http://lod.bco-dmo.org/id/dataset/958698
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
2025-04-10
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
NCBI accession numbers and related metadata for an SRA archive of the seagrass, Zostera marina
2025-04-10
publication
2025-04-10
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2025-04-11
publication
https://doi.org/10.26008/1912/bco-dmo.958698.1
Torrance C. Hanley
Northeastern University
principalInvestigator
Cynthia Hays
Keene State College
principalInvestigator
A. Randall Hughes
Northeastern University
principalInvestigator
Erik Sotka
Grice Marine Laboratory - College of Charleston
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: Sotka, E., Hanley, T. C., Hughes, A. R., Hays, C. (2025) NCBI accession numbers and related metadata for an SRA archive of the seagrass, Zostera marina. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-04-10 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.958698.1 [access date]
Zostera marina GenBank SRA accession numbers Dataset Description: Methods and Sampling: <p>During the June peak of seasonal flowering in 2019, divers on SCUBA collected a single vegetative shoot at each node within each sampling grid for genetic analysis (n=15 ramets per grid, 45 per depth, 90 per site). At approximately alternating nodes (i.e., 5-7 of the 15 nodes in each grid, depending on the location of bare patches), divers also harvested all shoots from within a 25 × 25 centimeter (cm) quadrat (n = 15-21 per depth) to estimate shoot density and canopy characteristics. Samples were returned to the lab on ice for processing. The second and third leaves of each genetic sample were preserved in silica.</p>
<p>After the flowering season and once seeds had dropped (September 2019; von Staats et al. 2021), we returned to each sampling grid to collect dispersed seeds. Sediment cores (10 cm in diameter and 10 cm in depth) were taken at three locations within each grid at Curlew Beach and at four locations within each grid at the other three field sites (n=9 or 12 cores per depth). Sediment cores were bagged and kept cold (4 degrees Celsius (°C)) until they could be processed; each core was hand-sieved for intact seeds within 3 days of collection. We counted all intact seeds encountered and assessed viability by firmness (the squeeze test; Marion and Orth 2010). Seeds deemed viable were individually weighed and stored in microfuge tubes and frozen at -80°C until DNA extraction.</p>
<p>Leaf samples (2 to 4 milligrams (mg) of dried tissue from the middle third of the leaf) were ground with a Retsch mixer mill MM400; seeds were ground by hand with a micropestle after removing the seed coat. DNA extraction was done with the Omega Bio-Tek E-Z 96 Tissue DNA kit, and samples were stored at -20°C. We prepared one genomic library of 464 individuals (359 adults, 105 seeds) by following the ddRADseq protocol of Parchman et al. (2012) and sequenced the library using two lanes of Illumina Novaseq. We digested gDNA with two restriction enzymes, EcoRI and MseI, and ligated adaptors containing unique 8-10bp barcodes to the digested DNA of each individual. The products were then PCR-amplified in two independent reactions with standard Illumina primers. All amplicons were pooled and shipped to the University of Texas Genomic Sequencing and Analysis Facility, which used Blue Pippen Prep to isolate the 300-450bp fraction. This fraction was then single-read-sequenced (approximately 100bp) with both lanes of an Illumina Novaseq machine. We used custom scripts to demultiplex into sample-specific FASTQ- formatted files.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1851262 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1851262
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1924599 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1924599
completed
Torrance C. Hanley
Northeastern University
4000 Mayflower Hill Diamond 204
Waterville
ME
04901
USA
hanleyt2@sacredheart.edu
pointOfContact
Cynthia Hays
Keene State College
603-358-2527
229 Main Street
Keene
NH
03435
USA
chays@keene.edu
pointOfContact
A. Randall Hughes
Northeastern University
781-581-7370
430 Nahant Rd.
Nahant
MA
01908
USA
ann.hughes@northeastern.edu
pointOfContact
Erik Sotka
Grice Marine Laboratory - College of Charleston
843-953-9191
Grice Marine Laboratory 205 Fort Johnson Road
Charleston
SC
29412
USA
SotkaE@cofc.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Accession
Sample_Name
adult_seed
site
SvD
quad_name
lon
lat
YearCollected
Illumina Novaseq machine
Retsch mixer mill MM400
sediment cores
SCUBA
theme
None, User defined
NCBI BioSample accession
sample identification
sample description
site
site description
longitude
latitude
year
featureType
BCO-DMO Standard Parameters
Automated DNA Sequencer
Homogenizer
Sediment Corer
Self-Contained Underwater Breathing Apparatus
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.
