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ARS Home » Southeast Area » Stuttgart, Arkansas » Dale Bumpers National Rice Research Center » Research » Publications at this Location » Publication #337558

Title: Ricebase - a resource for rice breeding

Author
item Edwards, Jeremy

Submitted to: Plant and Animal Genome
Publication Type: Abstract Only
Publication Acceptance Date: 12/2/2016
Publication Date: 1/18/2017
Citation: Edwards, J. 2017. Ricebase - a resource for rice breeding. Plant and Animal Genome. doi:10.106/j.fcr.2017.01.015.

Interpretive Summary:

Technical Abstract: Ricebase combines accessions, traits, markers, and genes with genome-scale datasets to empower rice breeders and geneticists to explore big-data resources. The underlying code and schema are shared with CassavaBase and the Sol Genomics Network (SGN) databases. Ricebase was launched specifically to meet critical needs of the rice research community. Accessions, phenotypes and genotypes are stored in a relational database using the Chado schema. Pedigree relationships are stored allowing users to traverse through genetic relationships between accessions. A unique feature of Ricebase is that it contains pseudomolecule positions on the latest assembly for the majority of rice SSR markers. This is critical for linking the bulk of published rice SSR-based genetic studies to current genome-based studies. A JBrowse instance is available to browse the rice genome and overlay various data tracks. The SSR marker locations are available as a data track along with published SNP datasets including the 3000 genome resequencing, high density rice diversity panels, and resequenced US elite lines. SNP effect predictions are available for all SNP data sets. Frequently, Ricebase has been used to develop additional markers for fine mapping, especially when transitioning from SSR markers to SNPs, and also for candidate gene exploration around significant markers detected in QTL/GWAS studies. Continuing enhancements to Ricebase will focus on community curation efforts involving rice breeders to help identify lists of genes, alleles, and validated markers that are useful for marker assisted selection.