Accessing BCO-DMO data
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BCO-DMO ERDDAP
Accessing BCO-DMO data |
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| Dataset Title: | [Switch RNAseq] - Transcriptional profile of marine bacterium Ruegeria pomeroyi in a three-member co-culture study (Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_719970) |
| Information: | Summary
| License
| ISO 19115
| Metadata
| Background
| Files
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Attributes {
s {
Locus_Tag {
String bcodmo_name "sample";
String description "gene identifier";
String long_name "Locus Tag";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
String units "unitless";
}
Description {
String bcodmo_name "brief_desc";
String description "gene function, if known";
String long_name "Description";
String units "unitless";
}
Day7_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 7, replicate 1";
String long_name "Day7 R1";
String units "TPM (transcripts per million)";
}
Day7_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 7, replicate 2";
String long_name "Day7 R2";
String units "TPM (transcripts per million)";
}
Day9_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 9, replicate 1";
String long_name "Day9 R1";
String units "TPM (transcripts per million)";
}
Day9_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 9, replicate 2";
String long_name "Day9 R2";
String units "TPM (transcripts per million)";
}
Day12_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 12, replicate 1";
String long_name "Day12 R1";
String units "TPM (transcripts per million)";
}
Day12_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 12, replicate 2";
String long_name "Day12 R2";
String units "TPM (transcripts per million)";
}
Day15_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 15, replicate 1";
String long_name "Day15 R1";
String units "TPM (transcripts per million)";
}
Day15_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 15, replicate 2";
String long_name "Day15 R2";
String units "TPM (transcripts per million)";
}
Day18_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 18, replicate 1";
String long_name "Day18 R1";
String units "TPM (transcripts per million)";
}
Day18_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 18, replicate 2";
String long_name "Day18 R2";
String units "TPM (transcripts per million)";
}
Day23_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 23, replicate 1";
String long_name "Day23 R1";
String units "TPM (transcripts per million)";
}
Day23_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 23, replicate 2";
String long_name "Day23 R2";
String units "TPM (transcripts per million)";
}
Day30_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 30, replicate 1";
String long_name "Day30 R1";
String units "TPM (transcripts per million)";
}
Day30_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 30, replicate 2";
String long_name "Day30 R2";
String units "TPM (transcripts per million)";
}
Day37_R1 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 37, replicate 1";
String long_name "Day37 R1";
String units "TPM (transcripts per million)";
}
Day37_R2 {
String bcodmo_name "count";
String description "Transcript count by day and replicate: day 37, replicate 2";
String long_name "Day37 R2";
String units "TPM (transcripts per million)";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Published methodology in Landa et al., 2017, ISME Journal, in press.
One liter samples were filtered through 2-um polycarbonate (PC) membranes to
collect bacterial cells and flash-frozen in liquid nitrogen and stored at
-80C. Filters were extracted for RNA by the acid
phenol:chloroform:isoamylalcohol method. Potential traces of DNA were removed
using the Turbo DNA-free kit (Invitrogen, Waltham, MA, USA). Samples were
tested for residual DNA by a 40-cycle PCR targeting the 16S rRNA gene of R.
pomeroyi. Samples were depleted of rRNA using custom probes for small and
large subunit rRNA genes from all three microbes (Stewart et al., 2010).
Libraries were prepared for two replicate cubitainers at 8 time points (16
samples) using the KAPA Stranded mRNA-Seq Kit (Kapa Biosystems, Wilmington,
MA, USA) at the Georgia Genomics Facility (University of Georgia) and
sequenced on a HiSeq Illumina 2500 at the Hudson Alpha Institute for
Biotechnology (AL, USA).
Reference cited:
Stewart FJ, Ottesen EA, DeLong EF. (2010). Development and quantitative
analyses of a universal rRNA-subtraction protocol for microbial
metatranscriptomics. ISME J 4: 896\\u2013907.
