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Dataset Title:  16S rRNA gene (from RNA) from samples collected on cruise Chikyu-331 in the
Okinawa Trough, Japan from September to October 2010
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_781114)
Range: longitude = 126.90056 to 126.91194°E, latitude = 27.790277 to 27.791668°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Cruise_ID {
    String bcodmo_name "cruise_id";
    String description "Cruise ID number";
    String long_name "Cruise ID";
    String units "unitless";
  Sample_Name {
    String bcodmo_name "sample";
    String description "Sample name";
    String long_name "Sample Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 27.790278, 27.791667;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude; positive values = North";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range 126.900556, 126.911944;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude; positive values = East";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  Water_depth {
    Float32 _FillValue NaN;
    Float32 actual_range 1059.0, 1229.5;
    String bcodmo_name "depth_w";
    String description "Water depth";
    String long_name "Water Depth";
    String units "meters";
  Top_Depth {
    Float32 _FillValue NaN;
    Float32 actual_range 0.23, 63.72;
    String bcodmo_name "depth_bsf";
    String description "Top depth";
    String long_name "Top Depth";
    String units "meters below seafloor";
  Bottom_Depth {
    Float32 _FillValue NaN;
    Float32 actual_range 0.38, 63.633;
    String bcodmo_name "depth_bsf";
    String description "Bottom depth";
    String long_name "Bottom Depth";
    String units "meters below seafloor";
  Sediment_type {
    String bcodmo_name "sample_descrip";
    String description "Sediment type";
    String long_name "Sediment Type";
    String units "unitless";
  Estimated_Temp {
    Float32 _FillValue NaN;
    Float32 actual_range 5.0, 25.0;
    String bcodmo_name "temperature";
    String description "Estimated temperature; based on 3 degrees C/m";
    String long_name "Estimated Temp";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  Nucleic_Acid_amplified {
    String bcodmo_name "sample_descrip";
    String description "Type of nucleic acid amplified";
    String long_name "Nucleic Acid Amplified";
    String units "unitless";
  Primer_Set_16S_rRNA {
    String bcodmo_name "sample_descrip";
    String description "16S rRNA primer set";
    String long_name "Primer Set 16 S R RNA";
    String units "unitless";
  Illumina_dataset {
    String bcodmo_name "sample_descrip";
    String description "Illumina dataset ID";
    String long_name "Illumina Dataset";
    String units "unitless";
  Notes {
    Float64 _FillValue NaN;
    String bcodmo_name "comment";
    String description "Notes";
    String long_name "Notes";
    String units "unitless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Sampling of cores was done in accordance with IODP protocols.
All C0014 samples were cored on 16 September 2010 via via HPCS (hydraulic
piston coring system).  
 All C0015 samples were cored on 18 September 2010 via HPCS.  
 All C0017 samples were cored on 27 September 2010 via HPCS.
Core sections were kept frozen (-80\\u00b0C) until DNA extractions. RNA was
extracted using a phenol chloroform protocol. The RNA extract was DNAse
treated using the Invitrogen\\u2122 Ambion\\u2122 Turbo DNA-free Kit and
purified using the Qiagen\\u00ae RNeasy Mini Kit. A cDNA library was made using
the Qiagen \\u00ae QuantiTec Reverse Transcription Kit. Polymerase chain
reactions used the KAPABiosystems\\u00ae KAPA2G Robust HotStart ReadyMix PCR
Kit for 32 cycles.
Sequencing of the product was performed on the Illumina\\u00ae MiSeq 2500.";
    String awards_0_award_nid "554980";
    String awards_0_award_number "OCE-0939564";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0939564";
    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 
"16S rRNA gene (from RNA) 
  PI: Christopher House (PSU) 
  Version date: 05 November 2019";
    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 "2019-11-06T21:03:22Z";
    String date_modified "2019-11-22T18:50:06Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.781114.1";
    Float64 Easternmost_Easting 126.911944;
    Float64 geospatial_lat_max 27.791667;
    Float64 geospatial_lat_min 27.790278;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 126.911944;
    Float64 geospatial_lon_min 126.900556;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-07-23T12:25:36Z (local files)
2024-07-23T12:25:36Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_781114.das";
    String infoUrl "https://www.bco-dmo.org/dataset/781114";
    String institution "BCO-DMO";
    String instruments_0_acronym "Automated Sequencer";
    String instruments_0_dataset_instrument_nid "781193";
    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 "Illumina MiSeq 2500";
    String instruments_1_acronym "APC";
    String instruments_1_dataset_instrument_nid "782754";
    String instruments_1_description 
"The JOIDES Resolution's Advanced Piston Corer (APC) is used in soft ooze and sediments. The APC is a hydraulically actuated piston corer designed to recover relatively undisturbed samples from very soft to firm sediments.

