14:I[71133,["4507","static/chunks/e2799680-446c489506865058.js","7665","static/chunks/7665-81c5407bc4489ff9.js","8500","static/chunks/8500-e4dd1cb1bb626827.js","9753","static/chunks/9753-028c0a26aa71f2d4.js","8437","static/chunks/8437-a09d0b83fcec76af.js","4557","static/chunks/4557-64c5efa221bc528f.js","947","static/chunks/947-410627998426400f.js","5357","static/chunks/5357-6142894e88cb7da2.js","8382","static/chunks/app/dataset/%5Bid%5D/data/view/page-177ea8adea7aed86.js"],"default"] 15:T5af,

Source populations for monoculture treatments included six wild populations and two proprietary broodstock lines (DEBY and LOLA) from the Aquaculture Genetics and Breeding Technology Center (ABC), Virginia Institute of Marine Science (VIMS). Wild populations spanned the species’ native range, which is structured into distinct genetic clusters separated by the Florida peninsula (Reeb & Avise, 1990, Puritz et al., 2022). Populations included oysters from: a variable salinity site in Texas (W1-TX), a low salinity site in Louisiana (W2-LA), a high salinity site on the east coast of Florida (W3-FL), a moderate salinity site in the James River, Virginia (W4-VA), a variable salinity site in New Hampshire (W5-NH), and a high salinity site in Maine (W6-ME). W4-VA was considered local to both common garden sites due to its geographic proximity and intermediate salinity.

Gill tissue was collected from each parent (n = 160) after spawning and stored in 95% ethanol at -80°C. DNA was extracted using the Qiagen DNeasy Blood and Tissue Kit and shipped to Neogen Genomics (Lincoln, NE) for genotyping on a 200K ThermoFisher Affymetrix Axiom SNP array derived from a 600K array (Gómez-Chiarri et al., 2015; Guo et al., 2023; Modak et al., 2021; Puritz et al., 2024) aligned to the haplotig-masked Crassostrea virginica reference genome (C_virginica-3.0, GCA_002022765.4) under NCBI BioProject PRJNA376014.

16:T6dd,

Raw genotypes were processed and filtered in R v4.4.2 (R Core Team 2025). Missing SNPs were imputed using LEA v3.6.0 (Frichot & François, 2015) with K = 2 ancestral groups to produce a full SNP set. We thinned SNPs for linkage disequilibrium (LD) for population structure analysis and neutral parameterization of genome scans (Lotterhos, 2019) using bigsnpr v1.11.3 (Privé et al., 2018). The archived genotype matrix contains the processed, imputed genotype calls per individual encoded in 0/1/2 integer format (homozygous reference, heterozygous, and homozygous alternate, respectively). The accompanying SNP metadata file provides per-locus descriptions including genomic position, gene identifiers, functional descriptions, Gene Ontology terms, and population genetic statistics derived from OutFLANK (FST, expected heterozygosity, p-values, q-values, and outlier flags), as well as a flag indicating inclusion in the LD-thinned dataset, enabling straightforward filtering for only LD-thinned SNPs.

The genotype data are provided as Exp_parents_full_SNP_matrix.rds, an RDS (R Data Serialization) binary file readable in R via readRDS(). The genotype data are also provided as a csv file Exp_parents_full_SNP_matrix.csv. These files contain a processed, imputed SNP genotype matrix with individuals as rows and loci as columns, encoded in 0/1/2 integer format. Genotyping, quality filtering, imputation, and formatting were performed using the code in the associated GitHub repository (https://github.com/DrK-Lo/MVP-H2F-HatcheryField). Code used to generate these files can be found in the /src/parental_genetics directory. The genotype data was generated on June 6, 2025.

