http://lod.bco-dmo.org/id/dataset/747872
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
2018-10-11
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
NCBI accessions of the harmful alga Heterosigma akashiwo (CCMP2393) grown under a range of CO2 concentrations from 200-1000 ppm
2018-10-11
publication
2018-10-11
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2019-04-01
publication
https://doi.org/10.1575/1912/bco-dmo.747872.1
Sonya T. Dyhrman
Lamont-Doherty Earth Observatory
principalInvestigator
James Jeffrey Morris
University of Alabama at Birmingham
principalInvestigator
Gwenn Hennon
Lamont-Doherty Earth Observatory
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: Hennon, G. (2018) NCBI accessions of the harmful alga Heterosigma akashiwo (CCMP2393) grown under a range of CO2 concentrations from 200-1000 ppm. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2018-10-11 [if applicable, indicate subset used]. doi:10.1575/1912/bco-dmo.747872.1 [access date]
Heterosigma akashiwo acclimation - BioProject PRJNA377729 Dataset Description: <p>This dataset includes metadata associated with&nbsp;NCBI BioProject PRJNA377729&nbsp;"Impacts of Evolution on the Response of Phytoplankton Populations to Rising CO2"&nbsp;<a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA377729" target="_blank">PRJNA377729</a><a href="http://www.ncbi.nlm.nih.gov/bioproject/PRJNA377729" target="_blank">:&nbsp;</a><a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA377729" target="_blank">https://www.ncbi.nlm.nih.gov/bioproject/PRJNA377729</a>. The alga&nbsp;Heterosigma&nbsp;akashiwo&nbsp;was grown&nbsp;at CO2 levels from about 200 to 1000 ppm and then the DNA and RNA were sequenced.</p> Methods and Sampling: <p>Uni-algal, non-axenic cultures of Heterosigma akashiwo (CCMP2393) were grown in L1 medium (without silicate) made with a Long Island Sound seawater base collected from Avery Point, CT, USA (salinity 32) at 18°C with a 14:10 (light:dark) cycle with an irradiance of approximately 100 µmol m-2 s-1 . Cells were acclimated in exponential growth phase to different carbonate chemistries in 1.2 L of L1 media in 2.5-L polycarbonate bottles. To control the carbonate chemistry of the water, the headspace of each bottle was purged continuously with a custom gas mixture of ~21% oxygen, ~79% nitrogen and either 200, 400, 600, 800 or 1000 ppmv CO2 (TechAir, NY).</p>
<p>At the point of harvest, 150 mL (~6 x 106 cells) were filtered on to 5 µm pore size, 25 mm polycarbonate filter and flash frozen in liquid nitrogen. Genetic material from samples was extracted with the RNeasy Mini kit (Qiagen, Valencia, CA) and DNA was removed on-column using the RNase-free DNase Set (Qiagen), yielding total RNA. Total RNA extracts of the triplicate cultures were quantified on a 2100 Bioanalyzer (Agilent, Santa Clara, CA). Libraries were prepared using poly-A pull down with the TruSeq Stranded mRNA Library Prep kit (Illumina, San Diego, CA). Library preparation, barcoding, and sequencing from each library was performed by the JP Sulzberger Columbia University Genome Center (New York, NY).</p>
<p>Sequence reads were de-multiplexed and trimmed to remove sequencing barcodes. Reads were aligned using Bowtie2 (Langmead and Salzberg 2012) to the MMETSP consensus contigs for Heterosigma akashiwo CCMP2393 (https://omictools.com/marine-microbial-eukaryotic-transcriptome-sequencing-project-tool).</p>
