BCO-DMO ERDDAP
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Row Type Variable Name Attribute Name Data Type Value
attribute NC_GLOBAL access_formats String .htmlTable,.csv,.json,.mat,.nc,.tsv
attribute NC_GLOBAL acquisition_description String Frozen rock material was crushed as above, and then ground quickly into a fine\npowder using a precooled sterilized mortar and pestle, and then RNA extraction\nstarted immediately. The jaw crusher was cleaned and rinsed with 70% ethanol\nand RNaseZap\\u2122 RNase Decontamination Solution (Invitrogen, USA) between\nsamples. About 40 g of material was extracted for each sample using the RNeasy\nPowerSoil Total RNA Isolation Kit (Qiagen, USA) according to the\nmanufacturer\\u2019s protocol with the following modifications.\n \nEach sample was evenly divided into 8 Bead Tubes (Qiagen, USA) and then 2.5 mL\nof Bead Solution were added into the Bead Tube followed by 0.25 mL of Solution\nSR1 and 0.8 mL of Solution SR2. Bead Tubes were frozen in liquid nitrogen and\nthen thawed at 65\\u00b0C in a water bath three times. RNA was purified using\nthe MEGAclear Transcription Clean-up Kit (Ambion, USA) and concentrated with\nan overnight isopropanol precipitation at 4 \\u00b0C. Trace amounts of\ncontaminating DNA were removed from the RNA extracts using TURBO DNA\nfree\\u2122 (Invitrogen, USA) as directed by the manufacturer. To ensure DNA\nwas removed thoroughly, each RNA extract was treated twice with TURBO DNase\n(Invitrogen, USA). A nested PCR reaction (2 x 35 cycles) using bacterial\nprimers was used to confirm the absence of DNA in our RNA solutions. RNA was\nconverted to cDNA using the Ovation\\u00ae RNA-Seq System V2 kit (NuGEN, USA)\naccording to the manufacturer\\u2019s protocol to preferentially prime non-rRNA\nsequences.\n \nThe cDNA was purified with the MinElute Reaction Cleanup Kit (Qiagen, USA) and\neluted into 20 \\u03bcL elution buffer. Extracts were quantified using a Qubit\nFluorometer (Life Technologies, USA) and cDNAs were stored at -80 \\u00b0C\nuntil sequencing using 150 bp paired-end Illumina NextSeq 550.\n \nTo control for potential contaminants introduced during drilling, sample\nhandling, and laboratory kit reagents, we sequenced a number of control\nsamples as above. Two samples controlled for potential nucleic acid\ncontamination; a \\u201cmethod\\u201d control to monitor possible contamination\nfrom our laboratory extractions, which included ~ 40 g sterilized glass beads\nprocessed through the entire protocol in place of rock, and a \\u201ckit\\u201d\ncontrol to account for any signal coming from trace contaminants in kit\nreagents, which received no addition. In addition, 3 more controls were\nextracted: a sample of the drilling mud (Sepiolite), and two drilling seawater\nsamples collected during the first and third weeks of drilling. cDNA obtained\nfrom these controls were sequenced together with the rock samples and co-\nassembled. Trimmomatic (v. 0.32) was used to trim adapter sequences\n(leading=20, trailing=20, sliding window=04:24, minlen=50).\n \nPaired reads were further quality checked and trimmed using FastQC (v. 0.11.7)\nand FASTX-toolkit (v. 0.014). Downstream analyses utilized paired reads. After\nco-assembling reads with Trinity (v. 2.4.0) from all controls (min length 150\nbp), Bowtie2 (v. 2.3.4.1, 50) was used (with the parameter \\u2018un-\nconc\\u2019) to align all sample reads to this co-assembly. Reads that mapped\nto our control co-assembly allowing 1 mismatch were removed from further\nanalysis (23.5-68.5% of sequences remained in sample data sets, see\nSupplementary Table 4). Trinity (v. 2.4.0) was used for de novo assembly of\nthe remaining reads in sample data sets (min. length 150 bp). Bowtie aligner\nwas used to align reads to assembled contigs, RSEM was used to estimate the\nexpression level of these reads, and TMM was used to perform cross sample\nnormalization and to generate a TMM-normalized expression matrix. Within the\nTrinotate suite, TransDecoder (v. 3.0.1) was used to identify coding regions\nwithin contigs and functional and taxonomic annotation was made 622 by BLASTx\nand BLASTp against UniProt, Swissprot (release 2018_02) and RefSeq non-\nredundant protein sequence (nr) databases (e-value threshold of 1e-5). BLASTp\nwas used to look for sequence homologies with the same e-values. HMMER (v.