Public Description for 16S rRNA Gene Sequence Data

Study Title: Regulatory mechanism of phosphorus supply intensity on plant nitrogen acquisition in soybean: Insight from the differences of rhizobia diversity between high-oil soybean and non-high-oil soybean.Background: This study investigates how phosphorus (P) supply regulates symbiotic nitrogen acquisition in soybean, with a focus on the differential responses between high-oil and non-high-oil varieties. We hypothesized that varietal differences in rhizobial community assembly under varying P regimes underlie divergent nitrogen use efficiencies.Experimental Design: A pot experiment was conducted with two high-oil soybean varieties (Kenong 18 and Kenong 39) and two non-high-oil varieties (Heihe 43 and Longken 310). Plants were subjected to five levels of phosphorus fertilization (0, 35, 70, 105, and 140 kg P2O5 per hectare) in a completely randomized design with three replicates. At the V6 growth stage, root nodules were collected from plants under the 0 and 105 kg per hectare P treatments, representing the phenotypic extremes.Sample Information: The dataset comprises 16S rRNA gene amplicon sequences (targeting the rpoB gene) obtained from surface-sterilized soybean root nodules. Samples are labeled according to variety (KN18, KN39, HR43, LK310) and P treatment level (0 or 105 kg per hectare).Sequencing and Analysis: Microbial DNA was extracted from nodules, and the rpoB gene was amplified using specific primers (rpoB1479-F / rpoB1831-R). Amplicons were sequenced on the Illumina MiSeq platform (paired-end). Bioinformatics processing included quality filtering, OTU clustering, taxonomic assignment, and downstream ecological analyses (e.g., PCoA, RDA) to assess community structure and its relationship with environmental variables and host physiology.Data Usage: These data provide insight into how phosphorus availability and host genotype (high-oil vs. non-high-oil) jointly shape the nodule rhizobial community, which in turn influences symbiotic nitrogen fixation efficiency. The dataset is suitable for studies on plant-microbe interactions, nutrient management, microbial ecology, and soybean breeding.