http://lod.bco-dmo.org/id/dataset/1004242
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
2026-08-07
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Oyster genetic assignment data from an experimental oyster reef restoration in Ninigret Pond, Rhode Island (USA) in 2017-2020
2026-08-07
publication
2026-08-07
revision
BCO-DMO Linked Data URI
2026-08-07
creation
http://lod.bco-dmo.org/id/dataset/1004242
A. Randall Hughes
Northeastern University
principalInvestigator
Sarit Truskey
Northeastern University
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: Hughes, A. R., Truskey, S. (2026) Oyster genetic assignment data from an experimental oyster reef restoration in Ninigret Pond, Rhode Island (USA) in 2017-2020. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2026-08-07 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/1004242 [access date]
Individual genetic assignments from hatchery samples and restored reefs Dataset Description: Methods and Sampling: <p>These data were published in Truskey et al. 2025 (Evolutionary Applications). All figure numbers and supplementary materials mentioned refer to Truskey et al. 2025 (Evolutionary Applications).</p>
<p><strong>Restoration experiment and sample collection</strong></p>
<p>In April 2017, we collaborated with local oyster farmers to source oyster eyed-larvae from four commercial hatcheries for the construction of new experimental oyster reefs in Ninigret Pond (Charlestown, Rhode Island, USA). Hatchery sources were selected across a broad geographic sampling range to maximize diversity (Figure&nbsp;1a of Truskey et al. 2025). They included two regional hatcheries, one from Massachusetts (MA) and one from New York (NY), and two more distant hatcheries, one from Maine (ME) and one from Virginia (VA). A local Rhode Island hatchery facility received oyster eyed-larvae from each source hatchery, set the eyed-larvae on dead oyster and/or clam shell (hereafter referred to as spat-on-shell oysters), and distributed the spat-on-shell oysters to three local oyster growers (Grower 1: MA; Grower 2: ME, NY, VA; Grower 3: NY, VA) who maintained these juvenile oysters on separate leased oyster farm plots prior to reef construction. Immediately prior to reef construction, we collected 20 juvenile spat-on-shell oysters from each grower-hatchery source combination for genetic analysis (<em>n</em> = 6 combinations; Grower 1-MA; Grower 2-ME; Grower 2-NY; Grower 2-VA; Grower 3-NY; Grower 3-VA).</p>
<p>In October and November 2017, we constructed 16 subtidal reefs within a no-harvest Shellfish Management Area in Ninigret Pond. Reefs were created across four 0.025-acre experimental blocks, with four reefs per block (Figure&nbsp;2 of Truskey et al. 2025). Each reef consisted of a base layer of 0.25 cubic yards of dead oyster or clam shell deployed in October and topped with 1.25 cubic yards of spat-on-shell oysters in early November from the stock grown out by the local oyster growers. Our experiment was originally designed to seed three reefs per block with a different single hatchery source from the four available hatchery sources and to seed the fourth reef per block with a mixed combination of the three sources (e.g., Reef 1: ME, Reef 2: MA, Reef 3: NY, Reef 4: ME+MA+NY). However, analysis of the hatchery samples from oyster growers collected prior to reef construction revealed an early, unintended mixing of some of the sources (Appendix&nbsp;S1 of Truskey et al. 2025; Figure&nbsp;S1 of Truskey et al. 2025), resulting in mixtures of multiple sources on 12 out of the 16 constructed reefs. Thus, we focused our analyses on the actual genetic composition of each reef as determined by genetic sampling at two time points (fall 2018, fall 2020).&nbsp;</p>
<p>In fall 2018, we haphazardly sampled live oysters from each reef on scuba or snorkel (<em>N</em> = 512 individuals total, 32 per reef). Oysters were put on ice and transported to the Northeastern University Marine Science Center where they were held at −80°C until DNA extraction. By the fall of 2020, live oyster densities on all experimental reefs had declined, reflecting mortality of the original planted oysters and a lack of recruitment, consistent with other data from this system (Barrett et&nbsp;al.&nbsp;2024). To assess whether this mortality was associated with a consistent change in the genetic composition of surviving oysters on reefs, we repeated our sampling in fall 2020 and compared the resulting reef genetic profiles to those from fall 2018. Reef sample sizes varied at this time point due to low live abundances (<em>N</em> = 249 individuals total, ranging from 8 to 32 per reef).</p>
<p><strong>DNA extraction, RADseq library preparation, and bioinformatics</strong></p>
<p>Genomic DNA was extracted using the E-Z 96 Tissue DNA Kit (Omega-Biotek, Norcross, GA) following the animal tissue protocol with tissue centrifugation. Double-digest restriction-site-associated DNA (ddRAD) libraries with individually barcoded samples were prepared in three batches following Parchman et al. (2012): (1) initial hatchery samples (n = 120), (2) fall 2018 reef samples (n = 480; 30 oysters per reef across 16 reefs), and (3) fall 2020 reef samples (n = 248). For additional details on ddRAD library preparation, see Appendix S2 of Truskey et al. 2025. All libraries were sequenced with 100-bp single-end reads on an Illumina platform. The initial and fall 2020 batches were sequenced on a single lane of the Illumina HiSeq 2500 at Tufts University Core Facility Genomics; the fall 2018 batch was sequenced on two lanes of the Illumina NovaSeq 6000 at the University of Texas at Austin Genomic Sequencing and Analysis Facility.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1652320 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1652320