<p>Significant differences between physiological parameters by CO2 treatment were assessed with analysis of variance (ANOVA) and Tukey’s honestly significant differences test (aov and TukeyHSD, stats, R). Differential expression of genes in any CO2 treatment compared to modern was determined using the general linear model (GLM) exact test (edgeR, R). Briefly, the read counts were normalized by trimmed mean of M-values (TMM) using the function calcNormFactors, tagwise dispersions were calculated with the function estimateGLMTagwiseDisp, a GLM was fit using glmFit, and log2 fold change (logFC) for each treatment was calculated relative to average expression at modern CO2. P-values from likelihood ratio tests were corrected for multiple testing using the false discovery method (fdr).</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1314336 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1314336
completed
Sonya T. Dyhrman
Lamont-Doherty Earth Observatory
845-365-8465
102E Geoscience 61 Route 9W, PO Box 1000
Palisades
NY
10964
USA
dyhrman@ldeo.columbia.edu
pointOfContact
James Jeffrey Morris
University of Alabama at Birmingham
205-934-9498
1300 University Blvd CH253
Birmingham
AL
35294
USA
evolve@uab.edu
pointOfContact
Gwenn Hennon
Lamont-Doherty Earth Observatory
907-474-6735
College of Fisheries and Ocean Sciences Irving II Rm 331
Fairbanks
AK
99775
USA
gmhennon@alaska.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
sample_name
sample_title
bioproject_accession
organism
strain
isolate
host
isolation_source
collection_date
geo_loc_name
sample_type
biomaterial_provider
collected_by
depth
env_biome
genotype
lat_lon
passage_history
samp_size
temp_C
light_level_umol_m2_s
light_dark_hr
Media
CO2_ppm
Alkalinity
pH
Illumina Hi-seq 2500 paired-end sequencing (PE100) with TruSeq RNA sample Prep Kit (Illumina, San Diego, CA)
theme
None, User defined
sample identification
accession number
taxon
No BCO-DMO term
site
date
sample description
laboratory
person name
depth
site description
latitude
treatment
cell_concentration
water temperature at measurement depth
irradiance
duration
Partial pressure of CO2
total alkalinity (TA)
pH
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.
Science, Engineering and Education for Sustainability NSF-Wide Investment (SEES): Ocean Acidification (formerly CRI-OA)
https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503477
Science, Engineering and Education for Sustainability NSF-Wide Investment (SEES): Ocean Acidification (formerly CRI-OA)
NSF Climate Research Investment (CRI) activities that were initiated in 2010 are now included under Science, Engineering and Education for Sustainability NSF-Wide Investment (SEES). SEES is a portfolio of activities that highlights NSF's unique role in helping society address the challenge(s) of achieving sustainability. Detailed information about the SEES program is available from NSF (https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504707).
In recognition of the need for basic research concerning the nature, extent and impact of ocean acidification on oceanic environments in the past, present and future, the goal of the SEES: OA program is to understand (a) the chemistry and physical chemistry of ocean acidification; (b) how ocean acidification interacts with processes at the organismal level; and (c) how the earth system history informs our understanding of the effects of ocean acidification on the present day and future ocean.
Solicitations issued under this program:
NSF 10-530, FY 2010-FY2011
NSF 12-500, FY 2012
NSF 12-600, FY 2013
NSF 13-586, FY 2014
NSF 13-586 was the final solicitation that will be released for this program.
PI Meetings:
1st U.S. Ocean Acidification PI Meeting(March 22-24, 2011, Woods Hole, MA)
2nd U.S. Ocean Acidification PI Meeting(Sept. 18-20, 2013, Washington, DC)
3rd U.S. Ocean Acidification PI Meeting (June 9-11, 2015, Woods Hole, MA – Tentative)
NSF media releases for the Ocean Acidification Program:
Press Release 10-186 NSF Awards Grants to Study Effects of Ocean Acidification
Discovery Blue Mussels "Hang On" Along Rocky Shores: For How Long?
