1. Phenotype Curation Susan R. McCouch Department of Plant Breeding Cornell University

2. QTL curation strategy for rice (Oryza sp.) Time Initiate with the current reports and work the backlog Traits Use of commonly accepted trait terms for clustering QTL phenotypes complementing the knowledge of breeders and geneticists Number Adopt a strategy that provides rapid processing of information on large number of QTLs followed by a deeper curation.

3. Three level curation strategy Level-1: A version with core features Trait, map position, and citation. Develop tools for community curation and data mining Level-2: Deeper curation includes Use of controlled vocabularies (PO, TO, GO and GEO), defining the phenotypic assay and environment Genetic population structure and germplasms QTL analysis methodology, etc. Level-3: Populations and genotypes Invite authors to submit raw data Train researchers to curate their own data

4. Demand for QTL curation Repeated requests from rice and other cereal research communities Thousands of QTLs reported in cereal crop literature Critical component of overall phenotype curation Continuity with previous versions of RiceGenes Critical links for breeders/geneticists looking for genes associated with agronomic traits

5. Comparison among cereals Build and share data structure/schema required for useful phenotypic/QTL comparison across cereal sp. Gramene is funded to curate QTL information for rice only, though working with cereal communities (e.g. maize and Triticeae). Contributions to a community based phenotype consortium of model organism databases through: Newly funded NSF initiatives POC (www.plantontology.org) Gramene RCN Phenotype Ontology initiatives of OBO (http://obo.sf.net)

6. QTL data in Gramene 3843 QTLs Rice (Oryza sp.): 3475 Maize: 327 Wild Rice (Zizania sp.): 41 Curated references: 152 Rice (Oryza sp.): 143 (2003-1999) Maize 8 (test cases on drought tolerance) Wild Rice (Zizania sp.): 1 57 QTL reference maps generated from different genetic populations such as DH, RIL, BC, F2 etc.

7. QTL traits clustered by trait categories Trait CategoryNumber of TraitsNumber of QTL Abiotic stress51589 Biotic stress8256 Quality30200 Yield24773 Development13314 Anatomy44662 Sterility or fertility938 Vigor14816 Biochemical27195

8. OPTION-1 Search your query QTL database search

9. Trait name. Links to all the QTLs in Gramene database, detected for this trait Number of QTLs listed in Gramene database, detected for the given trait Sort by any column heading Found 30 traits under category “Quality”. Displayed 25 entries per page. View Next 25 entries or type a page number and hit Page to go to that page OPTION-2 Browse by trait category Browse QTL database

10. Trait assayed QTL detected on linkage group. Links to all the QTLs listed in Gramene but mapped to this linkage group Trait symbol. Links to all the QTLs detected for this trait listed in Gramene. Trait category to which the trait belongs. Links to a trait browser displaying all the traits listed in Gramene belonging to this category. QTL symbol assigned in the publication Links to Gramene citation a published QTL reference. Links to the QTL map on Gramene Comparative map viewer

11. QTL displayed on CMap

12. QTL always defined by linkage Population x marker set x phenotypic assay x statistical test of association Generally many phenotypes assayed for each population and multiple loci identified per phenotype Entry into DB different than with mutants but information intersects with mutants phenotypic assay, gene, allele Entry is always via linkage to a set of markers

13. Level-2 Large number of QTL references (200-300 papers in rice) Inconsistent reporting style and format requires manual curation by experts Efforts to develop curation strategies using ontology etc. encouraged. Complicated data relationship and structure Prioritize based on data availability Prioritize based on trait Biotic and abiotic stress

14. Discussion points What linkage analysis tools should we make available to Gramene users, if any? How best to visualize QTLs on the comparative maps?

15. Updates to rice mutant database 1320 Genes characterized by phenotype 424 Genes fully annotated (562 references): Phenotypic description Associations to controlled vocabularies (TO, PO, GO) Map position Alleles, phenotypic study, germplasm, environment Sequence and gene product DBxref link to Oryzabase 896 Genes with only basic Info: Gene name and symbol; Map position DBxref link to Oryzabase

16. Annotated mutant gene an example

17. Linking phenotypes across genetic maps

18. Linking phenotypes across genetic and physical maps

19. Outreach and Acknowledgement Distributed Annotation of Mutants –Toshiro Kinoshita - rice mutants - Hokkaido Univ. (Japan) –HeeJong Koh-rice mutants-Seoul National Univ. (Korea) Distributed Annotation of QTL –Jonaliza Lanceras - drought-related QTLs in Rice - Kasetsart Univ. (Thailand) –Dr. Longxi Yu – drought-related QTLs in Maize Contributed Map Position Info to Gramene: Dr. H. W. Cai; Dr. Y. Fukuta; Dr. J. Leach; Dr. H. Leung; Dr. Z. Li; Dr. M. Maheswaran; Dr. D. Mackill; Dr. Adam Price; Dr. J. Xiao; Dr. M. Yano; Dr. Q. Zhang; Dr. K. Zheng, etc.