Babalola Olubukola Oluranti, Enagbonma Ben Jesuorsemwen
Food Security and Safety Focus Area, Faculty of Natural and Agricultural Sciences, North-West University, Private Mail Bag X2046, Mmabatho 2735, South Africa.
Data Brief. 2025 Jan 14;58:111270. doi: 10.1016/j.dib.2025.111270. eCollection 2025 Feb.
The dataset presents the microbial diversity, community structure, and functional potential of the rhizosphere microbiome associated with in response to crop rotation involving a precursor. Soil samples were collected from the rhizospheres of two cultivars, Avenger and NS55, cultivated in soils previously used for cultivated in soils that have not previously been used for cultivation as follows: i) (SA1, SA2, and SA3) cultivated in soils previously used for , ii) (SN1, SN2, and SN3) grown in soils that had been cultivated with , iii) (RA1, RA2, and RA3) cultivated in soils not previously used for , iv) (RN1, RN2, and RN3) grown in soils not previously cultivated with Thereafter, the shotgun sequencing was done to assess the microbial composition and functional genes from the extracted DNA. The effective metagenome after QC of the twelve samples include SA1 (99.72%), SA2 (99.50%), SA3 (99.68%), SN1 (99.75%), SN2 (99.76%), SN3 (99.70%), RA1 (99.72%), RA2 (99.77%), RN3 (99.72%), RN1 (99.67%), RN2 (99.68%), and RN3 (99.54%). Information from the metagenome sequences is accessible under the bioproject numbers PRJNA1166458 (SA1, SA2, and SA3), PRJNA1166463 (SN1, SN2, and SN3), PRJNA1166623 (RA1, RA2, and RA3), PRJNA1166627 (RN1, RN2 and RN3). Actinomycetota and Function unknown dominated the microbiomes across all cropping systems The insights gained from this dataset hold promise for advancing sustainable agricultural practices, particularly through optimizing crop rotations, developing microbial bioinoculants, and enhancing soil health. Furthermore, the functional data and the function unknown from this dataset could enrich our understanding of microbial roles in nutrient cycling, plant growth promotion, and stress mitigation, which are critical for addressing challenges in food security and environmental sustainability.
该数据集展示了与[具体作物]相关的根际微生物群落的微生物多样性、群落结构和功能潜力，以响应涉及[前作作物]的轮作。从两个[作物品种名称]品种Avenger和NS55的根际采集土壤样本，这些样本采集自以前用于[前作作物]种植的土壤以及以前未用于[前作作物]种植的土壤，具体如下：i）在以前用于[前作作物]种植的土壤中种植的[品种名称1]（SA1、SA2和SA3），ii）在曾种植过[前作作物]的土壤中生长的[品种名称2]（SN1、SN2和SN3），iii）在以前未用于[前作作物]种植的土壤中种植的[品种名称3]（RA1、RA2和RA3），iv）在以前未种植过[前作作物]的土壤中生长的[品种名称4]（RN1、RN2和RN3）。此后，进行鸟枪法测序以评估从提取的DNA中获得的微生物组成和功能基因。十二个样本经过质量控制后的有效宏基因组包括SA1（99.72%）、SA2（99.50%）、SA3（99.68%）、SN1（99.75%）、SN2（99.76%）、SN3（99.70%）、RA1（99.72%）、RA2（99.77%）、RN3（99.72%）、RN1（99.67%）、RN2（99.68%）和RN3（99.54%）。宏基因组序列信息可在生物项目编号PRJNA1166458（SA1、SA2和SA3）、PRJNA1166463（SN1、SN2和SN3）、PRJNA1166623（RA1、RA2和RA3）、PRJNA1166627（RN1、RN2和RN3）下获取。放线菌门和功能未知的微生物在所有种植系统的微生物群落中占主导地位。从该数据集中获得的见解有望推动可持续农业实践的发展，特别是通过优化作物轮作、开发微生物生物接种剂和改善土壤健康。此外，该数据集的功能数据和功能未知信息可以丰富我们对微生物在养分循环、促进植物生长和缓解胁迫中的作用的理解，这些对于应对粮食安全和环境可持续性方面的挑战至关重要。
