Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Varese Lake 2016-2017 bloom shotgun Metagenomics

PROVIDER: PRJNA694367 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR13516731_1.fastq.gz	Fastqsanger.gz
	SRR13516731_2.fastq.gz	Fastqsanger.gz
	SRR13516732_1.fastq.gz	Fastqsanger.gz
	SRR13516732_2.fastq.gz	Fastqsanger.gz
	SRR13516733_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 49

Similar Datasets

lake water metagenome

Project description:Shotgun metagenomics of virion (0.22 micrometer filtrate) in Lake Biwa (2016-2017)

| PRJDB7309 | ENA

Varese Lake 2016-2017 bloom 16S V3-V4 amplicons

Project description:Varese Lake 2016-2017 bloom 16S V3-V4 amplicons

| PRJNA694444 | ENA

lake water metagenome

Project description:Shotgun metagenomics of bacterioplankton in Lake Biwa (2016)

| PRJDB6644 | ENA

Climate warming and nutrient enrichment jointly affect microbial functional potentials important to nutrient cycling in shallow-lake mesocosms

Project description:Here, we applied a microarray-based metagenomics technology termed GeoChip 5.0 to investigate spring microbial functional genes in mesocosm-simulated shallow lake ecosystems having been undergoing nutrient enrichment and warming for nine years.

2020-12-30 | GSE155582 | GEO

RNA-seq data on leaf 8 blade tissue of 62 individual Brassica napus (Darmor) plants grown in the field.

Project description:62 individual Brassica napus plants of the same accession grown in the same field were expression-profiled in autumn 2016 and phenotyped extensively until harvest in spring 2017. Machine learning models were used to link gene expression to the phenotypes of individual plants, with the purpose of assessing how much phenotype information in encoded in ‘noisy’ gene expression variation among individual plants of the same background grown under the same uncontrolled field conditions. Rosette leaf 8 blades of 62 individual Brassica napus plants of the same winter-type accession (BnASSYST-120, Darmor) grown in the same field (50°58'24.9\\"N 3°46'49.1\\"E, Merelbeke, Belgium) were RNA-seq profiled. No treatments or stresses were applied, all plants were profiled individually under uncontrolled field conditions. Sown at 2016-09-08, rosette leaf 8 sampled for RNA-seq at 2016-11-28, plants harvested at 2017-06-13.

2022-10-10 | E-MTAB-11904 | biostudies-arrayexpress

Bacteria

Project description:Bacteria isolated from a Lake Erie Microcystis bloom in 2017

| PRJNA521711 | ENA

LMO J.Pinhassi_17_04 J.Pinhassi_18_06

Project description:LMO metaT 2016-2017

| PRJEB69280 | ENA

Project description:lake Baikal (Siberia, Russia) sediments, Shotgun Metagenomics

| PRJNA703749 | ENA

Towards functional profiling for eDNA based monitoring in coastal environments: a comparison of three approaches

Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.

2024-04-14 | E-MTAB-13075 | biostudies-arrayexpress

Metatranscriptomes of phytoplankton blooms from an ocean acidification mesocosm experiment

Project description:Sequencing the metatranscriptome can provide information about the response of organisms to varying environmental conditions. We present a methodology for obtaining random whole-community mRNA from a complex microbial assemblage using Pyrosequencing. The metatranscriptome had, with minimum contamination by ribosomal RNA, significant coverage of abundant transcripts, and included significantly more potentially novel proteins than in the metagenome. Keywords: metatranscriptome, mesocosm, ocean acidification This experiment is part of a much larger experiment. We have produced 4 454 metatranscriptomic datasets and 6 454 metagenomic datasets. These were derived from 4 samples. The experiment is an ocean acidification mesocosm set up in a Norwegian Fjord in 2006. We suspended 6 bags containing 11,000 L of sea water in a Coastal Fjord and then we bubbled CO2 through three of these bags to simulate ocean acidification conditions in the year 2100. The other three bags were bubbled with air. We then induced a phytoplankton bloom in all six bags and took measurements and performed analyses of phytoplankton, bacterioplankton and physiochemical characteristics over a 22 day period. We took water samples from the peak of the phytoplankton bloom and following the decline of the phytoplankton bloom to analyses using 454 metagenomics and 454 metatranscriptomics. Day 1, High CO2 Bag and Day 1, Present Day Bag, refer to the metatranscriptomes from the peak of the bloom. Day 2, High CO2 Bag and Day 2, Present Day Bag, refer to the metatranscriptomes following the decline of the bloom. Obviously High CO2 refers to the ocean acidification mesocosm and Present Day refers to the control mesocosm. Raw data for both the metagenomic and metatranscriptomic components are available at NCBI's Short Read Archive at ftp://ftp.ncbi.nlm.nih.gov/sra/Studies/SRP000/SRP000101

2008-02-08 | E-GEOD-10119 | 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