onGoing
A. Randall Hughes
Northeastern University
781-581-7370
430 Nahant Rd.
Nahant
MA
01908
USA
ann.hughes@northeastern.edu
pointOfContact
Sarit Truskey
Northeastern University
240-205-3117
sbtruskey@gmail.com
pointOfContact
asNeeded
Dataset Version: 1
Unknown
ind_id
sampling_group
yearcoll
reef
block
grower
hatcherysource_label
grower_by_hatcherysource_label
library
primary_genetic_assignment
dapc_assigned_genetic_cluster_g90maf01_ldprunedrsq05
dapc_assigned_genetic_cluster_g90maf01_g20f2020
dapc_assigned_genetic_cluster_g90maf01
dapc_assigned_genetic_cluster_g90maf025_g20f2020_ldprunedrsq05
dapc_assigned_genetic_cluster_g90maf025_ldprunedrsq05
dapc_assigned_genetic_cluster_g90maf025_g20f2020
dapc_assigned_genetic_cluster_g90maf025
dapc_assigned_genetic_cluster_g90maf05_g20f2020_ldprunedrsq05
dapc_assigned_genetic_cluster_g90maf05_ldprunedrsq05
dapc_assigned_genetic_cluster_g90maf05_g20f2020
dapc_assigned_genetic_cluster_g90maf05
snmf_primary_ancestry_cluster_g90maf01_g20f2020_ldprunedrsq05
snmf_primary_ancestry_cluster_g90maf01_ldprunedrsq05
snmf_primary_ancestry_cluster_g90maf01_g20f2020
snmf_primary_ancestry_cluster_g90maf01
snmf_primary_ancestry_cluster_g90maf025_g20f2020_ldprunedrsq05
snmf_primary_ancestry_cluster_g90maf025_ldprunedrsq05
snmf_primary_ancestry_cluster_g90maf025_g20f2020
snmf_primary_ancestry_cluster_g90maf025
snmf_primary_ancestry_cluster_g90maf05_g20f2020_ldprunedrsq05
snmf_primary_ancestry_cluster_g90maf05_ldprunedrsq05
snmf_primary_ancestry_cluster_g90maf05_g20f2020
snmf_primary_ancestry_cluster_g90maf05
Illumina HiSeq 2500
Illumina NovaSeq 6000
scuba
theme
None, User defined
sample identification
site description
season
site
seq_descrip
No BCO-DMO term
featureType
BCO-DMO Standard Parameters
Automated DNA Sequencer
Automated DNA Sequencer
Manual Biota Sampler
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.