More information is available from IODP (PDF).";
    String instruments_1_instrument_name "Advanced Piston Corer";
    String instruments_1_instrument_nid "628015";
    String instruments_1_supplied_name "hydraulic piston coring system (HPCS)";
    String keywords "acid, amplified, bco, bco-dmo, biological, bottom, Bottom_Depth, chemical, cruise, Cruise_ID, data, dataset, depth, dmo, erddap, estimated, Estimated_Temp, illumina, Illumina_dataset, latitude, longitude, management, name, notes, nucleic, Nucleic_Acid_amplified, oceanography, office, preliminary, primer, Primer_Set_16S_rRNA, rna, sample, Sample_Name, sediment, Sediment_type, set, temperature, top, Top_Depth, type, water, Water_depth";
    String license "https://www.bco-dmo.org/dataset/781114/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/781114";
    Float64 Northernmost_Northing 27.791667;
    String param_mapping "{'781114': {'Latitude': 'flag - latitude', 'Longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/781114/parameters";
    String people_0_affiliation "Pennsylvania State University";
    String people_0_affiliation_acronym "PSU";
    String people_0_person_name "Christopher House";
    String people_0_person_nid "714235";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Pennsylvania State University";
    String people_1_affiliation_acronym "PSU";
    String people_1_person_name "Leah Brandt";
    String people_1_person_nid "782699";
    String people_1_role "Scientist";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Subvent_Biosphere_Sediments";
    String projects_0_acronym "Subvent_Biosphere_Sediments";
    String projects_0_description 
"The Iheya North Hydrothermal Field in the Okinawa Backarc Basin represents an ideal environment in which to investigate the biotic temperature fringe of microbial life at depth because of its subsurface hydrothermal activity within its continental margin-type sediment profile. Geographically, the Okinawa Backarc Basin is situated along a continental margin, which is a sediment profile type commonly sampled and studied across the seafloor (e.g. Peru Margin, Costa Rica Margin, Cascadia Margin). The hydrothermal network within the subsurface here supplies an additional temperature obstacle to microbial life existing in the sediments. In particular, the sediment profile at Site C0014 exhibits a transition from hemipelagic ooze with pumiceous volcaniclastic sediments and low temperature (4°C) to a hydrothermally altered sequence of clays within the top ~10 mbsf of sediment. Temperature measurements indicate a gradient of approximately 3°C/m, which is roughly an order of magnitude greater than continental margin sites (e.g. Cascadia Margin, IODP 311 and Costa Rica Margin, IODP 344), but is more gradual than intense, centimeter-scale gradients from other hot, surface sediments. We have focused on the application of culture-independent, molecular methods to understand taxonomic and functional characteristics through this hydrothermal gradient. Confidence in DNA recovery suggests a microbial biosphere extent of approximately 15 mbsf (55°C).
Results from both 16S rRNA gene surveys and metagenomics analyses suggest a temperature-dependent stratigraphy of taxonomic and functional adaptations between the shallowest and deepest sample horizons. Cosmopolitan marine subsurface bacterial and archaeal taxa are present throughout the top 10 mbsf, whereas, hyperthermophilic heterotrophic as well as thermophilic anaerobic methanotrophic archaea appear in varying local abundances in deeper, hydrothermal clay horizons. \"An In-Depth analysis of the subvent biosphere within Okinawa Backarc Basin (IODP 331, Iheya North Hydrothermal Field) sediments\" encompasses datasets funded through C-DEBI to investigate the microbial communities in IODP 331 Iheya North Hydrothermal Field sediments. Site C0014 at this field site is 500 m away from the active vent and experiences a 3C/m temperature gradient with depth. In the research grant \"Investigating the active microbial populations in near hydrothermal vent sediments\" and the Research Exchange grant \"Learning new RNA extraction techniques\", we used an RNA-based approach to explore the active microbial community. Upon analysis, the RNA dataset does not appear to reflect the same information as the phylogenetic signals coming from both the 16S rRNA gene as well as the metagenomes. The data indicate significant background noise from the RNA extraction process rather than from an indigenous representation of the subsurface biosphere.
The graduate fellowship \"An in-depth analysis of the subvent biosphere within the Okinawa backarc basin Iheya North hydrothermal field\" provided an opportunity to bring together metagenomic, 16S rRNA gene amplicon (DNA), and 16S rRNA amplicon datasets from IODP 331 Iheya North Hydrothermal Field sediments to understand the biogeography of this subvent biosphere.
For more information, refer to the following C-DEBI grants/projects.
An in-depth analysis of the subvent biosphere within the Okinawa backarc basin Iheya North hydrothermal field:https://www.darkenergybiosphere.org/award/an-in-depth-analysis-of-the-subvent-biosphere-within-the-okinawa-backarc-basin-iheya-north-hydrothermal-field/
Investigating the active microbial populations in near hydrothermal vent sediments: https://www.darkenergybiosphere.org/award/investigating-the-active-microbial-populations-in-near-hydrothermal-vent-sediments/
Learn new RNA extraction techniques: https://www.darkenergybiosphere.org/award/learn-new-rna-extraction-techniques/";
    String projects_0_end_date "2016-05";
    String projects_0_geolocation "Iheya North Hydrothermal Field, Pacific Ocean";
    String projects_0_name "An In-Depth analysis of the subvent biosphere within Okinawa Backarc Basin (IODP 331, Iheya North Hydrothermal Field) sediments";
    String projects_0_project_nid "714230";
    String projects_0_start_date "2014-06";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 27.790278;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "Notes";
    String summary "RNA extractions were attempted from sediments at Sites C0014 and C0017 to selectively investigate the active microbial populations at these sites. This study was conducted to supplement the gene-based and metagenomic studies. However, the results from sequenced reverse transcribe 16S rRNA demonstrate the sensitivity of extraction and amplification to external nucleic acids and attest to the challenges in working with low biomass environmental samples. Inconsistencies between primersets and replicates make conclusions about the results of this RNA study extremely tenuous.";
    String title "16S rRNA gene (from RNA) from samples collected on cruise Chikyu-331 in the Okinawa Trough, Japan from September to October 2010";
    String version "1";
    Float64 Westernmost_Easting 126.900556;
    String xml_source "osprey2erddap.update_xml() v1.3";


Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

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
For example,
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.

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