\n3.1b2) was used to identify conserved domains by searching against the Pfam\n(v31.0) database. SignalP (v. 4.1) and TMHMM (2.0c) were used to predict\nsignal peptides and transmembrane domains. RNAMMER (v.1.2) was used to\nidentify rRNA homologies of archaea, bacteria and eukaryotes.\n \nBecause the Swissprot database does not have extensive representation of\nprotein sequences from environmental samples, particularly deep-sea and deep\nbiosphere samples, annotations of contigs utilized for analyses of selected\nprocesses were manually cross checked by BLASTx against GenBank nr database.\nAside from removing any reads that mapped well to our control co-assembly (1\nmismatch), as an extra precaution, any sequence that exhibited \\u2265 95%\nsequence identity over \\u2265 80% of the sequence length to suspected\ncontaminants (e.g., human pathogens, plants, or taxa known to be common\nmolecular kit reagent contaminants, and not described from the marine\nenvironment) as in Salter et al. and Glassing et al. were removed.\n \nThis conservative approach potentially removed environmentally relevant data\nthat were annotated to suspected contaminants due to poor taxonomic\nrepresentation from environmental taxa in public databases, however it affords\nthe highest possible confidence about any transcripts discussed. Additional\nfunctional annotations of contigs were obtained by BLAST against the KEGG,\nCOG, SEED, and MetaCyc databases using MetaPathways (v. 2.0) to gain insights\ninto particular cellularprocesses, and to provide overviews of metabolic\nfunctions across samples based on comparisons of FPKM-normalized data. All\nannotations were integrated into a SQLite database for further analysis.
attribute NC_GLOBAL awards_0_award_nid String 709555
attribute NC_GLOBAL awards_0_award_number String OCE-1658031
attribute NC_GLOBAL awards_0_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1658031 (external link)
attribute NC_GLOBAL awards_0_funder_name String NSF Division of Ocean Sciences
attribute NC_GLOBAL awards_0_funding_acronym String NSF OCE
attribute NC_GLOBAL awards_0_funding_source_nid String 355
attribute NC_GLOBAL awards_0_program_manager String David L. Garrison
attribute NC_GLOBAL awards_0_program_manager_nid String 50534
attribute NC_GLOBAL cdm_data_type String Other
attribute NC_GLOBAL Conventions String COARDS, CF-1.6, ACDD-1.3
attribute NC_GLOBAL creator_email String info at bco-dmo.org
attribute NC_GLOBAL creator_name String BCO-DMO
attribute NC_GLOBAL creator_type String institution
attribute NC_GLOBAL creator_url String https://www.bco-dmo.org/ (external link)
attribute NC_GLOBAL data_source String extract_data_as_tsv version 2.3  19 Dec 2019
attribute NC_GLOBAL dataset_current_state String Final and no updates
attribute NC_GLOBAL date_created String 2020-05-26T20:31:21Z
attribute NC_GLOBAL date_modified String 2020-07-08T20:46:44Z
attribute NC_GLOBAL defaultDataQuery String &time<now
attribute NC_GLOBAL infoUrl String https://www.bco-dmo.org/dataset/812936 (external link)
attribute NC_GLOBAL institution String BCO-DMO
attribute NC_GLOBAL instruments_0_acronym String Automated Sequencer
attribute NC_GLOBAL instruments_0_dataset_instrument_description String RNA sequencing was performed using the Illumina NextSeq 550 platform (Univ. of Georgia).v
attribute NC_GLOBAL instruments_0_dataset_instrument_nid String 813310
attribute NC_GLOBAL instruments_0_description String 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.
