http://lod.bco-dmo.org/id/dataset/719970
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
2017-11-27
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Transcriptional profile of marine bacterium Ruegeria pomeroyi in a three-member co-culture study
2017-11-29
publication
2017-11-29
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2020-01-14
publication
https://doi.org/10.1575/1912/bco-dmo.719970.1
Mary Ann Moran
University of Georgia
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: Moran, M. A. (2017) Transcriptional profile of marine bacterium Ruegeria pomeroyi in a three-member co-culture study. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2017-11-29 [if applicable, indicate subset used]. doi:10.1575/1912/bco-dmo.719970.1 [access date]
Transcriptional profile of marine bacterium Ruegeria pomeroyi in a three-member co-culture study Dataset Description: <p>Transcriptional profile of marine bacterium <em>Ruegeria pomeroyi</em> 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.</p>
<p>These data are published in table 2 of Landa et al., 2017, ISME Journal, in press.</p> Methods and Sampling: <p>Published methodology in Landa et al., 2017, ISME Journal, in press.</p>
<p>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 <em>R. pomeroyi</em>. Samples were depleted of rRNA using custom probes for small and large subunit rRNA genes from all three microbes (Stewart et al., 2010)<em>.</em> 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).</p>
<p><strong>Reference cited:</strong><br />
Stewart FJ, Ottesen EA, DeLong EF. (2010). Development and quantitative analyses of a universal rRNA-subtraction protocol for microbial metatranscriptomics. ISME J 4: 896–907. doi:<a href="http://dx.doi.org/10.1038/ismej.2010.18" target="_blank">10.1038/ismej.2010.18</a></p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1342694 Award URL: http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1342694
completed
Mary Ann Moran
University of Georgia
706-542-6481
Department of Marine Sciences
Athens
GA
30602
USA
mmoran@uga.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Locus_Tag
Description
Day7_R1
Day7_R2
Day9_R1
Day9_R2
Day12_R1
Day12_R2
Day15_R1
Day15_R2
Day18_R1
Day18_R2
Day23_R1
Day23_R2
Day30_R1
Day30_R2
Day37_R1
Day37_R2
HiSeq Illumina 2500
theme
None, User defined
sample identification
brief description
count
featureType
BCO-DMO Standard Parameters
Automated DNA Sequencer
instrument
BCO-DMO Standard Instruments
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.
Dimensions of Biodiversity
http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503446
Dimensions of Biodiversity
(adapted from the NSF Synopsis of Program)
Dimensions of Biodiversity is a program solicitation from the NSF Directorate for Biological Sciences. FY 2010 was year one of the program. [MORE from NSF]
The NSF Dimensions of Biodiversity program seeks to characterize biodiversity on Earth by using integrative, innovative approaches to fill rapidly the most substantial gaps in our understanding. The program will take a broad view of biodiversity, and in its initial phase will focus on the integration of genetic, taxonomic, and functional dimensions of biodiversity. Project investigators are encouraged to integrate these three dimensions to understand the interactions and feedbacks among them. While this focus complements several core NSF programs, it differs by requiring that multiple dimensions of biodiversity be addressed simultaneously, to understand the roles of biodiversity in critical ecological and evolutionary processes.
