Soil
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA551045 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR9695190_1.fastq.gz | Fastqsanger.gz | |||
| SRR9695190_2.fastq.gz | Fastqsanger.gz | |||
| SRR9695200_1.fastq.gz | Fastqsanger.gz | |||
| SRR9695200_2.fastq.gz | Fastqsanger.gz | |||
| SRR9695210_1.fastq.gz | Fastqsanger.gz |
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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 EarthM-bM-^@M-^Ys 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. Fifty four samples were collected from three soil types (Phaeozem,Cambisol,Acrisol) in three sites (Hailun, Fengqiu and Yingtan) along a latitude with reciprocal transplant; Both with and without maize cropping in each site; Three replicates in every treatments.
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Project description:Nitrogen (N), the primary limiting factor for plant growth and yield in agriculture, has a patchy distribution in soils due to fertilizer application or decomposing organic matter. Studies in solution culture over-simplify the complex soil environment where microbial competition and spatial and temporal heterogeneity challenge roots’ ability to acquire adequate amounts of nutrients required for plant growth. In this study, various ammonium treatments (as 15N) were applied to a discrete volume of soil containing tomato (Solanum lycopersicum) roots to simulate encounters with a localized enriched patch of soil. Transcriptome analysis was used to identify genes differentially expressed in roots 53 hrs after treatment. Results: The ammonium treatments resulted in significantly higher concentrations of both ammonium and nitrate in the patch soil. The plant roots and shoots exhibited increased levels of 15N over time, indicating a sustained response to the enriched environment. Root transcriptome analysis identified 585 genes differentially regulated 53 hrs after the treatments. Nitrogen metabolism and cell growth genes were induced by the high ammonium (65 ug NH4+-N g-1 soil), while stress response genes were repressed. The complex regulation of specific transporters following the ammonium pulse reflects a simultaneous and synergistic response to rapidly changing concentrations of both forms of inorganic N in the soil patch. Transcriptional analysis of the phosphate transporters demonstrates cross-talk between N and phosphate uptake pathways and suggests that roots increase phosphate uptake via the arbuscular mycorrhizal symbiosis in response to N. Conclusion: This work enhances our understanding of root function by providing a snapshot of the response of the tomato root transcriptome to a pulse of ammonium in a complex soil environment. This response includes an important role for the mycorrhizal symbiosis in the utilization of an N patch.
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Project description:Nitrogen (N), the primary limiting factor for plant growth and yield in agriculture, has a patchy distribution in soils due to fertilizer application or decomposing organic matter. Studies in solution culture over-simplify the complex soil environment where microbial competition and spatial and temporal heterogeneity challenge rootsâ ability to acquire adequate amounts of nutrients required for plant growth. In this study, various ammonium treatments (as 15N) were applied to a discrete volume of soil containing tomato (Solanum lycopersicum) roots to simulate encounters with a localized enriched patch of soil. Transcriptome analysis was used to identify genes differentially expressed in roots 53 hrs after treatment. Results: The ammonium treatments resulted in significantly higher concentrations of both ammonium and nitrate in the patch soil. The plant roots and shoots exhibited increased levels of 15N over time, indicating a sustained response to the enriched environment. Root transcriptome analysis identified 585 genes differentially regulated 53 hrs after the treatments. Nitrogen metabolism and cell growth genes were induced by the high ammonium (65 ug NH4+-N g-1 soil), while stress response genes were repressed. The complex regulation of specific transporters following the ammonium pulse reflects a simultaneous and synergistic response to rapidly changing concentrations of both forms of inorganic N in the soil patch. Transcriptional analysis of the phosphate transporters demonstrates cross-talk between N and phosphate uptake pathways and suggests that roots increase phosphate uptake via the arbuscular mycorrhizal symbiosis in response to N. Conclusion: This work enhances our understanding of root function by providing a snapshot of the response of the tomato root transcriptome to a pulse of ammonium in a complex soil environment. This response includes an important role for the mycorrhizal symbiosis in the utilization of an N patch. 9 Total samples were analyzed across 3 treatment groups (3 biological replicates per group). We generated the following pairwise comparisons using JMP Genomics software: Control vs. Low N, Control vs. high N, and low N vs. high N. One way ANOVA was used to determine significantly different expression. Genes with an FDRâ¤10% were presented.
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