C20
GDR, the Genome Database for Rosaceae: New Data and Functionality

Date: Tuesday, January 12, 2016
Time: 12:25 PM
Room: California
Sook Jung , Washington State University, Pullman, WA
Taein Lee , Washington State University, Pullman, WA
Chun-Huai Cheng , Washington State University, Pullman, WA
Stephen P. Ficklin , Washington State University, Pullman, WA
Anna Blenda , Erskine College, Due West, SC
Ksenija Gasic , Clemson University, Clemson, SC
Jing Yu , Washington State University, Pullman, WA
Kristin Scott , Washington State University, Pullman, WA
Michael Byrd , Erskine College, Due West, SC
Sushan Ru , Washington State University, Pullman, WA
Katherine M. Evans , Washington State University, Wenatchee, WA
Cameron Peace , Washington State University, Pullman, WA
Lisa DeVetter , Washington State University, Pullman, WA
Nnadozie Oraguzie , Washington State University, Prosser, WA
Albert G. Abbott , Forest Health Research and Education Center, University of Kentucky, Lexington, KY
Mercy Olmstead , University of Florida, Gainesville, FL
Dorrie Main , Washington State University, Pullman, WA
The Genome Database for Rosaceae (GDR, http:/ www.rosaceae.org) is the central repository and data-mining resource for genomics, genetics, and breeding data of Rosaceae, an economically important crop family that includes almond, apple, blackberry, cherry, peach, pear, plum, raspberry, rose, and strawberry. GDR contains whole genome sequences and annotation, reference transcriptomes, gene sequences from NCBI, genetic maps, trait loci, germplasm, marker diversity, breeding and publication data. The predicted genes of the whole genome sequence, reference transcriptomes and NCBI genes have been further annotated by homology to genes in other species, InterPro protein domains, GO terms and KEGG pathway terms. In this computer demo, we update the users with the new data including new whole genome, genetic maps, trait loci and genotypic and phenotypic data from breeding projects. We also report our effort toward data standardization on gene names, QTL metadata, and trait ontology.