http://lod.bco-dmo.org/id/dataset/812997
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2020-05-26
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Supplementary Table 4B: Annotations for contigs within transcriptome libraries for the eleven samples that were manually curated for selected metabolic processes
2020-06-22
publication
2020-06-22
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2020-07-09
publication
https://doi.org/10.26008/1912/bco-dmo.812997.1
Virginia P. Edgcomb
Woods Hole Oceanographic Institution
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Edgcomb, V. (2020) Supplementary Table 4B: Annotations for contigs within transcriptome libraries for the eleven samples that were manually curated for selected metabolic processes. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2020-06-22 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.812997.1 [access date]
Dataset Description: <p>Supplementary Table 4B: Metatranscriptome data summary for cellular activities presented and statistics on sequencing and removal of potential contaminant sequences: Annotations for contigs within transcriptome libraries for the eleven samples that were manually curated for selected metabolic processes. Samples&nbsp; taken on board of the R/V JOIDES Resolution between November 30, 2015 and January 30, 2016.</p> Methods and Sampling: <p>Frozen rock material was crushed as above, and then ground quickly into a fine powder using a precooled sterilized mortar and pestle, and then RNA extraction started immediately. The jaw crusher was cleaned and rinsed with 70% ethanol and RNaseZap™ RNase Decontamination Solution (Invitrogen, USA) between samples. About 40 g of material was extracted for each sample using the RNeasy PowerSoil Total RNA Isolation Kit (Qiagen, USA) according to the manufacturer’s protocol with the following modifications.</p>
<p>Each sample was evenly divided into 8 Bead Tubes (Qiagen, USA) and then 2.5 mL of Bead Solution were added into the Bead Tube followed by 0.25 mL of Solution SR1 and 0.8 mL of Solution SR2. Bead Tubes were frozen in liquid nitrogen and then thawed at 65°C in a water bath three times. RNA was purified using the MEGAclear Transcription Clean-up Kit (Ambion, USA) and concentrated with an overnight isopropanol precipitation at 4 °C. Trace amounts of contaminating DNA were removed from the RNA extracts using TURBO DNA free™ (Invitrogen, USA) as directed by the manufacturer.</p>
<p>To ensure DNA was removed thoroughly, each RNA extract was treated twice with TURBO DNase (Invitrogen, USA). A nested PCR reaction (2 x 35 cycles) using bacterial primers was used to confirm the absence of DNA in our RNA solutions. RNA was converted to cDNA using the Ovation® RNA-Seq System V2 kit (NuGEN, USA) according to the manufacturer’s protocol to preferentially prime non-rRNA sequences. The cDNA was purified with the MinElute Reaction Cleanup Kit (Qiagen, USA) and eluted into 20 μL elution buffer. Extracts were quantified using a Qubit Fluorometer (Life Technologies, USA) and cDNAs were stored at -80 °C until sequencing using 150 bp paired-end Illumina NextSeq 550.</p>
<p>To control for potential contaminants introduced during drilling, sample handling, and laboratory kit reagents, we sequenced a number of control samples as above. Two samples controlled for potential nucleic acid contamination; a “method” control to monitor possible contamination from our laboratory extractions, which included ~ 40 g sterilized glass beads processed through the entire protocol in place of rock, and a “kit” control to account for any signal coming from trace contaminants in kit reagents, which received no addition. In addition, 3 more controls were extracted: a sample of the drilling mud (Sepiolite), and two drilling seawater samples collected during the first and third weeks of drilling. cDNA obtained from these controls were sequenced together with the rock samples and co-assembled. Trimmomatic (v. 0.32) was used to trim adapter sequences (leading=20, trailing=20, sliding window=04:24, minlen=50). Paired reads were further quality checked and trimmed using FastQC (v. 0.11.7) and FASTX-toolkit (v. 0.014). Downstream analyses utilized paired reads. After co-assembling reads with Trinity (v. 2.4.0) from all controls (min length 150 bp), Bowtie2 (v. 2.3.4.1, 50) was used (with the parameter ‘un-conc’) to align all sample reads to this co-assembly. Reads that mapped to our control co-assembly allowing 1 mismatch were removed from further analysis (23.5-68.5% of sequences remained in sample data sets, see Supplementary Table 4).</p>
