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

Transcription

1 Outline GDR, the Genome Database for Rosaceae: New Data and Functionality Sook Jung, Taein Lee, Chun-Huai Cheng, Stephen Ficklin, Anna Blenda, Ksenija Gasic, Jing Yu, Kristin Scott, Michael Byrd, Sushan Ru, Kate Evans, Cameron Peace, Lisa DeVetter, Nnadozie Oraguzie, Albert Abbott, Mercy Olmstead, Dorrie Main Introduction Goals of GDR Available data and tools Effort toward data standardization (gene symbol, QTL metadata and trait ontology) Demo with exercises 1. Find sequences for DHN genes 2. Find apple and strawberry genomic regions that are in conserved syntenic regions with peach regions that contain QTL for SSC 3. Find apple varieties with an allele that are likely to be resistant to scab Future Directions Introduction Goals of GDR Current Data and Functionality Develop a genomic, genetic and breeding database and online analysis tools for Rosaceae Crop Improvement Develop/use ontologies in collaboration with the consortia to facilitate data sharing Content management system Biological schema Drupal modules for construction of biological web sites Develop bioinformatics community resources to facilitate sharing of tools Further develop search/data interface in Tripal BIMS in Tripal (compatible with the field data collecting App) Data for Almond, Apple, Apricot, Blackberry, Cherry, Peach, Pear, Raspberry, Rose, Strawberry Annotated peach, cultivated strawberry, diploid strawberries, pear and apple genome sequences Apple-peach-strawberry synteny available through GBrowse_Syn Curated Rosaceae gene database Annotated genera and family unigenes (v5) Pathway data (PeachCyc, FragariaCyc and AppleCyc) Data from SNP arrays of IRSC (9K apple, 9K peach and 6K cherry), 90K cultivated strawberry, 20K apple 68K Rose 160 Genetic maps Gene, EST, marker, trait, QTL, polymorphism, publications search modules Genotypic, phenotypic and breeding data for search and download Decision tools for breeders BLAST, GenSAS, CAP3, SSR, Sequence Retrieval online tools Effort towards data standardization 1. Standard gene nomenclature in the Rosaceae 2. QTL metadata 3. Rosaceae Trait ontology Standard Gene nomenclature 1. Developed by Rosaceae Gene Name Standardization Subcommittee 2. Published in Tree Genetics & Genomes in GDR pages for guidelines, gene class symbol browse page and gene data template 1

2 Standard Gene nomenclature (gene naming guideline page) Standard Gene nomenclature (gene class symbol page) QTL metadata standardization Data Templates 1. Standardized data templates available for Rosaceae (GDR), cool season food legumes (CSFL) and cotton (CottonGen) 2. Working with greater crop community (MOWG (metadata ontology working group) of AgBioData Rosaceae Trait Ontology 1. Development of Rosaceae Trait Ontology to describe trait in QTL data 2. Based on existing Trait ontology and more terms are added as necessary 3. QTL and Mendelian Trait Loci are associated with Rosaceae Trait Ontology Demo with exercises 1. Find sequences for DHN genes 2. Find apple and strawberry genomic regions that are in conserved syntenic regions with peach regions that contain QTL for SSC 3. Find apple varieties with an allele that are likely to be resistant to scab 2

3 Exercise 1 (cont.) Go to gene search page Exercise 1: Find sequences for DHN genes Exercise 1 (cont.) Download data in Excel or in Fasta format Exercise 1 (cont.) or find sequences for DHN anchored to peach genome Search for QTL for SSC Exercise 2: Find apple and strawberry genomic regions that are in conserved syntenic regions with peach regions that contain QTL for SSC 3

4 Download the results Choose markers associated with QTL Search for marker data View marker data View alignment Go to Gbrowse_syn to see if the genomic regions are conserved in other Rosaceae genome 4

5 Explore the conserved syntenic regions Exercise 4: Find apple varieties with an allele that are likely to be resistant to scab (Md-Exp7 allele 214) Exercise 4 (cont.) Go to search by marker/allele page and search for varieties with allele 214 for the marker Md-EXP7 Exercise 4 (cont.) Download search results Exercise 4 (cont.) Choose download options Future Directions Add more large-scale data (genomic, transcriptomes, phenotypic, genotypic) Add more curated QTL and trait data, annotated by standardized community agreed ontologies Implement Tripal BIMS (Breeding Information Management System) in GDR and further develop Further refinement/developement of the Tripal modules QTL, germplasm and diversity module Breeders toolbox Web services 5

6 Acknowledgements GDR team members Dorrie Main Taein Lee Stephen Ficklin Jing Yu ChunHuai Cheng Ping Zheng Anna Blenda Sushan Ru Project copis- Dorrie Main (PI), Lisa DeVetter, Kate Evans, Sook Jung, Cameron Peace, Ksenija Gasic, Mercy Olmstead Rosaceae and Bioinformatics Community USDA NIFA SCRI, USDA NIFA NRSP, NSF Plant Genome Program, USDA- ARS, Washington Tree Fruit Research Commission, WSU, Clemson University, University of Florida. 6