Accessing BCO-DMO data
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BCO-DMO ERDDAP
Accessing BCO-DMO data |
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| Dataset Title: | [IODP360 - iTAG and metatranscriptome data] - Supplementary Table 4C: Statistics of reads retained through bioinformatic processing of iTAG data for the 11 samples and control samples and metatranscriptome data. (Collaborative Research: Delineating The Microbial Diversity and Cross-domain Interactions in The Uncharted Subseafloor Lower Crust Using Meta-omics and Culturing Approaches) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_813173) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
Sample_ID {
String bcodmo_name "sample";
String description "Sample ID";
String long_name "Sample ID";
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 -32.70567, -32.70567;
String axis "Y";
String bcodmo_name "unknown";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "Latitude of sample, south is negative";
String ioos_category "Location";
String long_name "Latitude";
String standard_name "latitude";
String units "degrees_north";
}
longitude {
String _CoordinateAxisType "Lon";
Float64 _FillValue NaN;
Float64 actual_range 57.278183, 57.278183;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "Longitude of samples, west is negative";
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";
}
depth {
String _CoordinateAxisType "Height";
String _CoordinateZisPositive "down";
Float64 _FillValue NaN;
Float64 actual_range 10.7, 747.7;
String axis "Z";
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "Depth - meters below seafloor (mbsf)";
String ioos_category "Location";
String long_name "Depth";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
String positive "down";
String standard_name "depth";
String units "m";
}
iTAG_Raw {
Int32 _FillValue 2147483647;
Int32 actual_range 29227, 810682;
String bcodmo_name "unknown";
String description "iTAG data - Raw reads";
String long_name "I TAG Raw";
String units "number of reads";
}
iTAG_Paired_QC {
Int32 _FillValue 2147483647;
Int32 actual_range 19196, 599653;
String bcodmo_name "unknown";
Float64 colorBarMaximum 150.0;
Float64 colorBarMinimum 0.0;
String description "iTAG data - paired reads after QC";
String long_name "I TAG Paired QC";
String units "number of reads";
}
iTAG_Paired_Contmnt_Rem {
Int32 _FillValue 2147483647;
Int32 actual_range 38, 39021;
String bcodmo_name "unknown";
String description "iTAG data - Paired reads surviving removal of potential contaminants matching sequences in control samples or known contaminants.";
String long_name "I TAG Paired Contmnt Rem";
String units "number of reads";
}
iTAG_OTU {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 8, 97;
String bcodmo_name "unknown";
String description "iTAG data - Number of OTUs at 99% identity";
String long_name "I TAG OTU";
String units "number of OTUs";
}
Metatr_Raw {
Int32 _FillValue 2147483647;
Int32 actual_range 13032452, 63348900;
String bcodmo_name "unknown";
String description "Metatranscriptome data - Raw reads from sequencing";
String long_name "Metatr Raw";
String units "number of reads";
}
Metatr_Paired_QC {
Int32 _FillValue 2147483647;
Int32 actual_range 5807873, 29212385;
String bcodmo_name "unknown";
Float64 colorBarMaximum 150.0;
Float64 colorBarMinimum 0.0;
String description "Metatranscriptome data - Paired reads after QC";
String long_name "Metatr Paired QC";
String units "number of reads";
}
Metatr_Paired_Contmnt_Rem {
Int32 _FillValue 2147483647;
Int32 actual_range 1724455, 16336790;
String bcodmo_name "unknown";
String description "Metatranscriptome data - Paired reads surviving removal of potential contaminants matching sequences in control samples or known contaminants.";
String long_name "Metatr Paired Contmnt Rem";
String units "number of reads";
}
Metatr_Reads_Remaining {
Float32 _FillValue NaN;
Float32 actual_range 0.2344, 0.6815;
String bcodmo_name "unknown";
String description "Metatranscriptome data - Percent of original paired reads remaining";
String long_name "Metatr Reads Remaining";
String units "percentage (%)";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
String acquisition_description
"Rock material was crushed while still frozen in a Progressive Exploration Jaw
Crusher (Model 150) whose surfaces were sterilized with 70% ethanol and RNase
AWAY (Thermo Fisher Scientific, USA) inside a laminar flow hood. Powdered rock
material was returned to the -80\\u00b0C freezer until extraction.
DNA was extracted from 20, 30, or 40 grams of powdered rock material,
depending on the quantity of rock available. A DNeasy PowerMax Soil Kit
(Qiagen, USA) was used following the manufacturer\\u2019s protocol modified to
included three freeze/thaw treatments prior to the addition of Soil Kit
solution C1. Each treatment consisted of 1 minute in liquid nitrogen followed
by 5 minutes at 65 \\u00b0C. DNA extracts were concentrated by isopropanol
precipitation overnight at 4\\u00b0C.
The low biomass in our samples required whole genome amplification (WGA) prior
to PCR amplification of marker genes. Genomic DNA was amplified by Multiple
Displacement Amplification (MDA) using the REPLI-g Single Cell Kit (Qiagen) as
directed. MDA bias was minimized by splitting each WGA sample into triplicate
16 \\u03bcL reactions after 1 hr of amplification and then resuming
amplification for the manufacturer-specified 7 hrs (8 hrs total).
