The GRIN-Global Project

GRIN-Global (GG) is a database application that enables genebanks to store and manage information associated with plant genetic resources (germplasm) and deliver that information globally. The GRIN-Global project's mission is to provide a scalable version of the Germplasm Resource Information Network (GRIN) suitable for use by any interested genebank in the world.

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Maize Genetics Cooperation Stock Center Catalog of Stocks

The Maize Genetics Cooperation Stock Center is operated by USDA/ARS, located at the University of Illinois, Urbana/Champaign, and integrated with the National Plant Germplasm System (NPGS). The center serves the maize research community by collecting, maintaining and distributing seeds of maize genetic stocks, and providing information about maize stocks and the mutations they carry through the Maize Genetics and Genomics Database (MaizeGDB).

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Genome Database for Vaccinium

The Genome Database for Vaccinium (GDV) is a curated and integrated web-based relational database. The GDV is being developed to house and integrate genomic, genetic and breeding data for blueberry, cranberry and other Vaccinium species. The GDV will include the blueberry genome being sequenced by North Carolina State University, and annotated transcripts, traits, maps and markers being generated by Vaccinium researchers.

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Citrus Genome Database

The Citrus Genome Database, known as CGD, is a USDA and NSF funded resource to enable basic, translational and applied research in citrus. It houses genomics, genetics and breeding data for citrus species and organisms associated with HLB. It is built by the Mainlab at Washingotn State University using the open-source, generic database platform Tripal.

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National Plant Germplasm System

The U.S. National Plant Germplasm System (NPGS) is collaborative effort to safeguard the genetic diversity of agriculturally important plants.

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National Invertebrate Genetic Resources

Insects impact American agriculture both as destructive and beneficial organisms. Insect pests, parasites, predators, products, and pollinators are all economically important. It is critically important to distinguish between different species, races, stocks, strains, biotypes, and other genetic entities and to document their different interactions with agriculture and the environment. The goals of the National Invertebrate Genetic Resources Program include: 1. Preservation of reference specimens 2. Maintenance of genetically important germplasm 3. Documentation of specific insect stocks 4. Management of databases 5. Distribution of material to researchers and breeders.

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TreeGenes

The TreeGenes database provides custom informatics tools to manage the flood of information resulting from high-throughput genomics projects in forest trees from sample collection to downstream analysis. This resource is enhanced with systems that are well connected with federated databases, automated data flows, machine learning analysis, standardized annotations and quality control processes. The database itself contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools.

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Cool Season Food Legume Crop Database Resources

Genomic, Genetic and Breeding Resources for Pea, Lentil, Chickpea and Faba Bean Crop Improvement. The database contains genes, genomes, germplasm, maps, markers, QTL/MTL, species information, and transcripts.

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Gramene

Gramene is a curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species.

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The Animal Quantitative Trait Loci Database (Animal QTLdb)

The Animal Quantitative Trait Loci (QTL) Database (Animal QTLdb) strives to collect all publicly available trait mapping data, i.e. QTL (phenotype/expression, eQTL), candidate gene and association data (GWAS), and copy number variations (CNV) mapped to livestock animal genomes, in order to facilitate locating and comparing discoveries within and between species. New data and database tools are continually developed to align various trait mapping data to map-based genome features such as annotated genes.

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