Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Seagrass bed sediment Raw sequence reads

PROVIDER: PRJNA744715 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR15068625_1.fastq.gz	Fastqsanger.gz
	SRR15068625_2.fastq.gz	Fastqsanger.gz
	SRR15068626_1.fastq.gz	Fastqsanger.gz
	SRR15068626_2.fastq.gz	Fastqsanger.gz
	SRR15068627_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 60

Similar Datasets

Project description:Seagrass bed sediment Raw sequence reads

| PRJNA646607 | ENA

Seagrass bed sediment

Project description:Seagrass bed sediment Raw sequence reads

| PRJNA613355 | ENA

seagrass bed sediment, Hainan, China

Project description:seagrass bed sediment, Hainan, China Raw sequence reads

| PRJNA595452 | ENA

seagrass bed biome

Project description:Seagrass bed biome raw sequence reads

| PRJNA1042847 | ENA

Morus alba Raw protein sequence reads

Project description:Morus alba L. Raw protein sequence reads and sequence

2024-02-08 | PXD049451 |

16s RNA sequencing data from environmental and steel corrosion samples, Shoreham Harbour, UK

Project description:16s RNA gene sequencing data from seawater, bed sediment and steel corrosion samples from Shoreham Harbour, UK, collected to allow bacterial species comparisons between microbially influenced corrosion, the surrounding seawater, and the sea bed sediment at the seafloor and 50cm depth below seafloor.

2019-10-06 | E-MTAB-8373 | biostudies-arrayexpress

marine sediment metagenome and seagrass metagenome

Project description:marine sediment metagenome and seagrass metagenome Raw sequence reads

| PRJNA427074 | ENA

Eukaryotes associated with seagrass sediment

Project description:Raw sequence reads of eukaryotes associated with seagrass sediment

| PRJNA597113 | ENA

LC-MS/MS of autotrophic culture KS, that performs nitrate reduction coupled to iron(II) oxidation (NDFO)

Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.

2021-05-17 | PXD023186 | Pride

High-throughput 16S rRNA amplicon pyrosequencing of contaminated aquifer sediment

Project description:Contaminated aquifer (Dusseldorf-Flinger, Germany) templates extracted from 5 sediment depths ranging between 6.4 and 8.4 m below ground and over 3 years of sampling were amplified for amplicon pyrosequencing using the primers Ba27f (5’-aga gtt tga tcm tgg ctc ag-3’) and Ba519r (5’- tat tac cgc ggc kgc tg-3’), extended as amplicon fusion primers with respective primer A or B adapters, key sequence and multiplex identifiers (MID) as recommended by 454/Roche. Amplicons were purified and pooled as specified by the manufacturer. Emulsion PCR (emPCR), purification of DNA-enriched beads and sequencing run were performed following protocols and using a 2nd generation pyrosequencer (454 GS FLX Titanium, Roche) as recommended by the developer. Quality filtering of the pyrosequencing reads was performed using the automatic amplicon pipeline of the GS Run Processor (Roche), with a slight modification concerning the valley filter (vfScanAllFlows false instead of TiOnly) to extract the sequences. Demultiplexed raw reads were furhter trimmed for quality and lenght (>250 bp).

2012-11-11 | GSE25345 | 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