An integrated transcriptome, metabolome, and microbiomedataset of Populus under low nitrogen conditions

The rhizosphere microbiota recruited by plants contributes significantly to maintaining host productivity and resisting stress. However, the genetic mechanisms by which plants regulate this recruitment process remain largely unclear. Here, we generated a comprehensive dataset, including 27 root transcriptomes, 27 root metabolomes, and 54 bulk or rhizosphere soil 16S rRNA amplicons across nine poplar species from four sections grown in low-nitrogen natural soil, along witheleven growth phenotype data. We provided a thoroughdescription of thisdataset, followed by a comprehensiveco-expression network analysis example that broke down the wall ofthe four-way relationship between plant gene-metabolite-microbe-phenotype, thusidentifyingthelinks between plant gene expression, metabolite accumulation, growth behavior, and rhizosphere microbiome variationunder low nitrogen conditions. Overall, this dataset enhances our understanding of plant and microbe interactions, offering valuable strategies and novel insights for resolving how plants regulate rhizosphere microbialcompositions and functions, thereby improving host fitness, which will benefit future research.

植物招募的根际微生物群（rhizosphere microbiota）在维持宿主生产力与抵御胁迫方面发挥着关键作用。然而，植物调控这一招募过程的遗传机制在很大程度上仍未阐明。
本研究构建了一套完整的数据集，涵盖了种植于低氮自然土壤中的、来自4个组的9个杨树物种的27份根转录组（root transcriptomes）、27份根代谢组（root metabolomes）以及54份原状土壤（bulk soil）或根际土壤的16S rRNA扩增子（16S rRNA amplicons），同时包含11项生长表型数据。
本研究对该数据集进行了详尽阐述，并提供了一个全面的共表达网络分析（co-expression network analysis）案例，该案例打破了植物基因-代谢物-微生物-表型四方关联的研究壁垒，进而明确了低氮条件下植物基因表达、代谢物积累、生长特性与根际微生物组变异之间的关联。
总体而言，本数据集深化了我们对植物与微生物互作的认知，为解析植物如何调控根际微生物组的组成与功能、进而提升宿主适合度（host fitness）提供了宝贵的研究策略与全新视角，将为未来相关研究带来重要助力。