RUI: Collaborative Research: Trait differentiation and local adaptation to depth within meadows of the foundation seagrass Zostera marina
https://osprey.bco-dmo.org/project/792405
RUI: Collaborative Research: Trait differentiation and local adaptation to depth within meadows of the foundation seagrass Zostera marina
<p><em>NSF Award Abstract:</em><br />
Understanding how species cope with spatial variation in their environment (e.g. gradients in light and temperature) is necessary for informed management as well as for predicting how they may respond to change. This project will examine how key traits vary with depth in common eelgrass (Zostera marina), one of the most important foundation species in temperate nearshore ecosystems worldwide. The investigators will use a combination of experiments in the field and lab, paired with fine-scale molecular analyses, to determine the genetic and environmental components of seagrass trait variation. This work will provide important information on the microevolutionary mechanisms that allow a foundation species to persist in a variable environment, and thus to drive the ecological function of whole nearshore communities. The Northeastern University graduate and Keene State College (KSC) undergraduate students supported by this project will receive training in state-of-the-art molecular techniques, as well as mentorship and experience in scientific communication and outreach. A significant portion of KSC students are from groups under-represented in science. Key findings of the research will be incorporated into undergraduate courses and outreach programs for high school students from under-represented groups, and presented at local and national meetings of scientists and stakeholders.</p>
<p>Local adaptation, the superior performance of "home" versus "foreign" genotypes in a local environment, is a powerful demonstration of how natural selection can overcome gene flow and drift to shape phenotypes to match their environment. The classic test for local adaptation is a reciprocal transplant. However, such experiments often fail to capture critical aspects of the immigration process that may mediate realized gene flow in natural systems. For example, reciprocal transplant experiments typically test local and non-local phenotypes at the same (often adult) life history stage, and at the same abundance or density, which does not mirror how dispersal actually occurs for most species. In real populations, migrants (non-local) often arrive at low numbers compared to residents (local), and relative frequency itself can impact fitness. In particular, rare phenotypes may experience reduced competition for resources, or relative release from specialized pathogens. Such negative frequency dependent selection can reduce fitness differences between migrants and residents due to local adaptation, and magnify effective gene flow, thus maintaining greater within-population genetic diversity. The investigators will combine spatially paired sampling and fine-scale molecular analyses to link seed/seedling trait variation across the depth gradient at six meadows to key factors that may drive these patterns: local environmental conditions, population demography, and gene flow across depths. The team will then experimentally test the outcome of cross-gradient dispersal in an ecologically relevant context, by reciprocally out-planting seeds from different depths and manipulating relative frequency in relation to both adults and other seedling lineages. The possible interaction between local adaptation and frequency-dependence is particularly relevant for Zostera marina, which represents one of the best documented examples of the ecological effects of genetic diversity and identity. Further, a better understanding of seagrass trait differentiation is not simply a matter of academic interest, but critical to successful seagrass restoration and conservation.</p>
<p>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.</p>
ZosMarLA
largerWorkCitation
project
The genetic legacy of an Asian oyster introduction and its disease-causing parasite
https://osprey.bco-dmo.org/project/820200
The genetic legacy of an Asian oyster introduction and its disease-causing parasite
<p><em>NSF abstract:</em></p>
