Based on the integrated datasets of these information systems, decisions for the optimization of the breeding process and curation of passport data can be derived.ĭue to constantly decreasing costs for DNA sequencing, ever more extensive sequencing projects can be carried out at constant or even further decreasing costs ( Shendure and Ji, 2008 Shendure et al., 2017). To accompany this process, information systems are needed that integrate the extensive amounts of derived multi-omics data and make them accessible and available in a FAIR manner ( Wilkinson et al., 2016). These methods allow to increasingly benefit from the putative advantageous alleles of the PGRFA, which have not yet been used in recent breeding efforts. The necessary continued crop improvement can be achieved by modern plant breeding methods like marker assisted selection ( Varshney et al., 2005 Crossa et al., 2017), reverse breeding ( Dirks et al., 2009), and genome engineering/editing ( Voytas and Gao, 2014). PGRFA hold a promise for the way of responding to this pressure through crop improvement and yield increase per hectare. In prospect of the upcoming challenges of continued growth of the world population, climate change, and increasing scarcity of resources like arable land, water, and fertilizers enhances the pressure on agriculture to provide humankind with sufficient food ( Pachauri et al., 2015 FAO, 2018). The German Federal ex situ genebank hosted at the Leibniz Institute of Plant Genetics and Crop Plant Research in Gatersleben hosts more than 22,000 barley accessions consisting of wild relatives, landraces, and breeding material collected over the past 70 years ( Nagel et al., 2009 González et al., 2018 Milner et al., 2019). Large collections of plant genetic resources for food and agriculture (PGRFA) of diverse barley genotypes and phenotypes have been described in the literature ( Ullrich, 2010). With its diploid genome, inbreeding feature and in comparison to its relatives wheat and rye rather small genome size of 5.1 Gbp, barley is an excellent model for basic and applied research in the Triticeae tribe. Ĭereal grasses like barley, rye and wheat are the main nutrition source for human calorie intake in the world ( FAO, 2018). BRIDGE is accessible at the following URL. A search module to find and select germplasm by passport and phenotypic attributes is included as well as modules to export genotypic data in gzip-compressed variant call format (VCF) files and phenotypic data in MIAPPE-compliant ISA-Tab files. The core component is a manager for custom collections of germplasm. BRIDGE consists of interactively coupled modules to visualize integrated, curated and quality checked data, such as variation data, results of dimensionality reduction and genome wide association studies (GWAS), phenotyping results, passport data as well as the geographic distribution of germplasm samples. The underlying data resulted from a barley genebank genomics study cataloging sequence and morphological data of 22,626 barley accessions, mainly from the German Federal ex situ genebank. Using efficient technologies for data storage, data transfer and web development, we facilitate access to digital genebank resources of barley by prioritizing the interactive and visual analysis of integrated genotypic and phenotypic data. To support this process we have developed BRIDGE, a data warehouse and exploratory data analysis tool for genebank genomics of barley ( Hordeum vulgare L.). These requirements for improved plant cultivars can be supported by the broader exploitation of plant genetic resources (PGR) as inputs for genomics-assisted breeding. A growing world population and a changing climate require an increase in the production and development of stress resistant plant cultivars while decreasing the acreage. Genebanks harbor a large treasure trove of untapped plant genetic diversity. 3Center for Integrated Breeding Research, Georg-August University, Göttingen, Germany.2German Centre for Integrative Biodiversity Research (iDiv), Leipzig, Germany.1Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany.Patrick König 1*, Sebastian Beier 1, Martin Basterrechea 1, Danuta Schüler 1, Daniel Arend 1, Martin Mascher 1,2, Nils Stein 1,3, Uwe Scholz 1* and Matthias Lange 1
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