<p>Trinity (v. 2.4.0) was used for de novo assembly of the remaining reads in sample data sets (min. length 150 bp). Bowtie aligner was used to align reads to assembled contigs, RSEM was used to estimate the expression level of these reads, and TMM was used to perform cross sample normalization and to generate a TMM-normalized expression matrix. Within the Trinotate suite, TransDecoder (v. 3.0.1) was used to identify coding regions within contigs and functional and taxonomic annotation was made 622 by BLASTx and BLASTp against UniProt, Swissprot (release 2018_02) and RefSeq non-redundant protein sequence (nr) databases (e-value threshold of 1e-5). BLASTp was used to look for sequence homologies with the same e-values. HMMER (v. 3.1b2) was used to identify conserved domains by searching against the Pfam (v31.0) database. SignalP (v. 4.1) and TMHMM (2.0c) were used to predict signal peptides and transmembrane domains. RNAMMER (v.1.2) was used to identify rRNA homologies of archaea, bacteria and eukaryotes.</p>
<p>Because the Swissprot database does not have extensive representation of protein sequences from environmental samples, particularly deep-sea and deep biosphere samples, annotations of contigs utilized for analyses of selected processes were manually cross checked by BLASTx against GenBank nr database. Aside from removing any reads that mapped well to our control co-assembly (1 mismatch), as an extra precaution, any sequence that exhibited ≥ 95% sequence identity over ≥ 80% of the sequence length to suspected contaminants (e.g., human pathogens, plants, or taxa known to be common molecular kit reagent contaminants, and not described from the marine environment) as in Salter et al. and Glassing et al. were removed. This conservative approach potentially removed environmentally relevant data that were annotated to suspected contaminants due to poor taxonomic representation from environmental taxa in public databases, however it affords the highest possible confidence about any transcripts discussed.</p>
<p>Additional functional annotations of contigs were obtained by BLAST against the KEGG, COG, SEED, and MetaCyc databases using MetaPathways (v. 2.0) to gain insights into particular cellularprocesses, and to provide overviews of metabolic functions across samples based on comparisons of FPKM-normalized data. All annotations were integrated into a SQLite database for further analysis.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1658031 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1658031
completed
Virginia P. Edgcomb
Woods Hole Oceanographic Institution
508-289-3734
Department of Geology and Geophysics 220 McLean Lab, MS #8
Woods Hole
MA
02543
USA
vedgcomb@whoi.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Cycle
Biosynthetic_pathway
ID_2R1
ID_19R1
ID_26R2
ID_31R1
ID_42R2
ID_51R3
ID_62R1
ID_68R4
ID_71R1
ID_81R2
ID_84R6
Illumina NextSeq 550 platform
theme
None, User defined
No BCO-DMO term
featureType
BCO-DMO Standard Parameters
Automated DNA Sequencer
instrument
BCO-DMO Standard Instruments
IODP-360
service
Deployment Activity
SW Indian Ridge, Indian Ocean
place
Locations
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
International Ocean Discovery Program
http://www.iodp.org/index.php
International Ocean Discovery Program
The International Ocean Discovery Program (IODP) is an international marine research collaboration that explores Earth's history and dynamics using ocean-going research platforms to recover data recorded in seafloor sediments and rocks and to monitor subseafloor environments. IODP depends on facilities funded by three platform providers with financial contributions from five additional partner agencies. Together, these entities represent 26 nations whose scientists are selected to staff IODP research expeditions conducted throughout the world's oceans.
IODP expeditions are developed from hypothesis-driven science proposals aligned with the program's science plan Illuminating Earth's Past, Present, and Future. The science plan identifies 14 challenge questions in the four areas of climate change, deep life, planetary dynamics, and geohazards.
IODP's three platform providers include:
The U.S. National Science Foundation (NSF)
Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT)
The European Consortium for Ocean Research Drilling (ECORD)
More information on IODP, including the Science Plan and Policies/Procedures, can be found on their website at http://www.iodp.org/program-documents.