CAREER: Linking genetic diversity, population density, and disease prevalence in seagrass and oyster ecosystems
https://osprey.bco-dmo.org/project/709942
CAREER: Linking genetic diversity, population density, and disease prevalence in seagrass and oyster ecosystems
<p><em>NSF Award Abstract:</em><br />
Disease outbreaks in the ocean are increasing, causing losses of ecologically important marine species, but the factors contributing to these outbreaks are not well understood. This 5-year CAREER project will study disease prevalence and intensity in two marine foundation species - the seagrass Zostera marina and the Eastern oyster Crassostrea virginica. More specifically, host-disease relationships will be explored to understand how genetic diversity and population density of the host species impacts disease transmission and risk. This work will pair large-scale experimental restorations and smaller-scale field experiments to examine disease-host relationships across multiple spatial scales. Comparisons of patterns and mechanisms across the two coastal systems will provide an important first step towards identifying generalities in the diversity-density-disease relationship. To enhance the broader impacts and utility of this work, the experiments will be conducted in collaboration with restoration practitioners and guided by knowledge ascertained from key stakeholder groups. The project will support the development of an early career female researcher and multiple graduate and undergraduate students. Students will be trained in state-of-the-art molecular techniques to quantify oyster and seagrass parasites. Key findings from the surveys and experimental work will be incorporated into undergraduate courses focused on Conservation Biology, Marine Biology, and Disease Ecology. Finally, students in these courses will help develop social-ecological surveys and mutual learning games to stimulate knowledge transfer with stakeholders through a series of workshops.</p>
<p>The relationship between host genetic diversity and disease dynamics is complex. In some cases, known as a dilution effect, diversity reduces disease transmission and risk. However, the opposite relationship, known as the amplification effect, can also occur when diversity increases the risk of infection. Even if diversity directly reduces disease risk, simultaneous positive effects of diversity on host density could lead to amplification by increasing disease transmission between infected and uninfected individuals. Large-scale field restorations of seagrasses (Zostera marina) and oysters (Crassostrea virginica) will be utilized to test the effects of host genetic diversity on host population density and disease prevalence/intensity. Additional field experiments independently manipulating host genetic diversity and density will examine the mechanisms leading to dilution or amplification. Conducting similar manipulations in two marine foundation species - one a clonal plant and the other a non-clonal animal - will help identify commonalities in the diversity-density-disease relationship. Further, collaborations among project scientists, students, and stakeholders will enhance interdisciplinary training and help facilitate the exchange of information to improve management and restoration efforts. As part of these efforts, targeted surveys will be used to document the perceptions and attitudes of managers and restoration practitioners regarding genetic diversity and its role in ecological resilience and restoration.</p>
Seagrass and Oyster Ecosystems
largerWorkCitation
project
eng; USA
biota
oceans
-71.6929
-71.6929
41.3549
41.3549
2017-11-07
2020-10-07
Coastal New England
0
BCO-DMO catalogue of parameters from Oyster genetic assignment data from an experimental oyster reef restoration in Ninigret Pond, Rhode Island (USA) in 2017-2020
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/1004406.rdf
Name: ind_id
Units: unitless
Description: <p>Unique identifier for each individual oyster. This identifier corresponds to the associated FASTQ sequence file name</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004407.rdf
Name: sampling_group
Units: unitless
Description: <p>Indicator for whether an individual was sampled from either an experimental reef or pre-reef construction from an initial hatchery group</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004408.rdf
Name: yearcoll
Units: unitless
Description: <p>Year and season of sample collection (e.g., F2018 = Fall 2018, F2020 = Fall 2020, Init = hatchery-sourced samples taken before reef deployment)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004409.rdf
Name: reef
Units: unitless
Description: <p>For reef samples only. Restored reef from which an individual was collected. Letter refers to experimental block and number refers to the reef number within a block (e.g., D3)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004410.rdf
Name: block
Units: unitless
Description: <p>Experimental block in which a restored reef was situated (A - D)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004411.rdf
Name: grower
Units: unitless
Description: <p>For initial hatchery samples only. Oyster grower that provided the grown-out hatchery-source sample (e.g., Grower1, Grower3)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004412.rdf
