Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: rhizosphere bacterial community structure

PROVIDER: PRJNA1008852 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR25760700.fastq.gz	Fastqsanger.gz
	SRR25760701.fastq.gz	Fastqsanger.gz
	SRR25760702.fastq.gz	Fastqsanger.gz
	SRR25760703.fastq.gz	Fastqsanger.gz
	SRR25760704.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 12

Similar Datasets

GeoChip data of soil microbial communities in the maize rhizosphere and bulk soils

2014-09-12 | GSE61338 | GEO

Project description:peanut rhizosphere soil bacterial community structure

| PRJNA852215 | ENA

soil metagenome

Project description:bacterial community structure of oil palm rhizosphere

| PRJDB16473 | ENA

Bacterial community structure in Turmeric rhizosphere

Project description:Bacterial community structure in Turmeric rhizosphere Metagenome

| PRJNA659126 | ENA

Project description:Bacterial community structure in maize rhizosphere soil

| PRJNA656634 | ENA

Project description:Bacterial community structure of GM cotton rhizosphere

| PRJNA391400 | ENA

C. elegans genomic response to Konza Prairie Soil bacterial environment

Project description:Here we have compared adult wildtype (N2) C. elegans gene expression when grown on different bacterial environments/fod sources in an effort to model naturally occuring nematode-bacteria interactions at the Konza Prairie. We hypothesize that human-induced changes to natural environments, such as the addition of nitrogen fertalizer, have effects on the bacterial community in soils and this drives downstream changes in the structure on soil bacterial-feeding nematode community structure. Here we have used transcriptional profiling to identify candidate genes involved in the interaction of nematodes and bacteria in nature.

2009-05-02 | GSE15923 | GEO

Application of BiodegPhyloChip for expression profiling of functional genes from diverse contaminated habitats

Project description:Understanding the bacterial community structure, and their functional analysis for active bioremediation process is essential to design better and cost effective strategies. Microarray analysis enables us to simultaneously study the functional and phylogenetic markers of hundreds of microorganisms which are involved in active bioremediation process in an environment. We have previously described development of a hybrid 60-mer multibacterial microarray platform (BiodegPhyloChip) for profiling the bacterial communities and functional genes simultaneously in environments undergoing active bioremediation process (Pathak et al; Appl Microbiol Biotechnol,Vol. 90, 1739-1754). The present study involved profiling the status of bacterial communities and functional (biodegradation) genes using the developed 60-mer oligonucleotide microarray BiodegPhyloChip at five contaminated hotspots in the state of Gujarat, in western India. The expression pattern of functional genes (coding for key enzymes in active bioremediation process) at these sites was studied to understand the dynamics of biodegradation in the presence of diverse group of chemicals. The results indicated that the nature of pollutants and their abundance greatly influence the structure of bacterial communities and the extent of expression of genes involved in various biodegradation pathways. In addition, site specific factors also play a pivotal role to affect the microbial community structure as was evident from results of 16S rRNA gene profiling of the five contaminated sites, where the community structure varied from one site to another drastically.

2012-12-01 | GSE38004 | GEO

Project description:bacterial community structure in the rhizosphere of tea

| PRJNA916592 | ENA

GeoChip data of soil microbial communities in the maize rhizosphere and bulk soils

Project description:Microbial communities in the rhizosphere make significant contributions to crop health and nutrient cycling. However, their ability to perform important biogeochemical processes remains uncharacterized. Important functional genes, which characterize the rhizosphere microbial community, were identified to understand metabolic capabilities in the maize rhizosphere using GeoChip 3.0-based functional gene array method. Triplicate samples were taken for both rhizosphere and bulk soil, in which each individual sample was a pool of four plants or soil cores. To determine the abundance of functional genes in the rhizosphere and bulk soils, GeoChip 3.0 was used.

2014-09-12 | E-GEOD-61338 | biostudies-arrayexpress

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