Dimensions of Biodiversity
largerWorkCitation
program
Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere
https://www.bco-dmo.org/project/541255
Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere
<p>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.</p>
<p>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.</p>
<p>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.</p>
OceanSulfurFluxBact
largerWorkCitation
project
eng; USA
biota
oceans
2017-11-29
0
BCO-DMO catalogue of parameters from Transcriptional profile of marine bacterium Ruegeria pomeroyi in a three-member co-culture study
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/720149.rdf
Name: Locus_Tag
Units: unitless
Description: gene identifier
http://lod.bco-dmo.org/id/dataset-parameter/720150.rdf
Name: Description
Units: unitless
Description: gene function, if known
http://lod.bco-dmo.org/id/dataset-parameter/720151.rdf
Name: Day7_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 7, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720152.rdf
Name: Day7_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 7, replicate 2
http://lod.bco-dmo.org/id/dataset-parameter/720153.rdf
Name: Day9_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 9, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720154.rdf
Name: Day9_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 9, replicate 2
http://lod.bco-dmo.org/id/dataset-parameter/720155.rdf
Name: Day12_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 12, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720156.rdf
Name: Day12_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 12, replicate 2
http://lod.bco-dmo.org/id/dataset-parameter/720157.rdf
Name: Day15_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 15, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720158.rdf
Name: Day15_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 15, replicate 2
http://lod.bco-dmo.org/id/dataset-parameter/720159.rdf
Name: Day18_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 18, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720160.rdf
Name: Day18_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 18, replicate 2
http://lod.bco-dmo.org/id/dataset-parameter/720161.rdf
Name: Day23_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 23, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720162.rdf
Name: Day23_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 23, replicate 2
http://lod.bco-dmo.org/id/dataset-parameter/720163.rdf
Name: Day30_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 30, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720164.rdf
Name: Day30_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 30, replicate 2
http://lod.bco-dmo.org/id/dataset-parameter/720165.rdf
Name: Day37_R1
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 37, replicate 1
http://lod.bco-dmo.org/id/dataset-parameter/720166.rdf
Name: Day37_R2
Units: TPM (transcripts per million)
Description: Transcript count by day and replicate: day 37, replicate 2
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
654335
https://darchive.mblwhoilibrary.org/bitstream/1912/25145/1/dataset-719970_switch-rnaseq__v1.tsv
download
https://doi.org/10.1575/1912/bco-dmo.719970.1
download
onLine
dataset
<p>Published methodology in Landa et al., 2017, ISME Journal, in press.</p>
<p>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 <em>R. pomeroyi</em>. Samples were depleted of rRNA using custom probes for small and large subunit rRNA genes from all three microbes (Stewart et al., 2010)<em>.</em> 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).</p>
<p><strong>Reference cited:</strong><br />
Stewart FJ, Ottesen EA, DeLong EF. (2010). Development and quantitative analyses of a universal rRNA-subtraction protocol for microbial metatranscriptomics. ISME J 4: 896–907. doi:<a href="http://dx.doi.org/10.1038/ismej.2010.18" target="_blank">10.1038/ismej.2010.18</a></p>
Specified by the Principal Investigator(s)
<p>Sequence quality control was performed using the FASTX toolkit, imposing a minimum quality score of 20 over 80% of read length. Reads aligning to an in-house rRNA database were removed (blastn, score cutoff&nbsp;greater than or equal to 50). Remaining reads were mapped to the <em>R. pomeroyi</em> genome (Bowtie 2; Langmead and Salzberg, 2012) and counted (HTSeq; Anders et al., 2015). Counts were converted to transcripts per million (TPM, Table S2) and data were also deposited in the NCBI BioProject database under accession PRJNA381627.&nbsp;Genes with differential expression between selected time points were determined with DESeq2 (Love et al., 2014), and linear relationships of gene expression with phytoplankton abundance with Pearson correlations.</p>
<p><strong>References cited:</strong><br />
Langmead B, Salzberg SL. (2012). Fast gapped-read alignment with Bowtie 2. Nat Methods 9: 357–359. doi:<a href="http://dx.doi.org/10.1038/nmeth.1923" target="_blank">10.1038/nmeth.1923</a></p>
<p>Anders S, Pyl PT, Huber W. (2015). HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166–169. doi:<a href="http://dx.doi.org/10.1093/bioinformatics/btu638" target="_blank">10.1093/bioinformatics/btu638</a></p>
<p>Love MI, Huber W, Anders S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550. doi:<a href="http://dx.doi.org/10.1186/s13059-014-0550-8" target="_blank">10.1186/s13059-014-0550-8</a></p>
<p><strong>BCO-DMO Processing:</strong><br />
- modified parameter names to conform with BCO-DMO naming conventions;<br />
- replaced spaces with underscores in Description column.</p>
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
HiSeq Illumina 2500
HiSeq Illumina 2500
PI Supplied Instrument Name: HiSeq Illumina 2500 PI Supplied Instrument Description:Transcripts were sequenced on a HiSeq Illumina 2500 at the Hudson Alpha Institute for Biotechnology (AL, USA). Instrument Name: Automated DNA Sequencer Instrument Short Name:Automated Sequencer Instrument 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.