Name: hatcherysource_label
Units: unitless
Description: <p>For initial hatchery samples only. Original source hatchery ID as provided by oyster grower labels, corresponding to the state of origin of the respective hatcheries (e.g., NY, MA, VA, ME). *asterisk denotes a source that is likely mislabelled; see Problems/Issues section for details on the unintended mixing of hatchery-sourced samples prior to reef construction</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004413.rdf
Name: grower_by_hatcherysource_label
Units: unitless
Description: <p>For initial hatchery samples only. Combined identifier for oyster grower and original source hatchery label (e.g., Grower1_MA). *asterisk denotes a source that is likely mislabelled; see Problems/Issues section for details on the unintended mixing of hatchery-sourced samples prior to reef construction.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004414.rdf
Name: library
Units: unitless
Description: <p>RADseq library batch in which an individual was processed and sequenced</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004415.rdf
Name: primary_genetic_assignment
Units: unitless
Description: <p>Assigned genetic cluster for an individual using the primary genetic assignment set applied to all main text analyses (DAPC approach, SNP set filtered for MAF > 0.01, LD pruning, and Fall 2020 missing data). Label names correspond to the state of origin of the hatchery source associated with a given genetic cluster (gME, gMA, gNY, gVA)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004416.rdf
Name: dapc_assigned_genetic_cluster_g90maf01_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.01 and pruned for LD</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004417.rdf
Name: dapc_assigned_genetic_cluster_g90maf01_g20f2020
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.01 and pruned for Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004418.rdf
Name: dapc_assigned_genetic_cluster_g90maf01
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.01</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004419.rdf
Name: dapc_assigned_genetic_cluster_g90maf025_g20f2020_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.025, pruned for LD and Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004420.rdf
Name: dapc_assigned_genetic_cluster_g90maf025_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.025 and pruned for LD</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004421.rdf
Name: dapc_assigned_genetic_cluster_g90maf025_g20f2020
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.025 and pruned for Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004422.rdf
Name: dapc_assigned_genetic_cluster_g90maf025
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.025</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004423.rdf
Name: dapc_assigned_genetic_cluster_g90maf05_g20f2020_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.05, pruned for LD and Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004424.rdf
Name: dapc_assigned_genetic_cluster_g90maf05_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.05 and pruned for LD</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004425.rdf
Name: dapc_assigned_genetic_cluster_g90maf05_g20f2020
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.05 and pruned for Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004426.rdf
Name: dapc_assigned_genetic_cluster_g90maf05
Units: unitless
Description: <p>Individual genetic cluster assignments using DAPC approach with SNP set filtered for MAF > 0.05</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004427.rdf
Name: snmf_primary_ancestry_cluster_g90maf01_g20f2020_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.01, pruned for LD and Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004428.rdf
Name: snmf_primary_ancestry_cluster_g90maf01_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.01 and pruned for LD</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004429.rdf
Name: snmf_primary_ancestry_cluster_g90maf01_g20f2020
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.01 and pruned for Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004430.rdf
Name: snmf_primary_ancestry_cluster_g90maf01
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.01</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004431.rdf
Name: snmf_primary_ancestry_cluster_g90maf025_g20f2020_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.025, pruned for LD and Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004432.rdf
Name: snmf_primary_ancestry_cluster_g90maf025_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.025 and pruned for LD</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004433.rdf
Name: snmf_primary_ancestry_cluster_g90maf025_g20f2020
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.025 and pruned for Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004434.rdf
Name: snmf_primary_ancestry_cluster_g90maf025
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.025</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004435.rdf
Name: snmf_primary_ancestry_cluster_g90maf05_g20f2020_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.05, pruned for LD and Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004436.rdf