Discovery nsf.gov - National Science Foundation (NSF) Discoveries - Trouble in Paradise: Ocean Acidification This Way Comes - US National Science Foundation (NSF)
Press Release 12-179 nsf.gov - National Science Foundation (NSF) News - Ocean Acidification: Finding New Answers Through National Science Foundation Research Grants - US National Science Foundation (NSF)
Press Release 13-102 World Oceans Month Brings Mixed News for Oysters
Press Release 13-108 nsf.gov - National Science Foundation (NSF) News - Natural Underwater Springs Show How Coral Reefs Respond to Ocean Acidification - US National Science Foundation (NSF)
Press Release 13-148 Ocean acidification: Making new discoveries through National Science Foundation research grants
Press Release 13-148 - Video nsf.gov - News - Video - NSF Ocean Sciences Division Director David Conover answers questions about ocean acidification. - US National Science Foundation (NSF)
Press Release 14-010 nsf.gov - National Science Foundation (NSF) News - Palau's coral reefs surprisingly resistant to ocean acidification - US National Science Foundation (NSF)
Press Release 14-116 nsf.gov - National Science Foundation (NSF) News - Ocean Acidification: NSF awards $11.4 million in new grants to study effects on marine ecosystems - US National Science Foundation (NSF)
SEES-OA
largerWorkCitation
program
Impacts of Evolution on the Response of Phytoplankton Populations to Rising CO2
https://osprey.bco-dmo.org/project/2276
Impacts of Evolution on the Response of Phytoplankton Populations to Rising CO2
<p>Note: This project is also affiliated with the <a href="http://beacon-center.org/" target="_blank">NSF BEACON Center for the Study of Evolution in Action</a>.</p>
<p><em>Project Description from NSF Award:</em><br />
Human activities are driving up atmospheric carbon dioxide concentrations at an unprecedented rate, perturbing the ocean's carbonate buffering system, lowering oceanic pH, and changing the concentration and composition of dissolved inorganic carbon. Recent studies have shown that this ocean acidification has many short-term effects on phytoplankton, including changes in carbon fixation among others. These physiological changes could have profound effects on phytoplankton metabolism and community structure, with concomitant effects on Earth's carbon cycle and, hence, global climate. However, extrapolation of present understanding to the field are complicated by the possibility that natural populations might evolve in response to their changing environments, leading to different outcomes than those predicted from short-term studies. Indeed, evolution experiments demonstrate that microbes are often able to rapidly adapt to changes in the environment, and that beneficial mutations are capable of sweeping large populations on time scales relevant to predictions of environmental dynamics in the coming decades. This project addresses two major areas of uncertainty for phytoplankton populations with the following questions:<br />
1) What adaptive mutations to elevated CO2 are easily accessible to extant species, how often do they arise, and how large are their effects on fitness?<br />
2) How will physical and ecological interactions affect the expansion of those mutations into standing populations?</p>
<p>This study will address these questions by coupling experimental evolution with computational modeling of ocean biogeochemical cycles. First, cultured unicellular phytoplankton, representative of major functional groups (e.g. cyanobacteria, diatoms, coccolithophores), will be evolved under simulated year 2100 CO2 concentrations. From these experiments, estimates will be made of a) the rate of beneficial mutations, b) the magnitude of fitness gains conferred by these mutations, and c) secondary phenotypes (i.e., trade-offs) associated with these mutations, assayed using both physiological and genetic approaches. Second, an existing numerical model of the global ocean system will be modified to a) simulate the effects of changing atmospheric CO2 concentrations on ocean chemistry, and b) allow the introduction of CO2-specific adaptive mutants into the extant populations of virtual phytoplankton. The model will be used to explore the ecological and biogeochemical impacts of beneficial mutations in realistic environmental situations (e.g. resource availability, predation, etc.). Initially, the model will be applied to idealized sensitivity studies; then, as experimental results become available, the implications of the specific beneficial mutations observed in our experiments will be explored.</p>