<p>During the 20th century, the Pacific oyster <em>Crassostrea gigas</em> was deliberately introduced from its native range of coastal Asia to the estuaries of six continents. While the introduced Pacific oysters are widely aquacultured and thus can generate local economic wealth, they sometimes outcompete native oysters, and can carry microbial, animal and plant hitchhikers that negatively impact local economies and the ecological functioning of local estuaries. This study comprehensively assesses the pathways and sources of Pacific oyster introductions using a worldwide, population genetic survey. Simultaneously, the study also assesses the pathways and source of one hitchhiking protist (<em>Haplosporidium nelsoni</em>) that causes the disease MSX (multinucleated sphere X) in the Virginia oyster (<em>Crassostrea virginica</em>) along the eastern seaboard of the United States. One goal of this research is to generate management strategies that combat the negative impacts of the Pacific oyster and its associated invaders, and minimize future invasions. A second goal is to minimize some uncertainty about the population biology of the devastating Haplosporidium parasite, and thus, increase confidence of policy makers who are managing shellfish health, restoration and commerce. By quantifying the pathways and sources of <em>C. gigas</em>, this project may inform strategies to combat negative impacts of <em>C. gigas</em> and its associated invaders, as well as minimize future invasions. Moreover, quantifying dispersal within and among populations of <em>H. nelsoni</em> along the US East Coast will provide perspective on the effectiveness of regional biosecurity measures in preventing the ongoing dispersal of this destructive pathogen via aquaculture. In addition, the project lends itself well to programs that foster critical thinking and research experience among both undergraduate and K-12 students. The project provides opportunities for 6-9 undergraduates to perform research, includes a 2-day workshop on bioinformatics for the wider undergraduate community, and facilitates ongoing opportunities for K-12 students to participate in citizen-science research.</p>
<p>There is a wealth of information on the source, pathways and vectors of <em>C. gigas</em> based largely on historical documents but no study has comprehensively tested whether these historical accounts are correct using a worldwide, population genetic survey. Using >14K single-nucleotide polymorphisms (SNPs) from 41 populations across five continents a high level of spatial genetic differentiation was found within the native range and differences in source populations among non-native regions. Preliminary genetic data indicated that the parasitic protist, <em>Haplosporidium nelsoni </em>arrived with C. gigas imports to the US Atlantic coastline and then infected the native C. virginica, however the native source populations, the pathways and vector from which <em>H. nelsoni </em>arrived remain unknown. This project couples high-throughput sequencing technologies and Approximate Bayesian Computing (ABC)-based models to answer the following: What are the population genomic patterns among <em>C. gigas</em> from native and non-native regions? What are the population genomic patterns of <em>Haplosporidium nelsoni </em>among Asian and North American Crassostrea gigas and eastern North American <em>C. virginica</em>? What were the source populations and invasion pathways of <em>C. gigas</em> and <em>H. nelsoni</em>? Identifying source locations, pathways and vectors of introduction of C. gigas will provide researchers with a null-model of invasion history for dozens of other non-native species that were transported with <em>C. gigas</em>. Currently, there are no verified 'vector maps' for historical shipments of <em>C. gigas</em> that are similar to those generated from modern-day or historical shipping records.</p>
<p>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.</p>
Oyster historical genetics
largerWorkCitation
project
eng; USA
oceans
-70.91758865
-70.65518121
42.419022
42.596758
2019-06-01
2019-10-01
From projects that focused on the following 2 locations: 1. Massachusetts, USA 2. Global
0
BCO-DMO catalogue of parameters from NCBI accession numbers and related metadata for an SRA archive of the seagrass, Zostera marina
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/958716.rdf
Name: Accession
Units: unitless
Description: <p>GenBank BioSample number</p>
http://lod.bco-dmo.org/id/dataset-parameter/958717.rdf
Name: Sample_Name
Units: unitless
Description: <p>Sample Name (note: the S and A at the end of the names are seed vs adults; the S vs D at the 2nd character are deep vs shallow depths)</p>
http://lod.bco-dmo.org/id/dataset-parameter/958718.rdf
Name: adult_seed
Units: unitless
Description: <p>A = Adult or S = seed</p>
http://lod.bco-dmo.org/id/dataset-parameter/958719.rdf
Name: site
Units: unitless
Description: <p>One letter population code (D = Curlew, N = Niles, W = West, L = Lynn)</p>
http://lod.bco-dmo.org/id/dataset-parameter/958720.rdf
Name: SvD
Units: unitless
Description: <p>Depth of site. s = shallow or d = deep</p>
http://lod.bco-dmo.org/id/dataset-parameter/958721.rdf
Name: quad_name
Units: unitless
Description: <p>Within-site position in a transect (1st six places); 2 digit individual ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/958722.rdf
Name: lon
Units: decimal degrees
Description: <p>Longitude of opulation collection site</p>
http://lod.bco-dmo.org/id/dataset-parameter/958723.rdf
Name: lat
Units: decimal degrees
Description: <p>Latitude of population collection site</p>
http://lod.bco-dmo.org/id/dataset-parameter/958724.rdf
Name: YearCollected
Units: unitless