Name: snmf_primary_ancestry_cluster_g90maf05_ldprunedrsq05
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.05 and pruned for LD</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004437.rdf
Name: snmf_primary_ancestry_cluster_g90maf05_g20f2020
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.05 and pruned for Fall 2020 missing data</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004438.rdf
Name: snmf_primary_ancestry_cluster_g90maf05
Units: unitless
Description: <p>Individual genetic cluster assignments using sNMF approach with SNP set filtered for MAF > 0.05</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
https://osprey.bco-dmo.org/dataset/1004242/data/download
download
onLine
dataset
<p>These data were published in Truskey et al. 2025 (Evolutionary Applications). All figure numbers and supplementary materials mentioned refer to Truskey et al. 2025 (Evolutionary Applications).</p>
<p><strong>Restoration experiment and sample collection</strong></p>
<p>In April 2017, we collaborated with local oyster farmers to source oyster eyed-larvae from four commercial hatcheries for the construction of new experimental oyster reefs in Ninigret Pond (Charlestown, Rhode Island, USA). Hatchery sources were selected across a broad geographic sampling range to maximize diversity (Figure&nbsp;1a of Truskey et al. 2025). They included two regional hatcheries, one from Massachusetts (MA) and one from New York (NY), and two more distant hatcheries, one from Maine (ME) and one from Virginia (VA). A local Rhode Island hatchery facility received oyster eyed-larvae from each source hatchery, set the eyed-larvae on dead oyster and/or clam shell (hereafter referred to as spat-on-shell oysters), and distributed the spat-on-shell oysters to three local oyster growers (Grower 1: MA; Grower 2: ME, NY, VA; Grower 3: NY, VA) who maintained these juvenile oysters on separate leased oyster farm plots prior to reef construction. Immediately prior to reef construction, we collected 20 juvenile spat-on-shell oysters from each grower-hatchery source combination for genetic analysis (<em>n</em> = 6 combinations; Grower 1-MA; Grower 2-ME; Grower 2-NY; Grower 2-VA; Grower 3-NY; Grower 3-VA).</p>
<p>In October and November 2017, we constructed 16 subtidal reefs within a no-harvest Shellfish Management Area in Ninigret Pond. Reefs were created across four 0.025-acre experimental blocks, with four reefs per block (Figure&nbsp;2 of Truskey et al. 2025). Each reef consisted of a base layer of 0.25 cubic yards of dead oyster or clam shell deployed in October and topped with 1.25 cubic yards of spat-on-shell oysters in early November from the stock grown out by the local oyster growers. Our experiment was originally designed to seed three reefs per block with a different single hatchery source from the four available hatchery sources and to seed the fourth reef per block with a mixed combination of the three sources (e.g., Reef 1: ME, Reef 2: MA, Reef 3: NY, Reef 4: ME+MA+NY). However, analysis of the hatchery samples from oyster growers collected prior to reef construction revealed an early, unintended mixing of some of the sources (Appendix&nbsp;S1 of Truskey et al. 2025; Figure&nbsp;S1 of Truskey et al. 2025), resulting in mixtures of multiple sources on 12 out of the 16 constructed reefs. Thus, we focused our analyses on the actual genetic composition of each reef as determined by genetic sampling at two time points (fall 2018, fall 2020).&nbsp;</p>
<p>In fall 2018, we haphazardly sampled live oysters from each reef on scuba or snorkel (<em>N</em> = 512 individuals total, 32 per reef). Oysters were put on ice and transported to the Northeastern University Marine Science Center where they were held at −80°C until DNA extraction. By the fall of 2020, live oyster densities on all experimental reefs had declined, reflecting mortality of the original planted oysters and a lack of recruitment, consistent with other data from this system (Barrett et&nbsp;al.&nbsp;2024). To assess whether this mortality was associated with a consistent change in the genetic composition of surviving oysters on reefs, we repeated our sampling in fall 2020 and compared the resulting reef genetic profiles to those from fall 2018. Reef sample sizes varied at this time point due to low live abundances (<em>N</em> = 249 individuals total, ranging from 8 to 32 per reef).</p>
<p><strong>DNA extraction, RADseq library preparation, and bioinformatics</strong></p>
<p>Genomic DNA was extracted using the E-Z 96 Tissue DNA Kit (Omega-Biotek, Norcross, GA) following the animal tissue protocol with tissue centrifugation. Double-digest restriction-site-associated DNA (ddRAD) libraries with individually barcoded samples were prepared in three batches following Parchman et al. (2012): (1) initial hatchery samples (n = 120), (2) fall 2018 reef samples (n = 480; 30 oysters per reef across 16 reefs), and (3) fall 2020 reef samples (n = 248). For additional details on ddRAD library preparation, see Appendix S2 of Truskey et al. 2025. All libraries were sequenced with 100-bp single-end reads on an Illumina platform. The initial and fall 2020 batches were sequenced on a single lane of the Illumina HiSeq 2500 at Tufts University Core Facility Genomics; the fall 2018 batch was sequenced on two lanes of the Illumina NovaSeq 6000 at the University of Texas at Austin Genomic Sequencing and Analysis Facility.</p>
