines (RILs) contained a 234 individual derived from crosses between two cultivars Zhonghuang35 (ZH35) and Jindou21 (JD21) was evaluated for seed hardness across 3 years (2013, 2014, and 2015 in Gansu). Markedly, the parent varieties, shown significant differences in MSN. Also, the RIL population exhibited a wide range of genetic variation in MSN. A high-density genetic map composed of 8,078 specific-locus amplified fragment (SLAF) markers, spanning 3,480.98 centimorgans (cM) with an average inter-marker distance of 0.59 cM were used to construct linkage map. Using ICIM analysis identified a total of 23 Quantitative Trait Loci (QTLs) across the 20 chromosome, of which five QTLs were detected in multiple years in Chr.6. Notably, we identified a stable major QTL, qMSN-6-4, explaining up to 24.81% of phenotypic variation. This QTL govern seven candidate genes with potential roles in regulating MSN development in soybean, including Glyma.06G027500 with a domain of unknown function, Glyma.06G027600 involved in proton transport, Glyma.06G027700 linked to proteolysis, Glyma.06G027900 related to transcriptional regulation, and Glyma.06G028000 and Glyma.06G028050 associated with membrane functions. The RT-PCR analysis confirmed that these genes were expressed differently between the parental lines this supports the idea that they may play a role in determining MSN. Glyma.06G027500 and Glyma.06G027600 showing higher expression in JD21 leaves and nodes, while Glyma.06G027700 and Glyma.06G028000 exhibited increased expression in ZH35 stems, highlighting their distinct roles in transcription regulation, membrane activities, and protein degradation that contribute to MSN formation in soybean. This study offers valuable insights into the genetic mechanisms governing soybean MSN, providing a foundation for future research and crop improvement efforts.

Seed oil and protein contents are critical agronomic traits that determine soybean quality. However, the key loci and corresponding genes controlling these quality traits remain to be elucidated. Here, we performed bulked segregant analysis by sequencing (BSA-seq) using an F4 population derived from a cross between the cultivars Heinong 35 (HN35) and Dengke 3 (DK3). A major soybean oil and protein quantitative trait locus (QTL) designated as q-OP18 was identified on chromosome 18, and the sugar transporter gene GmSWEET46 was further cloned. Haplotype analysis revealed that a single-nucleotide polymorphism (SNP) in the sixth exon of GmSWEET46 results in an amino acid change between HN35 and DK3 and is associated with seed oil and protein content, suggesting its important role in determining seed quality in soybean. GmSWEET46 is expressed during the early stages of seed and pod development and localizes to the plasma membrane, indicating its potential function as a sugar transporter. Further studies demonstrated that GmSWEET46 can regulate seed protein content, oil content, and seed size in Arabidopsis and soybean. Collectively, this study provides a novel locus and gene for regulating soybean seed traits and offers valuable resources for the breeding of high-quality and high-yielding soybean cultivars.