1. Sook Jung, Taein Lee, Stephen Ficklin, Kate Evans, Cameron Peace and Dorrie Main

2. GDR: Genome database for Rosaceae Genomic, Genetic and Breeding data Other databases: CottonGen, Citrus Genome Database, Cool Season Food Legume Database, Genome Database for Vaccinium  Using open source tools for an efficient and flexible database construction (Chado, Tripal, Drupal)  Chado, with the recent Natural Diversity Module, allows integration of complex biological data from widely different projects and species Introduction

3. Part I: How to store data using Chado Part II: Demo of GDR Breeding Database Outline

4. Chado: Modular, Generic and Ontology-driven schema Feature Feature_id Name Uniquename Type_id Organism_id residues Feature_relationship Feature_relationship_id Subject_id Object_id Type_id Featureprop Featureprop_id Feature_id Type_id Value rank cvterm cvterm_id Name definition cv_id Dbxref_id gene, mRNA, marker, QTL, etc Abc- mRNA part_of Abc-gene Repeat_motif Product_size Subject_id object_id cv cv_id Name definition Sequence Ontology, Gene Ontology, etc

5. Storing Stock (from samples to population; pedigree) stock stock_id Name Uniquename Type_id Organism_id residues stock_relationship Feature_relationship_id Subject_id Object_id Type_id stockprop stockprop_id stock_id Type_id value cvterm cvterm_id Name definition cv_id Dbxref_id Population, cultivar, breeding line, clone, sample, etc Gala-001 sample_of Gala Description, population_size Subject_id object_id Gala Maternal_parent_of Sonya pedigree

6. Storing phenotype data (from measurements to projects) stock Feature_id Name Uniquename Type_id Organism_id residues nd_experiment Nd_experiment_id Nd_geolocation_id Type_id phenotype phenotype_id Uniquename value attr_id cvterm cvterm_id Name definition cv_id Dbxref_id Phenotyping Genotyping Cross_experiment project Featureprop_id Feature_id Type_id value NE_stock NE_phenoty pe project_relationsh ip NE_project

7. Genotypic data integrated with genomic/genetic data nd_experiment Nd_experiment_id Nd_geolocation_id Type_id genotype genotype_id name Uniquename description NE_genotype feature_genotype Feature Feature_id Name Uniquename Type_id Organism_id residues project stock uniquename: CPSCT038_190|192 description: 190:192 Uniquename:CPSCT038 Type:microsatellite map Explore sequences around marker in GBrowse

8. Relationship between genotype and phenotype (haplotype and haplotype effect) nd_experiment Nd_experiment_id Nd_geolocation_id Type_id genotype genotype_id name Uniquename description NE_genotype feature_genotype Feature Feature_id Name Uniquename Type_id Organism_id residues project stock uniquename: MA_H3|H4b description: H3|H4b Uniquename:Ma Type:MTL map phenotype phenotype_id Uniquename value attr_id NE_phenotype phenstatement phenstatement_id Type_id Genotype_id phenotype_id Environment pub attr_id: crisp value: 2.2 Germplasm with H3|H4b alleles of MA locus has value of 2.2 for crisp

9. Data Management (Browse, Search and Download) Data Conversion (Generate Input files for Pedimap) Decision Support Cross Assist Trait Locus Warehouse Marker Converter GDR Breeding Database Demo

10. 10 Phenotypic Data Search

11. 11

12. 12 Genotypic Data Search

13. o A web interface to generate a list of parents and the number of seedlings to get the progeny with desired traits o Methods  “Phenotype” (uses only phenotypic information of individuals in the dataset),  “+Pedigree” (uses both phenotypic and pedigree information)  “+Ped+DNA” (uses phenotypic, pedigree information and information provided by DNA- based functional genotypes). Cross Assist

14. Step 1: Select Method

15. Step 2: Select target number and trait thresholds

16. Step 3: Filter results by data completeness, required number of seedlings, and parentage

17. Future Development o Data  RosBreed QTLs and their genome positions  More breeding data and DNA based functional genotypes  More re-sequencing data o Functionality  Data management: online data submission and editing  Viewing data on screen and generating report pages  Decision support tools o Cross Assist: o to accommodate more complex situations (selfing, cross compatibility, etc) o To upload users’ own data o Further develop more tools

18. Natural diversity module working group Naama Menda, Seth Redmond, Robert M. Buels, Maren Friesen, Yuri Bendana, Lacey-Anne Sanderson, Hilmar Lapp, Taein Lee, Bob MacCallum, Kirstin E. Bett, Scott Cain, Dave Clements, Lukas A. Mueller and Dorrie Main Main Lab team All Project CoPIs (tfGDR, RosBreed and CottonGen) Funding Sources USDA NIFA SCRI, NSF Plant Genome Program, USDA-ARS, Washington Tree Fruit Research Commission, Cotton Incorporated, Washington State University, Clemson University, University of Florida, Boyce Thompson Institute, North Carolina State University Taein Lee Stephen Ficklin Chun-Huai Cheng Ping Zheng Anna Blenda Sushan Ru Dorrie Main Jing Yu Acknowledgement

19. Any Questions?