17:Tb63,Curation Actions Performed on Data - Loaded Exp_parents_SNP_metadata.csv as table 998738_v1_oyster-genotype-annotations, format csv, headers row 1, empty string treated as missing value - Updated column metadata (bcodmo: descriptions, standard_name_id, supplied_units) for columns including AX-ID, Affx_ID, Chromosome, FST, Group, He, OutlierFlag, Position, Rank, Replicates, SNPType, Sequence, Tile_Std, Tile_max, Tile_v3, chrom_position, cust_id, gene_description, gene_id, go_ids, go_terms, mutID, on_oystercv, organism, pvalues, pvaluesRightTail, qvalues, scaffold, thinned_dataset - Renamed column AX-ID to AX_ID - Set column types: AX_ID, Affx_ID, SNPType, Sequence, Group, OutlierFlag, cust_id, gene_description, gene_id, go_ids, go_terms, mutID, on_oystercv, organism, scaffold, thinned_dataset cast as string; Chromosome, Position, Rank, Replicates, Tile_Std, Tile_max, Tile_v3 cast as integer; FST, He, chrom_position, pvalues, pvaluesRightTail, qvalues cast as number - Saved as final tables: 998738_v1_oyster-genotype-annotations.csv - Provided matrix file Exp_parents_full_SNP_matrix.csv attached as a data file directly. [not imported as a table]. Data in R-language format RDS attached as a supplmental file Exp_parents_full_SNP_matrix.rds (same data as file Exp_parents_full_SNP_matrix.csv, different format) Curation Actions Performed on Metadata * Standard metadata entry and formatting of provided metadata. * Data manager set the temporal and spatial bounds to the same lat lon and time range was used as the related Environmental dataset (See related datasets) which included the broodstock source population collection time and locations. Known Issues [Potentially Impacting Reuse] * Information for sites (lat,lons, etc) and information for source populations of parental broodstock genotyped were not included in this dataset directly. See Related Datasets where that information was provided. However, the exact way to associate that data with this dataset was not explicitly stated (shared keys not explained). However there is an implied association between site IDs and source populations/spawning treatment IDs due to the shared use of state abbreviations within the values (e.g. source population identified by "FL-KingPlan" may be from the FL site "W3_FL, 30.44003,-81.43638"). Further recommendations: * The related github repository was cited and included in the related publication section of this dataset. We provided our guidance page on https://guide.bco-dmo.org/prepare/software-and-code which describes recommendations for publishing code and associating with datasets. * no exact time or commit specified for exact linkage to this dataset version. * we suggested the authors archive the code for long term curation. And if that happens in the future they can reach out to us and we will add the code'd DOI to the data citation we use at BCO-DMO.18:T79b,This dataset contains SNP genotype and metadata for broodstock (parent) Eastern oysters (Crassostrea virginica) used in a multi-year common garden field experiment (2023–2025) as part of the project "CAREER: Evaluation of machine learning algorithms for understanding and predicting adaptation to multivariate environments with a Model Validation Program (MVP)" (NSF award #2043905 to Dr. Katie Lotterhos). The goal of the broader project is to assess the ability of machine learning algorithms (MLAs) to predict adaptation of organisms from their DNA sequences. Broodstock were sourced from six wild populations along the U.S. Atlantic and Gulf coasts and two hatchery selection lines. These parents were used in spawning treatments that included monocultures of each population or line, as well as two polyculture (mixed) treatments. The resulting juvenile oysters were deployed at two common garden sites in the Chesapeake Bay (Lewisetta, VA and York River, VA) and monitored over two years. Mortality and phenotype data were collected at six-month intervals to assess fitness across spawn treatments and garden sites, providing a field-based validation of MLA predictions. Broodstock were genotyped on a 200K ThermoFisher Affymetrix Axiom SNP array derived from a 600K array (Gómez-Chiarri et al., 2015; Guo et al., 2023; Modak et al., 2021; Puritz et al., 2024) and aligned to the haplotig-masked C. virginica reference genome (C_virginica-3.0, GCA_002022765.4). The data are archived as two files: (1) a SNP genotype matrix with processed, imputed genotype calls per individual in 