attribute NC_GLOBAL instruments_0_instrument_name String Automated DNA Sequencer
attribute NC_GLOBAL instruments_0_instrument_nid String 649
attribute NC_GLOBAL instruments_0_supplied_name String Illumina NextSeq 550 platform
attribute NC_GLOBAL keywords String bco, bco-dmo, biological, biosynthetic, Biosynthetic_pathway, chemical, cycle, data, dataset, dmo, erddap, ID_19R1, ID_26R2, ID_2R1, ID_31R1, ID_42R2, ID_51R3, ID_62R1, ID_68R4, ID_71R1, ID_81R2, ID_84R6, management, oceanography, office, pathway, preliminary
attribute NC_GLOBAL license String https://www.bco-dmo.org/dataset/812936/license (external link)
attribute NC_GLOBAL metadata_source String https://www.bco-dmo.org/api/dataset/812936 (external link)
attribute NC_GLOBAL param_mapping String {'812936': {}}
attribute NC_GLOBAL parameter_source String https://www.bco-dmo.org/mapserver/dataset/812936/parameters (external link)
attribute NC_GLOBAL people_0_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_0_affiliation_acronym String WHOI
attribute NC_GLOBAL people_0_person_name String Virginia P. Edgcomb
attribute NC_GLOBAL people_0_person_nid String 51284
attribute NC_GLOBAL people_0_role String Principal Investigator
attribute NC_GLOBAL people_0_role_type String originator
attribute NC_GLOBAL people_1_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_1_affiliation_acronym String WHOI
attribute NC_GLOBAL people_1_person_name String Virginia P. Edgcomb
attribute NC_GLOBAL people_1_person_nid String 51284
attribute NC_GLOBAL people_1_role String Contact
attribute NC_GLOBAL people_1_role_type String related
attribute NC_GLOBAL people_2_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_2_affiliation_acronym String WHOI BCO-DMO
attribute NC_GLOBAL people_2_person_name String Karen Soenen
attribute NC_GLOBAL people_2_person_nid String 748773
attribute NC_GLOBAL people_2_role String BCO-DMO Data Manager
attribute NC_GLOBAL people_2_role_type String related
attribute NC_GLOBAL project String Subseafloor Lower Crust Microbiology
attribute NC_GLOBAL projects_0_acronym String Subseafloor Lower Crust Microbiology
attribute NC_GLOBAL projects_0_description String NSF abstract:\nThe 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.\nGiven 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.\nAbout the study area:\nThe 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.
attribute NC_GLOBAL projects_0_end_date String 2020-01
attribute NC_GLOBAL projects_0_geolocation String SW Indian Ridge, Indian Ocean
attribute NC_GLOBAL projects_0_name String Collaborative Research: Delineating The Microbial Diversity and Cross-domain Interactions in The Uncharted Subseafloor Lower Crust Using Meta-omics and Culturing Approaches
attribute NC_GLOBAL projects_0_project_nid String 709556
attribute NC_GLOBAL projects_0_start_date String 2017-02
attribute NC_GLOBAL publisher_name String Biological and Chemical Oceanographic Data Management Office (BCO-DMO)
attribute NC_GLOBAL publisher_type String institution
attribute NC_GLOBAL sourceUrl String (local files)
attribute NC_GLOBAL standard_name_vocabulary String CF Standard Name Table v55
attribute NC_GLOBAL summary String Supplementary Table 4A: Metatranscriptome data summary for cellular activities presented and statistics on sequencing and removal of potential contaminant sequences: FPKM values. Samples  taken on board of the R/V JOIDES Resolution between November 30, 2015 and January 30, 2016.
