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, Mirella Flores, Naftali Panitz, Ryan S. Preble, Afolabi Agbona, Ismail Rabbi, Peter Kulakow, Prasad Peteti, Robert KawukiWilliams Esuma, Micheal Kanaabi, Doreen M. Chelangat, Ezenwanyi Uba, Adeyemi Olojede, Joseph Onyeka, Trushar Shah, Margaret Karanja, Chiedozie Egesi, Hale Tufan, Agre Paterne, Asrat Asfaw, Jean Luc Jannink, Marnin Wolfe, Clay L. Birkett, David J. Waring, Jenna M. Hershberger, Michael A. Gore, Kelly R. Robbins, Trevor Rife, Chaney Courtney, Jesse Poland, Elizabeth Arnaud, Marie Angelique Laporte, Heneriko Kulembeka, Kasele Salum, Emmanuel Mrema, Allan Brown, Stanley Bayo, Brigitte Uwimana, Violet Akech, Craig Yencho, Bert De Boeck, Hugo Campos, Rony Swennen, Jeremy D. Edwards, Lukas A. Mueller

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish (US)
JournalG3: Genes, Genomes, Genetics
Volume12
Issue number7
DOIs
StatePublished - Jul 1 2022
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)

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