Soil metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB14264 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR429576.fastq.gz | Fastqsanger.gz | |||
| DRR429577.fastq.gz | Fastqsanger.gz | |||
| DRR429578.fastq.gz | Fastqsanger.gz | |||
| DRR429579.fastq.gz | Fastqsanger.gz | |||
| DRR429580.fastq.gz | Fastqsanger.gz |
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Project description:The goal of this growth chamber experiment was to investigate the effects of diverse soil microbial communities on the transcriptional responses of plants to drought. Specifically, we sought to understand how soil microbiomes' past exposure to water-limited conditions (either long-term exposure to dry conditions in low-precipitation sites, or recent acute drought) impacted their interactions with plants. Six soils collected from remnant prairies crossing a steep precipitation gradient in Kansas, USA were used as the starting microbial communities. Thirty-two pots (or mesocosms) of each soil were divided among four treatments: droughted or well-watered, and with or without a host plant (Tripsacum dactyloides) in a factorial design. The soil mesocosms were "conditioned" in these treatments for five months. (Metagenome and metatranscriptome data from the baseline soils and the post-conditioning soils are available in a separate BioProject on NCBI SRA and GEO). Then, a microbial slurry extracted from each of the 192 conditioned soils was used to inoculate 4 plants in a subsequent experiment (the “Test Phase”): one pot per combination of watering treatment (droughted or control) and host species (Zea mays or Tripsacum dactyloides). After 4 weeks (for maize) or 5 weeks (for eastern gamagrass) we harvested one crown root per plant for 16S rRNA sequencing and another crown root for RNA-seq. The 16S and RNA-seq data for these plants (both species) are contained in this BioProject. Note that 16S rRNA sequencing data are available for all plants in this experiment, but we conducted RNA-seq only for a subset (all plants grown in microbiomes originating from the 2 driest and 2 wettest collection sites).
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Project description:It has long been recognized that species occupy a specific ecological niche within their ecosystem. The ecological niche is defined as the number of conditions and resources that limit species distribution. Within their ecological niche, species do not exist in a single physiological state but in a number of states we call the Natural Operating Range. In this paper we link ecological niche theory to physiological ecology by measuring gene expression levels of collembolans exposed to various natural conditions. The soil-dwelling collembolan Folsomia candida was exposed to 26 natural soils with different soil characteristics (soil type, land use, practice, etc). The animals were exposed for two days and gene expression levels were measured. The main factor found to regulate gene expression was the soil type (sand or clay), in which 18.5% of the measured genes were differentially expressed. Gene Ontology analysis showed animals exposed to sandy soils experience general stress, affecting cell homeostasis and replication. Multivariate analysis linking soil chemical data to gene expression data revealed that soil fertility influences gene expression. Land-use and practice had less influence on gene expression; only forest soils showed a different expression pattern. A variation in gene expression variation analysis showed overall low variance in gene expression. The large difference in response to soil type was caused by the soil physicochemical properties where F. candida experiences clay soils and sandy soils as very different from each other. This collembolan prefers fertile soils with high organic matter content, as soil fertility was found to correlate with gene expression and animals exposed to sandy soils (which, in general, have lower organic matter content) experience more general stress. Finally, we conclude that there is no such thing as a fixed physiological state for animals in their ecological niche and the boundary between the ecological niche and a stressed state depends on the genes/pathways investigated. Test animals were exposed to 26 natural soils + 2 control soils. 4 biological replicates per soil containing 25 grams of soil and 30 23-day-old animals per replicate, RNA was isolated after two days of exposure. for the micro-array hybridization design we made use of an interwoven loop design. from the four replicates per soil two were labeled with Cy3 and 2 with Cy5. It was made sure that now two replicates of the same soil were ever hybridized against the same soil.
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Abstract
Two factors that are well-known to influence soil microbiomes include the depth of the soil as well as the level of moisture. Previous works have demonstrated that climate change will increase the incidence of drought in soils, but it is unknown how fluctuations in moisture availability affect soil microbiome composition and functioning down the depth profile. Here, we investigated soil and wheatgrass rhizosphere microbiomes in a common field setting under four different irrigation regimes and three depths. We demonstrated that there is a significant interactive effect, where fluctuations in soil moisture more strongly influence soil microbiomes at the surface layer than in deeper layers, including for soil community composition, diversity, and for functional profiles. Meanwhile, in rhizosphere communities the influence of irrigation was similar across the different depths, although there were slight discrepancies between the two cultivars of wheatgrass used. The lessened response of deeper soil microbiomes to changes in irrigation may be due to higher incidence of slow-growing, stress-resistant microbes.
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