attribute NC_GLOBAL title String [IODP360 - FPKM values] - Supplementary Table 4A: Metatranscriptome data summary for cellular activities presented and statistics on sequencing and removal of potential contaminant sequences, FPKM values (Collaborative Research: Delineating The Microbial Diversity and Cross-domain Interactions in The Uncharted Subseafloor Lower Crust Using Meta-omics and Culturing Approaches)
attribute NC_GLOBAL version String 1
attribute NC_GLOBAL xml_source String osprey2erddap.update_xml() v1.5
variable Cycle String
attribute Cycle bcodmo_name String unknown
attribute Cycle description String Cycle of the biosynthetic pathway
attribute Cycle long_name String Cycle
attribute Cycle units String unitless
variable Biosynthetic_pathway String
attribute Biosynthetic_pathway bcodmo_name String unknown
attribute Biosynthetic_pathway description String Name of biosynthetic pathway
attribute Biosynthetic_pathway long_name String Biosynthetic Pathway
attribute Biosynthetic_pathway units String unitless
variable ID_2R1 float
attribute ID_2R1 _FillValue float NaN
attribute ID_2R1 actual_range float 0.0, 540.183
attribute ID_2R1 bcodmo_name String unknown
attribute ID_2R1 description String FPKM values per pathway for sample 2R1
attribute ID_2R1 long_name String ID 2 R1
attribute ID_2R1 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_19R1 float
attribute ID_19R1 _FillValue float NaN
attribute ID_19R1 actual_range float 0.0, 86.455
attribute ID_19R1 bcodmo_name String unknown
attribute ID_19R1 description String FPKM values per pathway for sample 19R1
attribute ID_19R1 long_name String ID 19 R1
attribute ID_19R1 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_26R2 float
attribute ID_26R2 _FillValue float NaN
attribute ID_26R2 actual_range float 0.0, 968.764
attribute ID_26R2 bcodmo_name String unknown
attribute ID_26R2 description String FPKM values per pathway for sample 26R2
attribute ID_26R2 long_name String ID 26 R2
attribute ID_26R2 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_31R1 float
attribute ID_31R1 _FillValue float NaN
attribute ID_31R1 actual_range float 0.0, 256.836
attribute ID_31R1 bcodmo_name String unknown
attribute ID_31R1 description String FPKM values per pathway for sample 31R1
attribute ID_31R1 long_name String ID 31 R1
attribute ID_31R1 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_42R2 float
attribute ID_42R2 _FillValue float NaN
attribute ID_42R2 actual_range float 0.0, 1003.3
attribute ID_42R2 bcodmo_name String unknown
attribute ID_42R2 description String FPKM values per pathway for sample 42R2
attribute ID_42R2 long_name String ID 42 R2
attribute ID_42R2 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_51R3 float
attribute ID_51R3 _FillValue float NaN
attribute ID_51R3 actual_range float 0.0, 3001.126
attribute ID_51R3 bcodmo_name String unknown
attribute ID_51R3 description String FPKM values per pathway for sample 51R3
attribute ID_51R3 long_name String ID 51 R3
attribute ID_51R3 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_62R1 float
attribute ID_62R1 _FillValue float NaN
attribute ID_62R1 actual_range float 0.0, 2625.771
attribute ID_62R1 bcodmo_name String unknown
attribute ID_62R1 description String FPKM values per pathway for sample 62R1
attribute ID_62R1 long_name String ID 62 R1
attribute ID_62R1 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_68R4 float
attribute ID_68R4 _FillValue float NaN
attribute ID_68R4 actual_range float 0.0, 1097.931
attribute ID_68R4 bcodmo_name String unknown
attribute ID_68R4 description String FPKM values per pathway for sample 68R4
attribute ID_68R4 long_name String ID 68 R4
attribute ID_68R4 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_71R1 float
attribute ID_71R1 _FillValue float NaN
attribute ID_71R1 actual_range float 0.0, 500.262
attribute ID_71R1 bcodmo_name String unknown
attribute ID_71R1 description String FPKM values per pathway for sample 71R1
attribute ID_71R1 long_name String ID 71 R1
attribute ID_71R1 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_81R2 float
attribute ID_81R2 _FillValue float NaN
attribute ID_81R2 actual_range float 0.0, 163524.0
attribute ID_81R2 bcodmo_name String unknown
attribute ID_81R2 description String FPKM values per pathway for sample 81R2
attribute ID_81R2 long_name String ID 81 R2
attribute ID_81R2 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)
variable ID_84R6 float
attribute ID_84R6 _FillValue float NaN
attribute ID_84R6 actual_range float 0.0, 352.436
attribute ID_84R6 bcodmo_name String unknown
attribute ID_84R6 description String FPKM values per pathway for sample 84R6
attribute ID_84R6 long_name String ID 84 R6
attribute ID_84R6 units String Fragments per Kilobase of transcript per Million mapped reads (FPKM)

 
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