An integrated transcriptome, metabolome, and microbiome dataset of Populus under nutrient-poor 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 nutrient-poor 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 nutrient-poorconditions. 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重要作用。然而，植物调控这一招募过程的遗传机制在很大程度上仍不明晰。本研究构建了一套综合性数据集，涵盖源自4个组的9个杨树物种的27个根转录组（root transcriptomes）、27个根代谢组（root metabolomes），以及54份非根际土壤与根际土壤的16S rRNA扩增子（16S rRNA amplicons），所有材料均种植于贫营养自然土壤中，同时附带11项生长表型数据。本研究对该数据集进行了详尽阐述，并提供了一套完整的共表达网络分析（co-expression network analysis）示例，破解了植物基因-代谢物-微生物-表型四方关联的壁垒，从而明确了贫营养条件下植物基因表达、代谢物积累、生长特性与根际微生物群变异之间的关联。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群的组成与功能、进而提升宿主适合度提供了宝贵的研究策略与全新视角，将为后续相关研究提供重要支撑。