2013 ASHS Annual Conference

The Genome Database for Rosaceae (GDR, http://www.rosaceae.org) is an integrated database for genomic, genetic and breeding data. Rosaceae includes many economically important crops such as apple, peach, cherry, almond, raspberry, strawberry, pear, and rose. The GDR integrates genomic, genetic, and breeding data to facilitate data utilization across disciplines as well as across species. Current genomic data includes the annotated whole genome sequences of strawberry, peach, and apple that are available through GBrowse and download pages. In addition, all the Rosaceae sequences from NCBI have been anchored to the whole genome sequences of the closest genome where matches were found. New EST unigene sets have also been developed for major genera of Rosaceae. The predicted genes of the whole genome sequences, genes parsed from NCBI sequences, and EST unigenes have been further annotated by homology to genes in other species, InterPro protein domains, GO terms, and KEGG pathway terms provide a glimpse of the pathways and traits in which they are involved. The annotated sequence data can be browsed through the new species page or queried using various categories in the search sites. Pathway data can also be accessed through the GDR Cyc Pathways databases: FragariaCyc, AppleCyc, and PeachCyc. Synteny among the three sequenced genomes is also available through the graphic interface, GBrowse_Syn, to facilitate data utilization across species. Genetic data such as markers, QTLs, and genetic linkage maps are available through various search sites and graphic viewers. QTLs and markers from various maps can be compared using the comparative map viewer CMap and the markers that have been anchored to the genome can be viewed through GBrowse, facilitating the new marker development and the identification of underlying genes for the traits of interests. Breeding data, mostly from the RosBreed project, has also been integrated. The germplasm details and their phenotypic and genotypic data can be searched by datasets, germplasm names, trait thresholds, markers, and marker alleles. Tools that can facilitate Marker Assisted Breeding, such as Cross Assist, have also been developed.