Soil from different vineyards
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA907731 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22682022_1.fastq.gz | Fastqsanger.gz | |||
| SRR22682022_2.fastq.gz | Fastqsanger.gz | |||
| SRR22682023_1.fastq.gz | Fastqsanger.gz | |||
| SRR22682023_2.fastq.gz | Fastqsanger.gz | |||
| SRR22682024_1.fastq.gz | Fastqsanger.gz |
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Project description:Metagenome of soil from vineyards under different agricultural management practices
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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:Metaproteome analysis of a forest soil and a potting soil. Different protein extraction methods were compared to investigate protein extraction efficiency and compatibility with sample downstream processing.
2015-03-26 | PRD000542 | Pride
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.
2011-02-15 | GSE21213 | GEO
Project description:Polycyclic aromatic hydrocarbons are common pollutants in soil, have negative effects on soil ecosystems, and are potentially carcinogenic. The Springtail (Collembola) Folsomia candida is often used as an indicator species for soil toxicity. Here we report a toxicogenomic study that translates the ecological effects of the polycyclic aromatic hydrocarbon phenanthrene in soil to the early transcriptomic responses in Folsomia candida. Microarrays were used to examine two different exposure concentrations of phenanthrene, namely the EC10 (24.95 mg kg-1 soil) and EC50 (45.80 mg kg-1 soil) on reproduction of this springtail, which evoked 405 and 251 differentially expressed transcripts, respectively. Fifty transcripts were differential in response to either concentration. Many transcripts encoding xenobiotic detoxification and biotransformation enzymes (phases I, II, and III) were upregulated in response to either concentration. Furthermore, indications of general and oxidative stress were found in response to phenanthrene. Chitin metabolism appeared to be disrupted particularly at the low concentration, and protein translation appeared suppressed at the high concentration of phenanthrene; most likely in order to reallocate energy budgets for the detoxification process. Finally, an immune response was evoked especially in response to the high effect concentration, which was also described in a previous transcriptomic study using the same effect concentration (EC50) of cadmium. Our study provides new insights in the molecular mode of action of the important polluting class of polycyclic aromatic hydrocarbons in soil animals. Furthermore, we present a fast, sensitive, and specific soil toxicity test which enhances traditional tests and may help to improve current environmental risk assessments and monitoring of potentially polluted sites.
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Project description:Background: The soil environment is responsible for sustaining most terrestrial plant life on earth, yet we know surprisingly little about the important functions carried out by diverse microbial communities in soil. Soil microbes that inhabit the channels of decaying root systems, the detritusphere, are likely to be essential for plant growth and health, as these channels are the preferred locations of new root growth. Understanding the microbial metagenome of the detritusphere and how it responds to agricultural management such as crop rotations and soil tillage will be vital for improving global food production. Methods: The rhizosphere soils of wheat and chickpea growing under + and - decaying root were collected for metagenomics sequencing. A gene catalogue was established by de novo assembling metagenomic sequencing. Genes abundance was compared between bulk soil and rhizosphere soils under different treatments. Conclusions: The study describes the diversity and functional capacity of a high-quality soil microbial metagenome. The results demonstrate the contribution of the microbiome from decaying root in determining the metagenome of developing root systems, which is fundamental to plant growth, since roots preferentially inhabit previous root channels. Modifications in root microbial function through soil management, can ultimately govern plant health, productivity and food security.
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Project description:To study the soil mcirobial functional communities and the nutrient cycles couplings changes after exposure to different contaminant
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Project description:Environmental pollution is a worldwide problem, and metals are the largest group of contaminants in soil. Microarray toxicogenomic studies with ecologically relevant organisms such as springtails, supplement traditional ecotoxicological research, but are presently rather descriptive. Classifier analysis, a more analytical application of the microarray technique, is able to predict biological classes of unknown samples. We used the uncorrelated shrunken centroid (USC) method to classify gene expression profiles of the springtail Folsomia candida exposed to soil spiked with six different metals (barium, cadmium, cobalt, chromium, lead, and zinc). We identified a gene set (classifier) of 188 genes that can discriminate between six different metals present in soil, which allowed us to predict the correct classes for samples of an independent test set with an accuracy of 83% (error rate = 0.17). This study shows further that in order to apply classifier analysis to actual contaminated field soil samples, more insight and information is needed on the transcriptional responses of soil organisms to different soil types (properties) and mixtures of contaminants.
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