0/1/2 integer format (homozygous reference, heterozygous, homozygous alternate), and (2) a SNP metadata file with per-locus information including SNP identifiers, genomic positions, gene annotations, Gene Ontology terms, and population genetic statistics from OutFLANK outlier detection (FST, expected heterozygosity, p-values, q-values, and outlier flags).19:T105c,NSF Award Abstract: Environmental change can be rapid and involve multiple aspects of the environment changing at the same time, such as warming and increased disease pressure. Rapid environmental change threatens the productivity of aquaculture and crops on which humans depend. Predicting organisms' vulnerabilities to rapid and multifactor environmental change, however, is a major scientific challenge. A hurdle to addressing this challenge arises from the complex and non-intuitive ways that organisms adapt, through changes at the level of the DNA sequence, to many environmental stresses at the same time. Thus, there is a need for new approaches to understand and predict adaptation in multivariate environments. To address this need, this project integrates research and education with a Model Validation Program (MVP). The research is developing and evaluating Machine Learning Algorithms (MLAs) for understanding and predicting adaptation of organisms to multivariate environments from their DNA sequences. To evaluate MLAs, this research combines both data simulation and an empirical test in the field with the Eastern Oyster, which provide important ecosystem services and support a multi-million dollar industry. For oysters, this research is studying how temperature, disease pressure, and salinity interact with evolutionary history to determine fitness in the field. This research advances efforts toward addressing the major scientific challenge of predicting adaptation in complex environments by integrating concepts across the frontiers of marine, evolutionary, and statistical sciences in a new way. Machine learning and model validation are not traditionally taught in the marine and environmental sciences, but are becoming increasingly relevant to these fields. As part of a broader education program, this research is developing MVP Learning Modules for high school students and undergraduates, which help students build the foundational knowledge they need to critically evaluate and apply models. Modules are being disseminated to hundreds of students in the greater Boston area and are being made available online for widespread use. The MVP mentoring program is training graduate students, undergraduates, and high school students in marine evolutionary ecology, statistical genomics, and machine learning. This research addresses a pressing societal need to more informatively match genotypes to environments for restoration, farming, and assisted gene flow efforts. Results are being disseminated to stakeholders in the oyster industry. The goal of this research is to evaluate if MLAs, which can model non-linearities, can be used to understand and predict adaptation to multivariate environments under a wide range of scenarios. In Objective 1, the Principal Investigator (PI) is creating simulated datasets with different aspects of realism, and using them to evaluate and refine the MLAs. This novel set of simulations is studying genome evolution under high gene flow in complex, multivariate environments. In Objective 2, the PI is building on their expertise with the Eastern oyster to evaluate the MLAs in a field setting. The PI is first developing a comprehensive seascape genomic dataset and using it to train MLAs to predict an individual's multivariate environment based on a single nucleotide polymorphism genotype. Then, the PI is testing if the MLA prediction can predict the fitness of different genotypes from across the species range when raised in common garden field conditions. In Objective 3, the PI is integrating research and education by using the data obtained from Objs. 1 and 2 to develop a series of original "MVP Learning Modules" with interactive web apps for persons at different levels of understanding, using the relatable example of an oyster restoration project. This research lays the foundation for future studies by producing datasets that could become classical examples for developing and benchmarking innovative modeling approaches. 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.6:["$","$L14",null,{"dataset":{"_id":"998738","description":"