A summary table with links to IODP datasets currently hosted on Zenodo (https://zenodo.org/communities/iodp) can be accessed using the following link: https://iodp.tamu.edu/database/zenodo.html
IODP
largerWorkCitation
program
Collaborative Research: Delineating The Microbial Diversity and Cross-domain Interactions in The Uncharted Subseafloor Lower Crust Using Meta-omics and Culturing Approaches
https://osprey.bco-dmo.org/project/709556
Collaborative Research: Delineating The Microbial Diversity and Cross-domain Interactions in The Uncharted Subseafloor Lower Crust Using Meta-omics and Culturing Approaches
<p><strong>NSF abstract:</strong></p>
<p>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.</p>
<p>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.</p>
<p><strong>About the study area:</strong></p>
<p>The International Ocean Discovery Program (<a href="https://www.iodp.org/" target="_blank">IODP</a>) 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.</p>
Subseafloor Lower Crust Microbiology
largerWorkCitation
project
eng; USA
oceans
SW Indian Ridge, Indian Ocean
57.278183
57.278183
-32.70567
-32.70567
2015-11-30
2016-01-30
SW Indian Ridge, Indian Ocean
0
BCO-DMO catalogue of parameters from Supplementary Table 4B: Annotations for contigs within transcriptome libraries for the eleven samples that were manually curated for selected metabolic processes
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/813387.rdf
Name: Cycle
Units: unitless
Description: <p>Cycle of the biosynthetic pathway</p>
http://lod.bco-dmo.org/id/dataset-parameter/813388.rdf
Name: Biosynthetic_pathway
Units: unitless
Description: <p>Name of biosynthetic pathway</p>
http://lod.bco-dmo.org/id/dataset-parameter/813389.rdf
Name: ID_2R1
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 2R1</p>
http://lod.bco-dmo.org/id/dataset-parameter/813390.rdf
Name: ID_19R1
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 19R1</p>
http://lod.bco-dmo.org/id/dataset-parameter/813391.rdf
Name: ID_26R2
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 26R2</p>
http://lod.bco-dmo.org/id/dataset-parameter/813392.rdf
Name: ID_31R1
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 31R1</p>
http://lod.bco-dmo.org/id/dataset-parameter/813393.rdf
Name: ID_42R2
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 42R2</p>
http://lod.bco-dmo.org/id/dataset-parameter/813394.rdf
Name: ID_51R3
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 51R3</p>
http://lod.bco-dmo.org/id/dataset-parameter/813395.rdf
Name: ID_62R1
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 62R1</p>
http://lod.bco-dmo.org/id/dataset-parameter/813396.rdf
Name: ID_68R4
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 68R4</p>
http://lod.bco-dmo.org/id/dataset-parameter/813397.rdf
Name: ID_71R1
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 71R1</p>
http://lod.bco-dmo.org/id/dataset-parameter/813398.rdf
Name: ID_81R2
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 81R2</p>
http://lod.bco-dmo.org/id/dataset-parameter/813399.rdf
Name: ID_84R6
Units: unitless
Description: <p>Taxonomic annotations per pathway for sample 84R6</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
29920
https://darchive.mblwhoilibrary.org/bitstream/1912/25959/1/annotations.csv
download
https://doi.org/10.26008/1912/bco-dmo.812997.1
download
onLine
dataset
<p>Frozen rock material was crushed as above, and then ground quickly into a fine powder using a precooled sterilized mortar and pestle, and then RNA extraction started immediately. The jaw crusher was cleaned and rinsed with 70% ethanol and RNaseZap™ RNase Decontamination Solution (Invitrogen, USA) between samples. About 40 g of material was extracted for each sample using the RNeasy PowerSoil Total RNA Isolation Kit (Qiagen, USA) according to the manufacturer’s protocol with the following modifications.</p>
<p>Each sample was evenly divided into 8 Bead Tubes (Qiagen, USA) and then 2.5 mL of Bead Solution were added into the Bead Tube followed by 0.25 mL of Solution SR1 and 0.8 mL of Solution SR2. Bead Tubes were frozen in liquid nitrogen and then thawed at 65°C in a water bath three times. RNA was purified using the MEGAclear Transcription Clean-up Kit (Ambion, USA) and concentrated with an overnight isopropanol precipitation at 4 °C. Trace amounts of contaminating DNA were removed from the RNA extracts using TURBO DNA free™ (Invitrogen, USA) as directed by the manufacturer.</p>
<p>To ensure DNA was removed thoroughly, each RNA extract was treated twice with TURBO DNase (Invitrogen, USA). A nested PCR reaction (2 x 35 cycles) using bacterial primers was used to confirm the absence of DNA in our RNA solutions. RNA was converted to cDNA using the Ovation® RNA-Seq System V2 kit (NuGEN, USA) according to the manufacturer’s protocol to preferentially prime non-rRNA sequences. The cDNA was purified with the MinElute Reaction Cleanup Kit (Qiagen, USA) and eluted into 20 μL elution buffer. Extracts were quantified using a Qubit Fluorometer (Life Technologies, USA) and cDNAs were stored at -80 °C until sequencing using 150 bp paired-end Illumina NextSeq 550.</p>
