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 with eleven growth phenotype data. We provided a thorough description of this dataset, followed by a comprehensive co-expression network analysis example that broke down the wall of the four-way relationship between plant gene-metabolite-microbe-phenotype, thus identifying the links between plant gene expression, metabolite accumulation, growth behavior, and rhizosphere microbiome variation under nutrient-poor conditions. Overall, this dataset enhances our understanding of plant and microbe interactions, offering valuable strategies and novel insights for resolving how plants regulate rhizosphere microbial compositions and functions, thereby improving host fitness, which will benefit future research.

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Publication Details

Journal
Scientific Data
Published
2025-04-30
DOI
https://doi.org/10.1038/s41597-025-05029-1
Citations
4
Primary Topic
Bioenergy crop production and management
Type
article
Field-Weighted Citation Impact
7.61

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article

An integrated transcriptome, metabolome, and microbiome dataset of Populus under nutrient-poor conditions

Jianbo Xie, Jiadong Wu, Shuxian Tan, Deqiang Zhang et al.
4 citations
Scientific Data
Bioenergy crop production and management
7.61
article

An integrated transcriptome, metabolome, and microbiome dataset of Populus under nutrient-poor conditions

Jianbo Xie, Jiadong Wu, Shuxian Tan, Deqiang Zhang, Sijia Liu, Yue Wang, Haofei Wang, Dalin He, Yuxin Du
article en
4 citations

Abstract

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 with eleven growth phenotype data. We provided a thorough description of this dataset, followed by a comprehensive co-expression network analysis example that broke down the wall of the four-way relationship between plant gene-metabolite-microbe-phenotype, thus identifying the links between plant gene expression, metabolite accumulation, growth behavior, and rhizosphere microbiome variation under nutrient-poor conditions. Overall, this dataset enhances our understanding of plant and microbe interactions, offering valuable strategies and novel insights for resolving how plants regulate rhizosphere microbial compositions and functions, thereby improving host fitness, which will benefit future research.

Scientific DataVol. 12(1)
Beijing Forestry University (CN), State Forestry and Grassland Administration (CN)
National Natural Science Foundation of China, Higher Education Discipline Innovation Project
No poverty
Openalex Percentile: Top 3%
Bioenergy crop production and management
7.61
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