Acronyms:

SNP = Single-nucleotide Polymorphism
\nMLA = Machine Learning Algorithm
\nLD = Linkage Disequilibrium
\nNCBI = National Center for Biotechnology Information
\nDNA = Deoxyribonucleic acid
\nMVP = Model Validation Program
\nABC = Aquaculture Genetics and Breeding Technology Center
\nVIMS = Virginia Institute of Marine Science
\nGO = Gene Ontology

Organism identifiers:
\nEastern oyster, Crassostrea virginica, urn:lsid:marinespecies.org:taxname:140657

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The metadata includes genomic location (chromosome, position, and scaffold on assembly GCF_002022765.2), gene-level functional annotations (gene IDs, functional descriptions, and Gene Ontology terms derived from the Ensembl Metazoa database and the C. virginica GFF3 annotation), population genetic statistics from OutFLANK outlier detection (FST, expected heterozygosity, p-values, q-values, and outlier status), array design parameters, and a flag indicating whether each SNP is included in the linkage disequilibrium-thinned dataset used for population structure analysis.","filename":"998738_v1_oyster-genotype-annotations.csv","bytesize":79797276,"checksum":{"value":"536a23d2553657e21ebb9419197e6adf","Algorithm":{"_id":"190","name":"MD5"}},"mimetype":"text/csv","fileType":{"_id":"192","name":"Comma Separated Values (.csv)"},"isErddap":"","date":"","isPublicDuringEmbargo":false,"primaryDataFile":true,"showTable":true,"restricted":false}],"supplemental_files":[{"id":"1009975","title":"Exp_parents_full_SNP_matrix.rds","url":"https://datadocs.bco-dmo.org/dataset/998738/file/KAg8pyLuZZvwPY/Exp_parents_full_SNP_matrix.rds","showTableUrl":"","description":"This file contains a numeric genotype matrix for Eastern oyster (Crassostrea virginica) SNPs genotyped on a 200K ThermoFisher Affymetrix Axiom SNP array. Rows represent individual samples (160 individuals total) and columns represent SNP loci (154102 SNPs total). Genotypes are encoded as integer values: 0 (homozygous reference), 1 (heterozygous), or 2 (homozygous alternate). Raw genotypes were processed and filtered in R v4.4.2 (R Core Team 2025), and missing genotypes were imputed using LEA v3.6.0 (Frichot & François, 2015) with K = 2 ancestral groups. SNP identifiers in the column headers correspond to the Affx_ID column in the accompanying SNP metadata file, which provides genomic coordinates, functional annotations, and population genetic statistics for each locus. RDS (R Data Serialization) format, readable in R using readRDS().\n\nThese data were exported as csv file Exp_parents_full_SNP_matrix.csv for interoperability purposes. The files contain the same data in a different format.","filename":"Exp_parents_full_SNP_matrix.rds","bytesize":6972970,"checksum":{"value":"ce3e9e1e6fe7f899aff98f0cf8ca750b","Algorithm":{"_id":"190","name":"MD5"}},"mimetype":"application/octet-stream","fileType":{"_id":"419","name":"Octet Stream"},"isErddap":"","date":"","isPublicDuringEmbargo":false,"primaryDataFile":false,"showTable":false,"restricted":false}],"roles":[{"role":{"_id":"138","name":"Principal Investigator"},"performedBy":{"_id":"666501","name":"Katie Lotterhos"},"performedAtOrganization":{"_id":"490462","name":"Northeastern University"}},{"role":{"_id":"140","name":"Co-Principal Investigator"},"performedBy":{"_id":"998755","name":"Jessica Small"},"performedAtOrganization":{"_id":"65","name":"Virginia Institute of Marine Science"}},{"role":{"_id":"130","name":"Scientist"},"performedBy":{"_id":"998758","name":"Ryan Carnegie"},"performedAtOrganization":{"_id":"65","name":"Virginia Institute of Marine Science"}},{"role":{"_id":"128","name":"Student"},"performedBy":{"_id":"998742","name":"Kiran Bajaj"},"performedAtOrganization":{"_id":"490462","name":"Northeastern University"}},{"role":{"_id":"128","name":"Student"},"performedBy":{"_id":"998745","name":"Madeline Eppley"},"performedAtOrganization":{"_id":"490462","name":"Northeastern University"}},{"role":{"_id":"128","name":"Student"},"performedBy":{"_id":"998761","name":"Shelley Katsuki"},"performedAtOrganization":{"_id":"65","name":"Virginia Institute of Marine Science"}},{"role":{"_id":"128","name":"Student"},"performedBy":{"_id":"998751","name":"Nicole Mongillo"},"performedAtOrganization":{"_id":"490462","name":"Northeastern University"}},{"role":{"_id":"128","name":"Student"},"performedBy":{"_id":"998748","name":"Camille Rumberger"},"performedAtOrganization":{"_id":"490462","name":"Northeastern University"}},{"role":{"_id":"128","name":"Student"},"performedBy":{"_id":"998764","name":"Zea Segnitz"},"performedAtOrganization":{"_id":"490462","name":"Northeastern University"}},{"role":{"_id":"145","name":"BCO-DMO Data Manager"},"performedBy":{"_id":"643627","name":"Amber D. York"},"performedAtOrganization":{"_id":"191","name":"Woods Hole Oceanographic Institution"}}],"deployments":[],"funding":[{"_id":"876609","name":"OCE-2043905","fundingSource":{"_id":"355","name":"NSF Division of Ocean Sciences"},"url":"https://www.nsf.gov/awardsearch/show-award?AWD_ID=2043905"}],"instruments":[],"parameters":[{"_id":"998837","name":"Affx_ID","format":"","frictionlessType":"string","description":"

