GrainGenes: a data-rich repository for small grains genetics and genomics.

As one of the US Department of Agriculture-Agricultural Research Service flagship databases, GrainGenes (https://wheat.pw.usda.gov) serves the data and community needs of globally distributed small grains researchers for the genetic improvement of the Triticeae family and Avena species that include wheat, barley, rye and oat. GrainGenes accomplishes its mission by continually enriching its cross-linked data content following the findable, accessible, interoperable and reusable principles, enhancing and maintaining an intuitive web interface, creating tools to enable easy data access and establishing data connections within and between GrainGenes and other biological databases to facilitate knowledge discovery. GrainGenes operates within the biological database community, collaborates with curators and genome sequencing groups and contributes to the AgBioData Consortium and the International Wheat Initiative through the Wheat Information System (WheatIS). Interactive and linked content is paramount for successful biological databases and GrainGenes now has 2917 manually curated gene records, including 289 genes and 254 alleles from the Wheat Gene Catalogue (WGC). There are >4.8 million gene models in 51 genome browser assemblies, 6273 quantitative trait loci and >1.4 million genetic loci on 4756 genetic and physical maps contained within 443 mapping sets, complete with standardized metadata. Most notably, 50 new genome browsers that include outputs from the Wheat and Barley PanGenome projects have been created. We provide an example of an expression quantitative trait loci track on the International Wheat Genome Sequencing Consortium Chinese Spring wheat browser to demonstrate how genome browser tracks can be adapted for different data types. To help users benefit more from its data, GrainGenes created four tutorials available on YouTube. GrainGenes is executing its vision of service by continuously responding to the needs of the global small grains community by creating a centralized, long-term, interconnected data repository. Database URL:https://wheat.pw.usda.gov.

Breedbase: a digital ecosystem for modern plant breeding.

Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem.