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Phenotype Curation

Phenotype Curation. Susan R. McCouch Department of Plant Breeding Cornell University. QTL curation strategy for rice ( Oryza sp.). Time Initiate with the current reports and work the backlog Traits

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Phenotype Curation

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  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. Trait Category Number of Traits Number of QTL Abiotic stress 51 589 Biotic stress 8 256 Quality 30 200 Yield 24 773 Development 13 314 Anatomy 44 662 Sterility or fertility 9 38 Vigor 14 816 Biochemical 27 195 QTL traits clustered by trait categories

  8. QTL database search OPTION-1 Search your query

  9. OPTION-2 Browse by trait category Browse QTL database View Next 25 entries or type a page number and hit Pageto go to that page Found 30 traits under category “Quality”. Displayed 25 entries per page. Sort by any column heading 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

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

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