<p>This interdisciplinary study will provide novel, transformative understanding of the extent to which evolutionary processes influence phytoplankton diversity, physiological ecology, and carbon cycling in the near-future ocean. One of many important outcomes will be the development and testing of nearly-neutral genetic markers useful for competition studies in major phytoplankton functional groups, which has applications well beyond the current proposal.</p>
P-ExpEv
largerWorkCitation
project
eng; USA
biota
oceans
2017-06-21
2017-07-13
Experiment housed in laboratories at Michigan State University
0
BCO-DMO catalogue of parameters from NCBI accessions of the harmful alga Heterosigma akashiwo (CCMP2393) grown under a range of CO2 concentrations from 200-1000 ppm
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/747882.rdf
Name: sample_name
Units: unitless
Description: <p>A unique name for the sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/747883.rdf
Name: sample_title
Units: unitless
Description: <p>Title of the sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/747884.rdf
Name: bioproject_accession
Units: unitless
Description: <p>The accession number of the BioProject(s) to which the BioSample belongs.</p>
http://lod.bco-dmo.org/id/dataset-parameter/747885.rdf
Name: organism
Units: unitless
Description: <p>The most descriptive organism name for this sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/747886.rdf
Name: strain
Units: unitless
Description: <p>The microbial or eukaryotic strain name</p>
http://lod.bco-dmo.org/id/dataset-parameter/747887.rdf
Name: isolate
Units: unitless
Description: <p>Identification or description of the specific individual from which this sample was obtained</p>
http://lod.bco-dmo.org/id/dataset-parameter/747888.rdf
Name: host
Units: unitless
Description: <p>The natural (as opposed to laboratory) host to the organism from which the sample was obtained.</p>
http://lod.bco-dmo.org/id/dataset-parameter/747889.rdf
Name: isolation_source
Units: unitless
Description: <p>Describes the physical - environmental and/or local geographical source of the biological sample from which the sample was derived.</p>
http://lod.bco-dmo.org/id/dataset-parameter/747890.rdf
Name: collection_date
Units: unitless
Description: <p>Date of sampling formatted as yyyy-mm-dd</p>
http://lod.bco-dmo.org/id/dataset-parameter/747891.rdf
Name: geo_loc_name
Units: unitless
Description: <p>Geographical origin of the sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/747892.rdf
Name: sample_type
Units: unitless
Description: <p>Sample type</p>
http://lod.bco-dmo.org/id/dataset-parameter/747893.rdf
Name: biomaterial_provider
Units: unitless
Description: <p>Name and address of the lab or PI or a culture collection identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/747894.rdf
Name: collected_by
Units: unitless
Description: <p>Name of persons or institute who collected the sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/747895.rdf
Name: depth
Units: meters
Description: <p>Sample collection depth</p>
http://lod.bco-dmo.org/id/dataset-parameter/747896.rdf
Name: env_biome
Units: unitless
Description: <p>Descriptor of the broad ecological context of a sample.</p>
http://lod.bco-dmo.org/id/dataset-parameter/747897.rdf
Name: genotype
Units: unitless
Description: <p>Observed genotype</p>
http://lod.bco-dmo.org/id/dataset-parameter/747898.rdf
Name: lat_lon
Units: decimal degrees
Description: <p>latitude and longitude of sample colllection</p>
http://lod.bco-dmo.org/id/dataset-parameter/747899.rdf
Name: passage_history
Units: unitless
Description: <p>Number of passages and passage method</p>
http://lod.bco-dmo.org/id/dataset-parameter/747900.rdf
Name: samp_size
Units: unitless
Description: <p>Amount or size of sample that was collected</p>
http://lod.bco-dmo.org/id/dataset-parameter/747901.rdf
Name: temp_C
Units: degrees Celsius
Description: <p>Temperature of the sample at time of sampling</p>
http://lod.bco-dmo.org/id/dataset-parameter/747902.rdf
Name: light_level_umol_m2_s
Units: micromol photons m-2 s-1
Description: <p>Light level</p>
http://lod.bco-dmo.org/id/dataset-parameter/747903.rdf
Name: light_dark_hr
