Breedbase: a digital ecosystem for modern plant breeding - Nicolas Morales; Alex C Ogbonna; Bryan J Ellerbrock; Guillaume J Bauchet; Titima Tantikanjana; Isaak Y Tecle; Adrian F Powell; David Lyon; Naama Menda; Christiano C Simoes; Surya Saha; Prashant Hosmani; et al. (G3: Genes, Genomes, Genetics, 2022)
AbstractModern 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 4/18/2022https://cassavabase.org/https://www.nextgencassava.org/https://github.com/solgenomics/https://hub.docker.com/u/breedbase