Thermofisher SNP identifiers that refer to the specific probe or probe set as it was designed for the array

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998838","name":"AX_ID","format":"","frictionlessType":"string","description":"

Thermofisher analysis-ready SNP identifiers that are assigned after the array is finalized

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998839","name":"Chromosome","format":"","frictionlessType":"integer","description":"

Chromosome where SNP occurs on assembly GCF_002022765.2_C_virginica-3.0_genomic

","units":{"_id":"","name":"unitless"},"type":{"_id":"759","name":"brief_desc","description":"

brief description, open ended, specific to the data set in which it appears

"}},{"_id":"998840","name":"Position","format":"","frictionlessType":"integer","description":"

Chromosomal position where SNP occurs on assembly GCF_002022765.2_C_virginica-3.0_genomic

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998841","name":"FST","format":"","frictionlessType":"number","description":"

Fixation index for the locus calculated by OutFLANK (Whitlock and Lotterhos 2015)

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998842","name":"He","format":"","frictionlessType":"number","description":"

Expected heterozygosity for the locus calculated by OutFLANK (Whitlock and Lotterhos 2015)

","units":{"_id":"","name":"unitless"},"type":{"_id":"759","name":"brief_desc","description":"

brief description, open ended, specific to the data set in which it appears

"}},{"_id":"998843","name":"pvalues","format":"","frictionlessType":"number","description":"

Two-tailed p-value for the test of neutrality for the locus calculated by OutFLANK (Whitlock and Lotterhos 2015)

","units":{"_id":"","name":"unitless"},"type":{"_id":"887009","name":"p-value","description":"

A quantitative confidence value that represents the probability of obtaining a result at least as extreme as that actually obtained, assuming that the actual value was the result of chance alone.

"}},{"_id":"998844","name":"pvaluesRightTail","format":"","frictionlessType":"number","description":"

Right-tailed p-value for the test of neutrality for the locus calculated by OutFLANK (Whitlock and Lotterhos 2015)

","units":{"_id":"","name":"unitless"},"type":{"_id":"1073","name":"no_bcodmo_term","description":"

An association with a community-wide standard parameter has not yet been made.

"}},{"_id":"998845","name":"qvalues","format":"","frictionlessType":"number","description":"

q-value for the test of neutrality for the locus based on the right-tailed p-value calculated by OutFLANK (Whitlock and Lotterhos 2015)

","units":{"_id":"","name":"unitless"},"type":{"_id":"1073","name":"no_bcodmo_term","description":"

An association with a community-wide standard parameter has not yet been made.

"}},{"_id":"998846","name":"OutlierFlag","format":"","frictionlessType":"string","description":"

True (T) or False (F) if the SNP was detected as an outlier by OutFLANK (Whitlock and Lotterhos 2015)

","units":{"_id":"","name":"unitless"},"type":{"_id":"1730","name":"flag","description":"

Data flag. Multiple uses which are dataset dependent. Some uses: data quality, collection occurrence or success, depth indicator. See dataset documentation for specific details

"}},{"_id":"998847","name":"gene_id","format":"","frictionlessType":"string","description":"

Generic locus IDs (NCBI) for gene(s) where SNP occurs

","units":{"_id":"","name":"unitless"},"type":{"_id":"995410","name":"gene_id","description":"

A unique (and typically persistent) identifier of a gene in a database, that is (typically) different to the gene name/symbol.