Units: hours
Description: <p>duration of light and dark cycles</p>
http://lod.bco-dmo.org/id/dataset-parameter/747904.rdf
Name: Media
Units: unitless
Description: <p>Type of growth medium used</p>
http://lod.bco-dmo.org/id/dataset-parameter/747905.rdf
Name: CO2_ppm
Units: parts per million
Description: <p>CO2 concentration</p>
http://lod.bco-dmo.org/id/dataset-parameter/747906.rdf
Name: Alkalinity
Units: micromol per kilogram (umol/kg)
Description: <p>Alkalinity of sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/747907.rdf
Name: pH
Units: unitless; pH scale
Description: <p>The measure of the acidity or basicity of an aqueous solution</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
6587
https://darchive.mblwhoilibrary.org/bitstream/1912/23944/1/dataset-747872_heterosigma-akashiwo-acclimation__v1.tsv
download
https://doi.org/10.1575/1912/bco-dmo.747872.1
download
onLine
dataset
<p>Uni-algal, non-axenic cultures of Heterosigma akashiwo (CCMP2393) were grown in L1 medium (without silicate) made with a Long Island Sound seawater base collected from Avery Point, CT, USA (salinity 32) at 18°C with a 14:10 (light:dark) cycle with an irradiance of approximately 100 µmol m-2 s-1 . Cells were acclimated in exponential growth phase to different carbonate chemistries in 1.2 L of L1 media in 2.5-L polycarbonate bottles. To control the carbonate chemistry of the water, the headspace of each bottle was purged continuously with a custom gas mixture of ~21% oxygen, ~79% nitrogen and either 200, 400, 600, 800 or 1000 ppmv CO2 (TechAir, NY).</p>
<p>At the point of harvest, 150 mL (~6 x 106 cells) were filtered on to 5 µm pore size, 25 mm polycarbonate filter and flash frozen in liquid nitrogen. Genetic material from samples was extracted with the RNeasy Mini kit (Qiagen, Valencia, CA) and DNA was removed on-column using the RNase-free DNase Set (Qiagen), yielding total RNA. Total RNA extracts of the triplicate cultures were quantified on a 2100 Bioanalyzer (Agilent, Santa Clara, CA). Libraries were prepared using poly-A pull down with the TruSeq Stranded mRNA Library Prep kit (Illumina, San Diego, CA). Library preparation, barcoding, and sequencing from each library was performed by the JP Sulzberger Columbia University Genome Center (New York, NY).</p>
<p>Sequence reads were de-multiplexed and trimmed to remove sequencing barcodes. Reads were aligned using Bowtie2 (Langmead and Salzberg 2012) to the MMETSP consensus contigs for Heterosigma akashiwo CCMP2393 (https://omictools.com/marine-microbial-eukaryotic-transcriptome-sequencing-project-tool).</p>
<p>Significant differences between physiological parameters by CO2 treatment were assessed with analysis of variance (ANOVA) and Tukey’s honestly significant differences test (aov and TukeyHSD, stats, R). Differential expression of genes in any CO2 treatment compared to modern was determined using the general linear model (GLM) exact test (edgeR, R). Briefly, the read counts were normalized by trimmed mean of M-values (TMM) using the function calcNormFactors, tagwise dispersions were calculated with the function estimateGLMTagwiseDisp, a GLM was fit using glmFit, and log2 fold change (logFC) for each treatment was calculated relative to average expression at modern CO2. P-values from likelihood ratio tests were corrected for multiple testing using the false discovery method (fdr).</p>
Specified by the Principal Investigator(s)
<p><strong>BCO-DMO Processing Notes:</strong><br />
- added conventional header with dataset name, PI name, version date<br />
- modified parameter names to conform with BCO-DMO naming conventions<br />
- reformatted date from DD-Mmm-YYYY to yyyy-mm-dd<br />
- changed entries of 'not applicable' to 'nd'</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
Illumina Hi-seq 2500 paired-end sequencing (PE100) with TruSeq RNA sample Prep Kit (Illumina, San Diego, CA)
Illumina Hi-seq 2500 paired-end sequencing (PE100) with TruSeq RNA sample Prep Kit (Illumina, San Diego, CA)
PI Supplied Instrument Name: Illumina Hi-seq 2500 paired-end sequencing (PE100) with TruSeq RNA sample Prep Kit (Illumina, San Diego, CA) PI Supplied Instrument Description:Used to prepare the mRNA libraries. Samples were barcoded for multiplex sequencing and run on in a single lane by the Columbia University Genome Center (CUGC) (New York, NY). 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.