Specified by the Principal Investigator(s)
<p><strong>SNP calling, filtering, and defining datasets</strong></p>
<p>Raw sequence quality was assessed with FastQC v0.11.9 (Andrews 2010), and files were demultiplexed using the process_radtags function in STACKS v2.41 (Catchen et al. 2013). Read trimming, mapping, SNP calling, and genotyping were performed with the dDocent pipeline v2.9.4 (Puritz et al. 2014), with reads mapped to the <em>C. virginica</em> genome pruned for haplotigs (Puritz et al. 2024). Variant calling was performed using Freebayes v1.3.6 (Garrison and Marth 2012). SNP loci were then filtered using vcftools v0.1.16 (Danecek et al. 2011) following standard iterative quality filtering procedures for RADseq-generated SNP data (O'Leary et al. 2018), including filters for minor allele count, base quality, genotype call rate, and read depth, followed by individual-level filtering for missing data. Because genetic assignment approaches can be sensitive to the SNP dataset used, we generated 12 SNP sets varying in minor allele frequency (MAF) threshold, locus-level filtering for missingness specific to the fall 2020 library, and pruning for high linkage disequilibrium (LD), to evaluate the robustness of downstream genetic cluster assignments to these bioinformatic decisions. Filtering outcomes for each SNP set are detailed in Table S1 of Truskey et al. 2025.</p>
<p><strong>Individual genetic assignments</strong></p>
<p>Individual genetic assignments to one of four genetic clusters (K = 4) were generated using discriminant analysis of principal components (DAPC; adegenet v2.1.10, Jombart 2008) and sparse non-negative matrix factorization (sNMF; LEA v3.10.0, Frichot and Francois 2015), applied independently to each of the 12 SNP sets, yielding 24 genetic assignment sets in total. Both approaches supported an optimal K = 4 (Figures S3-S4 of Truskey et al. 2025). For sNMF, individual assignments reflect the single cluster assignment with the highest admixture coefficient under K = 4. The primary genetic assignment referred to in the dataset and used in downstream analyses reflects DAPC assignments from the LD-pruned SNP set filtered for MAF &gt; 0.01 and fall 2020 library-specific missingness. Additional details on DAPC and sNMF runs and outcomes are provided in Appendix S3 of Truskey et al. 2025.</p>
<p>The individuals presented in this dataset are those retained after SNP filtering steps and not sampled from single-source reefs at the start of the experiment in fall 2018 as reflected by the individual genetic assignments. Genetic assignments for all individuals retained after SNP filtering (n=803), including those from single-source fall 2018 reefs, are provided in the related Sequence Metadata dataset.</p>
Specified by the Principal Investigator(s)
- Loaded table Truskey_EVA2025_ind_genetic_assignments_combined_bcodmo.csv, using filename as table name, with header row on row 1; set missing value sentinels to "", "nd", and "NA"
- Exported file as 1004242_v1_ind_genetic_assignments.csv
Specified by BCO-DMO Data Managers
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Illumina HiSeq 2500
Illumina HiSeq 2500
PI Supplied Instrument Name: Illumina HiSeq 2500 PI Supplied Instrument Description:The initial and fall 2020 batches were sequenced on a single lane of the Illumina HiSeq 2500 at Tufts University Core Facility Genomics; the fall 2018 batch was sequenced on two lanes of the Illumina NovaSeq 6000 at the University of Texas at Austin Genomic Sequencing and Analysis Facility. 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.
Illumina NovaSeq 6000
Illumina NovaSeq 6000
PI Supplied Instrument Name: Illumina NovaSeq 6000 PI Supplied Instrument Description:The initial and fall 2020 batches were sequenced on a single lane of the Illumina HiSeq 2500 at Tufts University Core Facility Genomics; the fall 2018 batch was sequenced on two lanes of the Illumina NovaSeq 6000 at the University of Texas at Austin Genomic Sequencing and Analysis Facility. 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.
PI Supplied Instrument Name: PI Supplied Instrument Description:In fall 2018, we haphazardly sampled live oysters from each reef on scuba or snorkel (N = 512 individuals total, 32 per reef). Oysters were put on ice and transported to the Northeastern University Marine Science Center where they were held at −80°C until DNA extraction. Instrument Name: Manual Biota Sampler Instrument Short Name:Manual Biota Sampler Instrument Description: "Manual Biota Sampler" indicates that a sample was collected in situ by a person, possibly using a hand-held collection device such as a jar, a net, or their hands. This term could also refer to a simple tool like a hammer, saw, or other hand-held tool. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/90/
scuba
scuba
PI Supplied Instrument Name: scuba PI Supplied Instrument Description:In fall 2018, we haphazardly sampled live oysters from each reef on scuba or snorkel (N = 512 individuals total, 32 per reef). Oysters were put on ice and transported to the Northeastern University Marine Science Center where they were held at −80°C until DNA extraction. 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