<p>To control for potential contaminants introduced during drilling, sample handling, and laboratory kit reagents, we sequenced a number of control samples as above. Two samples controlled for potential nucleic acid contamination; a “method” control to monitor possible contamination from our laboratory extractions, which included ~ 40 g sterilized glass beads processed through the entire protocol in place of rock, and a “kit” control to account for any signal coming from trace contaminants in kit reagents, which received no addition. In addition, 3 more controls were extracted: a sample of the drilling mud (Sepiolite), and two drilling seawater samples collected during the first and third weeks of drilling. cDNA obtained from these controls were sequenced together with the rock samples and co-assembled. Trimmomatic (v. 0.32) was used to trim adapter sequences (leading=20, trailing=20, sliding window=04:24, minlen=50). Paired reads were further quality checked and trimmed using FastQC (v. 0.11.7) and FASTX-toolkit (v. 0.014). Downstream analyses utilized paired reads. After co-assembling reads with Trinity (v. 2.4.0) from all controls (min length 150 bp), Bowtie2 (v. 2.3.4.1, 50) was used (with the parameter ‘un-conc’) to align all sample reads to this co-assembly. Reads that mapped to our control co-assembly allowing 1 mismatch were removed from further analysis (23.5-68.5% of sequences remained in sample data sets, see Supplementary Table 4).</p>
<p>Trinity (v. 2.4.0) was used for de novo assembly of the remaining reads in sample data sets (min. length 150 bp). Bowtie aligner was used to align reads to assembled contigs, RSEM was used to estimate the expression level of these reads, and TMM was used to perform cross sample normalization and to generate a TMM-normalized expression matrix. Within the Trinotate suite, TransDecoder (v. 3.0.1) was used to identify coding regions within contigs and functional and taxonomic annotation was made 622 by BLASTx and BLASTp against UniProt, Swissprot (release 2018_02) and RefSeq non-redundant protein sequence (nr) databases (e-value threshold of 1e-5). BLASTp was used to look for sequence homologies with the same e-values. HMMER (v. 3.1b2) was used to identify conserved domains by searching against the Pfam (v31.0) database. SignalP (v. 4.1) and TMHMM (2.0c) were used to predict signal peptides and transmembrane domains. RNAMMER (v.1.2) was used to identify rRNA homologies of archaea, bacteria and eukaryotes.</p>
<p>Because the Swissprot database does not have extensive representation of protein sequences from environmental samples, particularly deep-sea and deep biosphere samples, annotations of contigs utilized for analyses of selected processes were manually cross checked by BLASTx against GenBank nr database. Aside from removing any reads that mapped well to our control co-assembly (1 mismatch), as an extra precaution, any sequence that exhibited ≥ 95% sequence identity over ≥ 80% of the sequence length to suspected contaminants (e.g., human pathogens, plants, or taxa known to be common molecular kit reagent contaminants, and not described from the marine environment) as in Salter et al. and Glassing et al. were removed. This conservative approach potentially removed environmentally relevant data that were annotated to suspected contaminants due to poor taxonomic representation from environmental taxa in public databases, however it affords the highest possible confidence about any transcripts discussed.</p>
<p>Additional functional annotations of contigs were obtained by BLAST against the KEGG, COG, SEED, and MetaCyc databases using MetaPathways (v. 2.0) to gain insights into particular cellularprocesses, and to provide overviews of metabolic functions across samples based on comparisons of FPKM-normalized data. All annotations were integrated into a SQLite database for further analysis.</p>
Specified by the Principal Investigator(s)
<p>BCO-DMO processing notes:</p>
<ul>
<li>Reformatted table structure</li>
<li>Adjusted column header names to comply with database requirements</li>
<li>Replaced , with ; in data table to comply with database requirements</li>
</ul>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Illumina NextSeq 550 platform
Illumina NextSeq 550 platform
PI Supplied Instrument Name: Illumina NextSeq 550 platform PI Supplied Instrument Description:RNA sequencing was performed using the Illumina NextSeq 550 platform (Univ. of Georgia). Instrument Name: Automated DNA Sequencer Instrument Short Name:Automated Sequencer Instrument Description: A DNA sequencer is an instrument that determines the order of deoxynucleotides in deoxyribonucleic acid sequences.
Cruise: IODP-360
IODP-360
R/V JOIDES Resolution
Community Standard Description
International Council for the Exploration of the Sea
R/V JOIDES Resolution
vessel
IODP-360
Henry J.B. Dick
Woods Hole Oceanographic Institution
http://publications.iodp.org/scientific_prospectus/360/index.html
Report describing IODP-360
R/V JOIDES Resolution
Community Standard Description
International Council for the Exploration of the Sea
R/V JOIDES Resolution
vessel