"}},{"_id":"998848","name":"gene_description","format":"","frictionlessType":"string","description":"

Functional description(s) of gene(s) where SNP occurs

","units":{"_id":"","name":"unitless"},"type":{"_id":"759","name":"brief_desc","description":"

brief description, open ended, specific to the data set in which it appears

"}},{"_id":"998849","name":"go_ids","format":"","frictionlessType":"string","description":"

Unique seven-digit identifier for a gene ontology term

","units":{"_id":"","name":"unitless"},"type":{"_id":"1971","name":"accession number","description":"

Database identifier assigned by repository and linked to GenBank or other repository.

"}},{"_id":"998850","name":"go_terms","format":"","frictionlessType":"string","description":"

Description for a gene ontology term

","units":{"_id":"","name":"unitless"},"type":{"_id":"759","name":"brief_desc","description":"

brief description, open ended, specific to the data set in which it appears

"}},{"_id":"998851","name":"SNPType","format":"","frictionlessType":"string","description":"

SNPType. K - G/T M - A/C R - A/G (most common) S - C/G (rarest) W - A/T Y - C/T (most common)

","units":{"_id":"","name":"unitless"},"type":{"_id":"759","name":"brief_desc","description":"

brief description, open ended, specific to the data set in which it appears

"}},{"_id":"998852","name":"Tile_Std","format":"","frictionlessType":"integer","description":"

Affymetrix parameter for SNP chip design

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998853","name":"Tile_max","format":"","frictionlessType":"integer","description":"

Affymetrix parameter for SNP chip design

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998854","name":"Tile_v3","format":"","frictionlessType":"integer","description":"

SNPs tiled on the 200K chip

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998855","name":"Replicates","format":"","frictionlessType":"integer","description":"

Affymetrix parameter for SNP chip design

","units":{"_id":"","name":"unitless"},"type":{"_id":"953","name":"replicate","description":"

an identifier used to distinguish between one or more replicate samples

"}},{"_id":"998856","name":"Rank","format":"","frictionlessType":"integer","description":"

Affymetrix parameter for SNP chip design

","units":{"_id":"","name":"unitless"},"type":{"_id":"759","name":"brief_desc","description":"

brief description, open ended, specific to the data set in which it appears

"}},{"_id":"998857","name":"Group","format":"","frictionlessType":"string","description":"

pathogen detection CN probesets, content of Axiom_OysterCV, additional well-performing markers from screen

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"998858","name":"organism","format":"","frictionlessType":"string","description":"

Genus species

","units":{"_id":"","name":"unitless"},"type":{"_id":"994","name":"taxon","description":"

taxonomic group or entity. This may be a family, class, genus, species, etc.; usually this parameter will contain a mixture of taxonomic entities.

"}},{"_id":"998859","name":"cust_id","format":"","frictionlessType":"string","description":"

Annotation

","units":{"_id":"","name":"unitless"},"type":{"_id":"1073","name":"no_bcodmo_term","description":"

An association with a community-wide standard parameter has not yet been made.

"}},{"_id":"998860","name":"on_oystercv","format":"","frictionlessType":"string","description":"

on Axiom_OysterCV developed be Breeding Consortium

","units":{"_id":"","name":"unitless"},"type":{"_id":"759","name":"brief_desc","description":"

brief description, open ended, specific to the data set in which it appears

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Mutation ID Affymetrix parameter for SNP chip design

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text description or other traits of the sample collected

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Chromosome location and position of SNP on the 200K array; separated by a '.'

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text description or other traits of the sample collected

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Scaffold on assembly GCF_002022765.2_C_virginica-3.0_genomic

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text description or other traits of the sample collected

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71mer sequence

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A genetic sequence; e.g. the order of nucleotides in DNA or RNA

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True or False if the SNP occurs in the linkage-disequilibrium thinned SNP dataset

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brief description, open ended, specific to the data set in which it appears

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The dataset is related to another dataset.