doi:[10.1038/ismej.2010.18](\\\\\"https://dx.doi.org/10.1038/ismej.2010.18\\\\\")";
String awards_0_award_nid "541254";
String awards_0_award_number "OCE-1342694";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1342694";
String awards_0_funder_name "NSF Division of Ocean Sciences";
String awards_0_funding_acronym "NSF OCE";
String awards_0_funding_source_nid "355";
String awards_0_program_manager "David L. Garrison";
String awards_0_program_manager_nid "50534";
String cdm_data_type "Other";
String comment
"Switch RNAseq Data
PI: Mary Ann Moran (University of Georgia)
Version: 29 November 2017
Note: Transcript counts are reported in TPM (transcripts per million). This is the number of transcript
reads mapped to an individual gene for every million transcripts mapped to the entire genome.";
String Conventions "COARDS, CF-1.6, ACDD-1.3";
String creator_email "info@bco-dmo.org";
String creator_name "BCO-DMO";
String creator_type "institution";
String creator_url "https://www.bco-dmo.org/";
String data_source "extract_data_as_tsv version 2.3 19 Dec 2019";
String date_created "2017-11-27T20:45:13Z";
String date_modified "2020-01-14T16:35:14Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.719970.1";
String history
"2024-12-03T17:30:50Z (local files)
2024-12-03T17:30:50Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_719970.html";
String infoUrl "https://www.bco-dmo.org/dataset/719970";
String institution "BCO-DMO";
String instruments_0_acronym "Automated Sequencer";
String instruments_0_dataset_instrument_description "Transcripts were sequenced on a HiSeq Illumina 2500 at the Hudson Alpha Institute for Biotechnology (AL, USA).";
String instruments_0_dataset_instrument_nid "720063";
String instruments_0_description "General term for a laboratory instrument used for deciphering the order of bases in a strand of DNA. Sanger sequencers detect fluorescence from different dyes that are used to identify the A, C, G, and T extension reactions. Contemporary or Pyrosequencer methods are based on detecting the activity of DNA polymerase (a DNA synthesizing enzyme) with another chemoluminescent enzyme. Essentially, the method allows sequencing of a single strand of DNA by synthesizing the complementary strand along it, one base pair at a time, and detecting which base was actually added at each step.";
String instruments_0_instrument_name "Automated DNA Sequencer";
String instruments_0_instrument_nid "649";
String instruments_0_supplied_name "HiSeq Illumina 2500";
String keywords "bco, bco-dmo, biological, chemical, data, dataset, day12, Day12_R1, Day12_R2, day15, Day15_R1, Day15_R2, day18, Day18_R1, Day18_R2, day23, Day23_R1, Day23_R2, day30, Day30_R1, Day30_R2, day37, Day37_R1, Day37_R2, day7, Day7_R1, Day7_R2, day9, Day9_R1, Day9_R2, description, dmo, erddap, locus, Locus_Tag, management, oceanography, office, preliminary, tag";
String license "https://www.bco-dmo.org/dataset/719970/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/719970";
String param_mapping "{'719970': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/719970/parameters";
String people_0_affiliation "University of Georgia";
String people_0_affiliation_acronym "UGA";
String people_0_person_name "Mary Ann Moran";
String people_0_person_nid "51592";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Woods Hole Oceanographic Institution";
String people_1_affiliation_acronym "WHOI BCO-DMO";
String people_1_person_name "Shannon Rauch";
String people_1_person_nid "51498";
String people_1_role "BCO-DMO Data Manager";
String people_1_role_type "related";
String project "OceanSulfurFluxBact";
String projects_0_acronym "OceanSulfurFluxBact";
String projects_0_description
"Surface ocean bacterioplankton preside over a divergence point in the marine sulfur cycle where the fate of dimethylsulfoniopropionate (DMSP) is determined. While it is well recognized that this juncture influences the fate of sulfur in the ocean and atmosphere, its regulation by bacterioplankton is not yet understood. Based on recent findings in biogeochemistry, bacterial physiology, bacterial genetics, and ocean instrumentation, the microbial oceanography community is poised to make major advances in knowledge of this control point. This research project is ascertaining how the major taxa of bacterial DMSP degraders in seawater regulate DMSP transformations, and addresses the implications of bacterial functional, genetic, and taxonomic diversity for global sulfur cycling.
The project is founded on the globally important function of bacterial transformation of the ubiquitous organic sulfur compound DMSP in ocean surface waters. Recent genetic discoveries have identified key genes in the two major DMSP degradation pathways, and the stage is now set to identify the factors that regulate gene expression to favor one or the other pathway during DMSP processing. The taxonomy of the bacteria mediating DMSP cycling has been deduced from genomic and metagenomic sequencing surveys to include four major groups of surface ocean bacterioplankton. How regulation of DMSP degradation differs among these groups and maps to phylogeny in co-occurring members is key information for understanding the marine sulfur cycle and predicting its function in a changing ocean. Using model organism studies, microcosm experiments (at Dauphin Island Sea Lab, AL), and time-series field studies with an autonomous sample collection instrument (at Monterey Bay, CA), this project is taking a taxon-specific approach to decipher the regulation of bacterial DMSP degradation.
This research addresses fundamental questions of how the diversity of microbial life influences the geochemical environment of the oceans and atmosphere, linking the genetic basis of metabolic potential to taxonomic diversity. The project is training graduate students and post-doctoral scholars in microbial biodiversity and providing research opportunities and mentoring for undergraduate students. An outreach program is enhance understanding of the role and diversity of marine microorganisms in global elemental cycles among high school students. Advanced Placement Biology students are participating in marine microbial research that covers key learning goals in the AP Biology curriculum. Two high school students are selected each year for summer research internships in PI laboratories.";
String projects_0_end_date "2018-12";
String projects_0_name "Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere";
String projects_0_project_nid "541255";
String projects_0_start_date "2014-01";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Transcriptional profile of marine bacterium Ruegeria pomeroyi in a three-member co-culture study. This dataset contains the processed, QC'ed, normalized sequence data. The full raw data file is deposited in the NCBI BioProject database under accession PRJNA381627.";
String title "[Switch RNAseq] - Transcriptional profile of marine bacterium Ruegeria pomeroyi in a three-member co-culture study (Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere)";
String version "1";
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.
Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names,
followed by a collection of
constraints (e.g., variable<value),
each preceded by '&' (which is interpreted as "AND").
For details, see the tabledap Documentation.