DNA was also recovered from samples of drilling mud and drilling fluid
(surface water collected during the coring process) for negative controls, as
well as two \\u201ckit control\\u201d samples, in which no sample was added, to
account for any contaminants originating from either the DNeasy PowerMax Soil
Kit or the REPLI-g Single Cell Kit.
Bacterial SSU rRNA gene fragments were PCR amplified from MDA samples and
sequenced at Georgia Genomics and Bioinformatics Core (Univ. of Georgia). The
primers used were: Bac515-Y and Bac926R. Dual-indexed libraries were prepared
with (HT) iTruS (Kappa Biosystems) chemistry and sequencing was performed on
an Illumina MiSeq 2 x 300 bp system with all samples combined equally on a
single flow cell.
Raw sequence reads were processed through Trim Galore
[[http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/]](\\\\\"http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\\]\\\\\"),
FLASH (ccb.jhu.edu/software/FLASH/) and FASTX Toolkit
[[http://hannonlab.cshl.edu/fastx_toolkit/]](\\\\\"http://hannonlab.cshl.edu/fastx_toolkit/\\]\\\\\")
for trimming and removal of low quality/short reads.
Quality filtering included requiring a minimum average quality of 25 and
rejection of paired reads less than 250 nucleotides.
Operational Taxonomic Unit (OTU) clusters were constructed at 99% similarity
with the script pick_otus.py within the Quantitative Insights Into Microbial
Ecology (QIIME) v.1.9.1 software and \\u2018uclust\\u2019. Any OTU that matched
an OTU in one of our control samples (drilling fluids, drilling mud,
extraction and WGA controls) was removed (using filter_otus_from_otu_table.py)
along with any sequences of land plants and human pathogens that may have
survived the control filtering due to clustering at 99%
(filter_taxa_from_otu_table.py). As an additional quality control measure,
genera that are commonly identified as PCR contaminants were removed.
Unclassified OTUs were queried using BLAST against the GenBank nr database and
further information about these OTUs is provided in the Supplementary
Discussion text under the section \\u201cTaxonomic diversity information from
iTAGs.\\u201d OTUs that could not be assigned to Bacteria or Archaea were
removed from further analysis. For downstream analyses, any OTUs not
representing more than 0.01% of relative abundance of sequences overall were
removed as those are unlikely to contribute significantly to in situ
communities. The OTU data table was transformed to a presence/absence table
and the Jaccard method was used to generate a distance matrix using the
dist.binary() function in the R package ade4.";
String awards_0_award_nid "709555";
String awards_0_award_number "OCE-1658031";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1658031";
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
"Supplementary Table 4C: iTAG
PI: Virginia Edgcomb
Data Version 1: 2020-05-28";
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 dataset_current_state "Final and no updates";
String date_created "2020-05-28T12:54:12Z";
String date_modified "2020-07-09T16:05:24Z";
String defaultDataQuery "&time<now";
String doi "10.26008/1912/bco-dmo.813173.1";
Float64 Easternmost_Easting 57.278183;
Float64 geospatial_lat_max -32.70567;
Float64 geospatial_lat_min -32.70567;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max 57.278183;
Float64 geospatial_lon_min 57.278183;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 747.7;
Float64 geospatial_vertical_min 10.7;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-11-23T17:15:37Z (local files)
2024-11-23T17:15:37Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_813173.html";
String infoUrl "https://www.bco-dmo.org/dataset/813173";
String institution "BCO-DMO";
String instruments_0_acronym "Automated Sequencer";
String instruments_0_dataset_instrument_description "DNA sequencing performed using the Illumina MiSeq 2 x 300 bp platform (Univ. of Georgia)";
String instruments_0_dataset_instrument_nid "813183";
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 2 x 300 bp platform";
String keywords "bco, bco-dmo, biological, chemical, contmnt, data, dataset, depth, dmo, erddap, iTAG_OTU, iTAG_Paired_Contmnt_Rem, iTAG_Paired_QC, iTAG_Raw, latitude, longitude, management, metatr, Metatr_Paired_Contmnt_Rem, Metatr_Paired_QC, Metatr_Raw, Metatr_Reads_Remaining, oceanography, office, otu, paired, preliminary, raw, reads, rem, remaining, sample, Sample_ID, tag";
String license "https://www.bco-dmo.org/dataset/813173/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/813173";
Float64 Northernmost_Northing -32.70567;
String param_mapping "{'813173': {'Latitude': 'flag - latitude', 'Depth': 'flag - depth', 'Longitude': 'flag - longitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/813173/parameters";
String people_0_affiliation "Woods Hole Oceanographic Institution";
String people_0_affiliation_acronym "WHOI";
String people_0_person_name "Virginia P. Edgcomb";
String people_0_person_nid "51284";
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";
String people_1_person_name "Virginia P. Edgcomb";
String people_1_person_nid "51284";
String people_1_role "Contact";
String people_1_role_type "related";
String people_2_affiliation "Woods Hole Oceanographic Institution";
String people_2_affiliation_acronym "WHOI BCO-DMO";
String people_2_person_name "Karen Soenen";
String people_2_person_nid "748773";
String people_2_role "BCO-DMO Data Manager";
String people_2_role_type "related";
String project "Subseafloor Lower Crust Microbiology";
String projects_0_acronym "Subseafloor Lower Crust Microbiology";
String projects_0_description
"NSF abstract:
The lower ocean crust has remained largely unexplored and represents one of the last frontiers for biological exploration on Earth. Preliminary data indicate an active subsurface biosphere in samples of the lower oceanic crust collected from Atlantis Bank in the SW Indian Ocean as deep as 790 m below the seafloor. Even if life exists in only a fraction of the habitable volume where temperatures permit and fluid flow can deliver carbon and energy sources, an active lower oceanic crust biosphere would have implications for deep carbon budgets and yield insights into microbiota that may have existed on early Earth. This is all of great interest to other research disciplines, educators, and students alike. A K-12 education program will capitalize on groundwork laid by outreach collaborator, A. Martinez, a 7th grade teacher in Eagle Pass, TX, who sailed as outreach expert on Drilling Expedition 360. Martinez works at a Title 1 school with ~98% Hispanic and ~2% Native American students and a high number of English Language Learners and migrants. Annual school visits occur during which the project investigators present hands on-activities introducing students to microbiology, and talks on marine microbiology, the project, and how to pursue science related careers. In addition, monthly Skype meetings with students and PIs update them on project progress. Students travel to the University of Texas Marine Science Institute annually, where they get a campus tour and a 3-hour cruise on the R/V Katy, during which they learn about and help with different oceanographic sampling approaches. The project partially supports two graduate students, a Woods Hole undergraduate summer student, the participation of multiple Texas A+M undergraduate students, and 3 principal investigators at two institutions, including one early career researcher who has not previously received NSF support of his own.
Given the dearth of knowledge of the lower oceanic crust, this project is poised to transform our understanding of life in this vast environment. The project assesses metabolic functions within all three domains of life in this crustal biosphere, with a focus on nutrient cycling and evaluation of connections to other deep marine microbial habitats. The lower ocean crust represents a potentially vast biosphere whose microbial constituents and the biogeochemical cycles they mediate are likely linked to deep ocean processes through faulting and subsurface fluid flow. Atlantis Bank represents a tectonic window that exposes lower oceanic crust directly at the seafloor. This enables seafloor drilling and research on an environment that can transform our understanding of connections between the deep subseafloor biosphere and the rest of the ocean. Preliminary analysis of recovered rocks from Expedition 360 suggests the interaction of seawater with the lower oceanic crust creates varied geochemical conditions capable of supporting diverse microbial life by providing nutrients and chemical energy. This project is the first interdisciplinary investigation of the microbiology of all 3 domains of life in basement samples that combines diversity and \"meta-omics\" analyses, analysis of nutrient addition experiments, high-throughput culturing and physiological analyses of isolates, including evaluation of their ability to utilize specific carbon sources, Raman spectroscopy, and lipid biomarker analyses. Comparative genomics are used to compare genes and pathways relevant to carbon cycling in these samples to data from published studies of other deep-sea environments. The collected samples present a rare and time-sensitive opportunity to gain detailed insights into microbial life, available carbon and energy sources for this life, and of dispersal of microbiota and connections in biogeochemical processes between the lower oceanic crust and the overlying aphotic water column.
About the study area:
The International Ocean Discovery Program (IODP) Expedition 360 explored the lower crust at Atlantis Bank, a 12 Ma oceanic core complex on the ultraslow-spreading SW Indian Ridge. This oceanic core complex represents a tectonic window that exposes lower oceanic crust and mantle directly at the seafloor, and the expedition provided an unprecedented opportunity to access this habitat in the Indian Ocean.";
String projects_0_end_date "2020-01";
String projects_0_geolocation "SW Indian Ridge, Indian Ocean";
String projects_0_name "Collaborative Research: Delineating The Microbial Diversity and Cross-domain Interactions in The Uncharted Subseafloor Lower Crust Using Meta-omics and Culturing Approaches";
String projects_0_project_nid "709556";
String projects_0_start_date "2017-02";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing -32.70567;
String standard_name_vocabulary "CF Standard Name Table v55";
String subsetVariables "latitude,longitude";
String summary "Supplementary Table 4C: Metatranscriptome data summary for cellular activities presented and statistics on sequencing and removal of potential contaminant sequences: Statistics of reads retained through bioinformatic processing of iTAG data for the 11 samples and control samples and metatranscriptome data. Samples taken on board of the R/V JOIDES Resolution between November 30, 2015 and January 30, 2016";
String title "[IODP360 - iTAG and metatranscriptome data] - Supplementary Table 4C: Statistics of reads retained through bioinformatic processing of iTAG data for the 11 samples and control samples and metatranscriptome data. (Collaborative Research: Delineating The Microbial Diversity and Cross-domain Interactions in The Uncharted Subseafloor Lower Crust Using Meta-omics and Culturing Approaches)";
String version "1";
Float64 Westernmost_Easting 57.278183;
String xml_source "osprey2erddap.update_xml() v1.5";
}
}
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.