Rainfed cropland soil metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA728219 | ENA |
REPOSITORIES: ENA
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2024-08-12 | GSE274211 | GEO
Project description:Purpose: Deconstructing the soil microbiome into reduced-complexity functional modules represents a novel method of microbiome analysis. The goals of this study are to confirm differences in transcriptomic patterns among five functional module consortia. Methods: mRNA profiles of 3 replicates each of functional module enrichments of soil inoculum in M9 media with either 1) xylose, 2) n-acetylglucosamine, 3) glucose and gentamycin, 4) xylan, or 5) pectin were generated by sequencing using an Illumina platform (GENEWIZ performed sequencing). Sequence reads that passed quality filters were aligned to a soil metagenome using Burrows Wheeler Aligner. Resulting SAM files were converted to raw reads using HTSeq, and annotated using Uniref90 or EGGNOG databases. Results: To reduce the size of the RNA-Seq counts table and increase its computational tractability, transcripts containing a minimum of 75 total counts, but no more than 3 zero counts, across the 15 samples were removed. The subsequent dataset was normalized using DESeq2, resulting in a dataset consisting of 6947 unique transcripts across the 15 samples, and 185,920,068 reads. We identified gene categories that were enriched in a sample type relative to the overall dataset using Fisher’s exact test. Conclusions: our dataset confirms that the functional module consortia generated from targeted enrichments of a starting soil inoculum had distinct functional trends by enrichment type.
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Project description:The experiment at three long-term agricultural experimental stations (namely the N, M and S sites) across northeast to southeast China was setup and operated by the Institute of Soil Science, Chinese Academy of Sciences. This experiment belongs to an integrated project (The Soil Reciprocal Transplant Experiment, SRTE) which serves as a platform for a number of studies evaluating climate and cropping effects on soil microbial diversity and its agro-ecosystem functioning. Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of soil type, soil transplant and landuse changes on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles.
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Project description:The present invention relates to methods for determining soil quality, and especially soil pollution, using the invertebrate soil organism Folsomia candida also designated as springtail. Specifically, the present invention relates to a method for determining soil quality comprising: contacting Folsomia Candida with a soil sample to be analysed during a time period of 1 to 5 days; isolating said soil contacted Folsomia Candida; extracting RNA from said isolated soil contacted Folsomia Candida; determing a gene expression profile based on said extracted RNA using microarray technology; comparing said gene expression profile with a reference gene expression profile; and determing soil quality based expression level differences between said gene expression profile and said control expression profile.
2014-07-19 | GSE59588 | GEO
Project description:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.
2013-10-30 | GSE51592 | GEO