Fishery subject-water-phytoplankton-2016
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA482936 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7610790_1.fastq.gz | Fastqsanger.gz | |||
| SRR7610790_2.fastq.gz | Fastqsanger.gz | |||
| SRR7610800_1.fastq.gz | Fastqsanger.gz | |||
| SRR7610800_2.fastq.gz | Fastqsanger.gz | |||
| SRR7610810_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 112 |
Similar Datasets
Project description:The dataset represents the proteome analysis of six sampling dates during the phytoplankton bloom at the island of Helgoland in the North Sea at the long term research station ‘Kabeltonne’ (54° 11' 17.88'' N, 7° 54' 0'' E) in 2016.
2020-12-15 | PXD019294 | Pride
Project description:Water column Macquarie Harbour - 2016 Raw sequence reads
| PRJNA738648 | ENA
Project description:The spring bloom in the North Atlantic develops over a few weeks in response to the physical stabilization of the nutrient replete water column and is one of the biggest biological signals on earth. The composition of the phytoplankton assemblage during the spring bloom of 2008 was evaluated, using a microarray, on the basis of functional genes that encode key enzymes in nitrogen and carbon assimilation in eukaryotic and prokaryotic phytoplankton. Oligonucleotide archetype probes representing RuBisCO, nitrate reductase and nitrate transporter genes from major phytoplankton classes detected a diverse assemblage. For RuBisCO, the archetypes with strongest signals represented known phytoplankton groups, but for the nitrate related genes, the major signals were not closely related to any known phytoplankton sequences. Most of the assemblage's components exhibited consistent temporal/spatial patterns. Yet, the strongest archetype signals often showed quite different patterns, indicating different ecological responses by the main players. The most abundant phytoplankton genera identified previously by microscopy, however, were not well represented on the microarray. The lack of sequence data for well-studied species, and the inability to identify organisms associated with functional gene sequences in the environment, still limits our understanding of phytoplankton ecology even in this relatively well-studied system.
2016-05-11 | GSE81262 | GEO
Project description:In summer 2014, we conducted experiments to determine the effects of different N substrates on phytoplankton communities in the North Pacific Ocean and in the transition zone of the California Current and gyre (Shilova, Mills et al., 2017). Samples were incubated with nitrate, ammonium, urea, and filtered deep water (FDW) for 48 hours (T48). Two treatments added iron, alone (Fe) or with a mix of N substrates (N+Fe), to determine the effects of Fe on the utilization of N substrates. All treatments resulted in changes in phytoplankton cell abundances and photosynthetic activity at both locations, with differences between phytoplankton groups. Prochlorococcus had large increases in biomass in response to ammonium and urea, while both eukaryotic phytoplankton and Synechococcus had only modest biomass increases in response to N+Fe and FDW. Moreover, distinct physiological responses were observed within sub-populations of Prochlorococcus and Synechococcus. In order to understand the variable responses to N substrates among phytoplankton groups and sub-populations in the California Current transition zone, the present work examines transcriptional changes that occurred 24 h after the substrates were added. Specifically, we hypothesize that transcription changes at 24 h indicate which phytoplankton taxa are N-limited, and thus help explain changes in cell abundances and photosynthetic activity by individual phytoplankton groups observed at 48 h. Furthermore, we hypothesize that the diversity in physiological responses within Prochlorococcus and Synechococcus are evident in the transcriptional responses measured at sub-population resolution.
2020-04-12 | GSE130464 | GEO
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
Project description:Seasonal changes in nitrogen assimilation have been studied in the western English Channel by sampling at approximately weekly intervals for 12 months. Nitrate concentrations showed strong seasonal variations. Available nitrogen in the winter was dominated by nitrate but this was close to limit of detection from May to September, after the spring phytoplankton bloom. 15N uptake experiments showed that nitrate was the nitrogen source for the spring phytoplankton bloom but regenerated nitrogen supported phytoplankton productivity throughout the summer. The average annual f ratio was 0.35, which demonstrated the importance of ammonia regeneration in this dynamic temperate region. Nitrogen uptake rate measurements were related to the phytoplankton responsible by assessing the relative abundance of nitrate reductase (NR) genes and the expression of NR among eukaryotic phytoplankton. Strong signals were detected from NR sequences that are not associated with known phylotypes or cultures. NR sequences from the diatom Phaeodactylum tricornutum were highly represented in gene abundance and expression, and were significantly correlated with f ratio. The results demonstrate that analysis of functional genes provides additional information, and may be able to give better indications of which phytoplankton species are responsible for the observed seasonal changes in f ratio than microscopic phytoplankton identification.
2011-03-17 | GSE27998 | GEO
Project description:phytoplankton metagenome Raw sequence reads
| PRJNA997602 | ENA
Project description:phytoplankton metagenome Raw sequence reads
| PRJNA645508 | ENA
Project description:phytoplankton metagenome Raw sequence reads
| PRJNA707255 | ENA
Project description:phytoplankton metagenome Raw sequence reads
| PRJNA975668 | ENA