\n","relation_desc":"The experimental results dataset (1007522) includes fitness data and metadata from a common garden experiment run as part of the CviMVP project from 2023-2025. In the experiment juvenile oysters were transplanted to two sites to assess fitness across environments. These juveniles were spawned from a set of parental oysters, and data and metadata on that parental generation (used to produce the juveniles for this experiment) are contained in a separate dataset (1008652). Additional genotype information for the parent oysters is provided in dataset (998738). Environmental data from the experiment is in dataset 1007572.","citation":"K. Eaton, A., Lotterhos, K., Rumberger, C., Eppley, M., Bajaj, K., Mongillo, N., Small, J., Carnegie, R., Segnitz, Z., Armstrong, M. (2026) Parent eastern oysters (Crassostrea virginica) from wild and hatchery populations along U.S. Atlantic and Gulf coasts (collected 2022), used as broodstock in a field experiment (2023–2025). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2026-09-30 http://lod.bco-dmo.org/id/dataset/1008652"},{"_id":"","name":"","url":"https://github.com/DrK-Lo/MVP-H2F-HatcheryField","relation_type":"Software","type_desc":"The software that was used to derive this data.","relation_desc":"This repository contains data and code for a hatchery-to-field (H2F) experiment evaluating survival, growth, and genetic predictors of performance in Eastern oysters (Crassostrea virginica), part of the project \"CAREER: Evaluation of machine learning algorithms for understanding and predicting adaptation to multivariate environments with a Model Validation Program (MVP)\" (NSF award #2043905, PI: Dr. Katie Lotterhos).\r\n\r\nThis repository contains the analysis code and the same data as this BCO-DMO dataset in the exact format used in the analysis. (See BCO-DMO Processing notes for changes made to this BCO-DMO dataset to support data reuse and interoperability.","citation":"Bajaj, K., Eppley, M., Rumberger, C., Mongillo, N., Lotterhos, K., & Segnitz, Z. (n.d.). MVP-H2F-HatcheryField: MVP experimental data hatchery to field [Source code]. GitHub. https://github.com/DrK-Lo/MVP-H2F-HatcheryField"},{"_id":"","name":"","url":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA376014","relation_type":"IsRelatedTo","type_desc":"The dataset is related to another dataset.","relation_desc":"NCBI BioProject with the related sequences and sample information in BioSample SAMN06349363.","citation":"McDonnell Genome Institute - Washington University School of Medicine (2017). Crassostrea virginica Genome sequencing and assembly. 2017/03. NCBI:BioProject: PRJNA376014 [Internet]. Bethesda, MD: National Library of Medicine (US), National Center for Biotechnology Information; Available from: http://www.ncbi.nlm.nih.gov/bioproject/PRJNA376014"}],"services":[{"grouping":"","items":[{"name":"View Data","description":"An in-browser view of the primary tabular data file","url":"https://www.bco-dmo.org/dataset/998738/data/view","contentType":"text/html","actionType":"view"}]},{"grouping":"Metadata","items":[{"name":"HTML","description":"A simple HTML page of the dataset metadata","url":"https://www.bco-dmo.org/dataset/998738/description","contentType":"text/html","actionType":"view"},{"name":"PDF","description":"A PDF of the HTML dataset metadata","url":"https://www.bco-dmo.org/dataset/998738/Dataset_description.pdf","contentType":"application/pdf","actionType":"download"},{"name":"ISO 19115-2 (NOAA Profile)","description":"","url":"https://www.bco-dmo.org/dataset/998738/iso","contentType":"application/xml","actionType":"download"}]}],"programs":[],"projects":[{"_id":"876610","name":"CAREER: Evaluation of machine learning algorithms for understanding and predicting adaptation to multivariate environments with a Model Validation Program (MVP)","acronym":"Model Validation Program","description":"$19"}],"archives":[],"license":{"name":"Creative Commons Attribution 4.0","id":"CC-BY-4.0","uri":"https://creativecommons.org/licenses/by/4.0/","spdxUri":"https://spdx.org/licenses/CC-BY-4.0"},"metrics":{"views":{"count":72},"downloads":{"count":25}}}}]