Description: <p>Year of collection</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
29427
https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/3556ab3e-1157-46e6-8cb2-32d85ae5988c/content
download
https://doi.org/10.26008/1912/bco-dmo.958698.1
download
onLine
dataset
<p>During the June peak of seasonal flowering in 2019, divers on SCUBA collected a single vegetative shoot at each node within each sampling grid for genetic analysis (n=15 ramets per grid, 45 per depth, 90 per site). At approximately alternating nodes (i.e., 5-7 of the 15 nodes in each grid, depending on the location of bare patches), divers also harvested all shoots from within a 25 × 25 centimeter (cm) quadrat (n = 15-21 per depth) to estimate shoot density and canopy characteristics. Samples were returned to the lab on ice for processing. The second and third leaves of each genetic sample were preserved in silica.</p>
<p>After the flowering season and once seeds had dropped (September 2019; von Staats et al. 2021), we returned to each sampling grid to collect dispersed seeds. Sediment cores (10 cm in diameter and 10 cm in depth) were taken at three locations within each grid at Curlew Beach and at four locations within each grid at the other three field sites (n=9 or 12 cores per depth). Sediment cores were bagged and kept cold (4 degrees Celsius (°C)) until they could be processed; each core was hand-sieved for intact seeds within 3 days of collection. We counted all intact seeds encountered and assessed viability by firmness (the squeeze test; Marion and Orth 2010). Seeds deemed viable were individually weighed and stored in microfuge tubes and frozen at -80°C until DNA extraction.</p>
<p>Leaf samples (2 to 4 milligrams (mg) of dried tissue from the middle third of the leaf) were ground with a Retsch mixer mill MM400; seeds were ground by hand with a micropestle after removing the seed coat. DNA extraction was done with the Omega Bio-Tek E-Z 96 Tissue DNA kit, and samples were stored at -20°C. We prepared one genomic library of 464 individuals (359 adults, 105 seeds) by following the ddRADseq protocol of Parchman et al. (2012) and sequenced the library using two lanes of Illumina Novaseq. We digested gDNA with two restriction enzymes, EcoRI and MseI, and ligated adaptors containing unique 8-10bp barcodes to the digested DNA of each individual. The products were then PCR-amplified in two independent reactions with standard Illumina primers. All amplicons were pooled and shipped to the University of Texas Genomic Sequencing and Analysis Facility, which used Blue Pippen Prep to isolate the 300-450bp fraction. This fraction was then single-read-sequenced (approximately 100bp) with both lanes of an Illumina Novaseq machine. We used custom scripts to demultiplex into sample-specific FASTQ- formatted files.</p>
Specified by the Principal Investigator(s)
<p>These are the raw sequences from the Illumina sequencer after the demultiplex step (see methods above).</p>
Specified by the Principal Investigator(s)
- Imported original file "BioSampleObjects_wLatLon_final.csv" into the BCO-DMO system.
- Renamed fields to comply with BCO-DMO naming conventions.
- Saved final file as "958698_v1_z_marina_genbank_accessions.csv".
Specified by BCO-DMO Data Managers
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 Novaseq machine
Illumina Novaseq machine
PI Supplied Instrument Name: Illumina Novaseq machine 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.
Retsch mixer mill MM400
Retsch mixer mill MM400
PI Supplied Instrument Name: Retsch mixer mill MM400 Instrument Name: Homogenizer Instrument Short Name:Homogenizer Instrument Description: A homogenizer is a piece of laboratory equipment used for the homogenization of various types of material, such as tissue, plant, food, soil, and many others.
sediment cores
sediment cores
PI Supplied Instrument Name: sediment cores Instrument Name: Sediment Corer Instrument Short Name: Instrument Description: A generic term for a coring device that allows for relatively undisturbed penetration of the sediment. Generally, core samplers consist of a core barrel (a hollow pipe or box) and a core cutter (or cutting head), located at the advancing end of the core barrel to facilitate the sampler's advancement into the sediment. Core catchers are commonly inserted into the cutting head to prevent sample loss during retrieval.
SCUBA
SCUBA
PI Supplied Instrument Name: SCUBA Instrument Name: Self-Contained Underwater Breathing Apparatus Instrument Short Name:SCUBA Instrument Description: The self-contained underwater breathing apparatus or scuba diving system is the result of technological developments and innovations that began almost 300 years ago. Scuba diving is the most extensively used system for breathing underwater by recreational divers throughout the world and in various forms is also widely used to perform underwater work for military, scientific, and commercial purposes.
Reference: https://oceanexplorer.noaa.gov/technology/technical/technical.html