Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Soil samples of Karst

PROVIDER: PRJNA899297 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR22225200_1.fastq.gz	Fastqsanger.gz
	SRR22225200_2.fastq.gz	Fastqsanger.gz
	SRR22225201_1.fastq.gz	Fastqsanger.gz
	SRR22225201_2.fastq.gz	Fastqsanger.gz
	SRR22225202_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 66

Similar Datasets

Project description:Forest soil samples from the Karst area

| PRJNA722275 | ENA

Project description:Karst Rice Soil

| PRJNA814987 | ENA

Project description:Karst tiankeng soil microbes

| PRJNA1132395 | ENA

soil metagenome

Project description:Karst soil sample Metagenome

| PRJNA302087 | ENA

Project description:Soil chronosequences in karst area

| PRJNA756871 | ENA

Karst tiankeng soil

Project description:Karst tiankeng soil Raw sequence reads

| PRJNA843191 | ENA

Karst tiankeng soil

Project description:Karst tiankeng soil Raw sequence reads

| PRJNA843199 | ENA

Project description:Soil microbiome along karst vegetation restoration

| PRJNA913838 | ENA

Functional environmental genomics of a municipal landfill soil

Project description:We investigated the toxicity of soil samples derived from a former municipal landfill site in the South of the Netherlands, where a bioremediation project is running aiming at reusing the site for recreation. Both an organic soil extract and the original soil sample was investigated using the ISO standardised Folsomia soil ecotoxicological testing and gene expression analysis. The 28 day survival/reproduction test revealed that the ecologically more relevant original soil sample was more toxic than the organic soil extract. Microarray analysis showed that the more toxic soil samples induced gene regulatory changes in twice as less genes compared to the soil extract. Consequently gene regulatory changes were highly dependent on sample type, and were to a lesser extent caused by exposure level. An important biological process shared among the two sample types was the detoxification pathway for xenobiotics (biotransformation I, II and III) suggesting a link between compound type and observed adverse effects. Finally, we were able to retrieve a selected group of genes that show highly significant dose-dependent gene expression and thus were tightly linked with adverse effects on reproduction. Expression of four cytochrome P450 genes showed highest correlation values with reproduction, and maybe promising genetic markers for soil quality. However, a more elaborate set of environmental soil samples is needed to validate the correlation between gene expression induction and adverse phenotypic effects.

2012-04-16 | GSE37154 | GEO

Classifier analysis of gene expression profiles reveals a discriminatory gene set for soil containing different metals

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.

2010-02-05 | GSE19353 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data