Poster presented at 3rd international Biocuration Conference. Berlin (Germany). 17 Apr 2009

Alercia, A.

Arnaud, Elizabeth

Bruskiewich, R.

Channelière, S.

Davenport, G.

Jayashree, B.

Manansala, K.

Mauleon, R.

McLaren, G.

Metz, T.

Senger, M.

Shrestha, R.

Simon, R.

English

CGSpace

DEVELOPMENT OF GCP ONTOLOGY FOR SHARING CROP INFORMATION Develop a validation process for ontology terms involving a community of crop experts and botanists.Apply the GCP ontology in the GCP phenotyping templates for annotation of representative data sets by researchers and integrate it into crop databases, e.g. the International Crop Information System (ICIS).To provide a browser interface for searching ontology terms or specific ontology hierarchy and an annotation page for annotating GCP datasets with GCP ontology.To integrate ontology management into the GCP platform for distributed integration of data across the Internet.Integration with plant ontology (PO) and gramene trait ontology (GTO), to develop a common, internationally-shared crop trait and anatomy ontology. FUTURE STRATEGYWithin the Consultative Group on International Agricultural Research (CGIAR), there is an enormous volume of agriculture-related information that is generated. In the past six or seven decades the CGIAR has accumulated historic crop datasets that are related to phenotype, breeding, germplasm, pedigree, traits, etc. However, available data is not systematically formatted and annotated which complicates data management, retrieval, and accessibility. Therefore, the Generation Challenge Programme (GCP) is deploying crop ontology to semantically characterize these datasets. The GCP crop ontology and associated open source software framework is described on the GCP “ Pantheon" project web site (http://www.pantheon.generationcp.org).INTRODUCTION 1Crop Research Informatics Laboratory - Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), Mexico; 2Crop Research Informatics Laboratory - International Rice Research Institute (IRRI), Philippines; 3Centro Internacional de la Papa (CIP), Peru; 4International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), India; 5Bioversity International, Montpellier, France; 6Generation Challenge Programme (GCP), Mexico. *Principal InvestigatorI. GCP crop ontologyThe GCP ontology consolidates and adds to existing public ontology by indexing each ontology within the model in a consistent fashion.The GCP ontology focuses on crop-specific anatomy, development, and trait ontology for the GCP mandate crops (Figure 2) and provides the exact meaning of terms related to phenotypes described by crop physiologists, plant breeders, and other crop scientists.Figure 5. Overview of the GCP semantics. Part I indicates submenus under the main menu GCP semantics (http://pantheon.generationcp.org/index.php). Part II indicates an overview of the application part of crop ontology which is ongoing at present. The light rectangular box represents the major GCP target ontology domains. Rosemary Shrestha1, Mauleon Ramil2, Reinhard Simon3, Jayashree Balaji4, Stephanie Channelière5, Martin Senger2, Kevin Manansala2, Thomas Metz2, Guy Davenport1, Richard Bruskiewich2, Graham McLaren,6 and Elizabeth Arnaud5*GCP semanticsProjectInventoryUsing ontologyRelated linksAnnotated data with the ontologyWeb query and data analysis using GCP ontologyUpload ontology into Chado(GCP ontology database)GCP modelsGCP ontologyBioMoby data typesDomain modelXML schemasOntology source: ICIS-based databases, GCP data templates Germplasm ontologyTaxonomic ontologyPlant anatomy and development ontologyPhenotype and trait ontologyStructural and functional genomic ontologyLocation and environment ontologyGeneral science ontologyList of ontology domainDeveloping the ontologyKoios (Zeus) web interfaceICIS databaseGCP datasets Part IPart IIPO TOLinkage to external ontologyPlant ontology Qualities &units ontologyAssessment methods or evidence ontology(e.g. ICIS)PATOqualifierPhenotype Plant structureLeafDevelopment stagesV3 stage - Markers/alleles - Sequence ontologyGenotype factor (G)EFFECTS- Treatment- Location- Climatic variable - Growth conditions - Water stress- Agronomy managementExternal environmental factor (E)- Time ontology two weeks post irrigationTemporal factor (T)Experimental design ontologyExperiment factor (ED)Phenotypic qualities Plant anatomy100 CCUChlorophyll contentUnit for chlorophyll measurementValue of measurementYoung leaf “ Quality”  a. Osmotic pressure           Osmotic pressure morning     Osmotic pressure morning well water     Osmotic pressure morning intermediate stress     Osmotic pressure morning stressed     Osmotic pressure afternoon     Osmotic pressure afternoon well water     Osmotic pressure afternoon intermediate stress     Osmotic pressure afternoon stressed c. Helminthosporium sativum blotch disease resistance      Hsativum on leaf (0-5)     % Hsativum on node     % Hsativum_Flag     % Hsativum_Flag1     % Hsativum_Flag2     % Hsativum_Tiller1_Flag     % Hsativum_Tiller1_Flag1     % Hsativum_Tiller1_Flag2     % Hsativum_Tiller2_Flag     % Hsativum_Tiller2_Flag1     % Hsativum_Tiller2_Flag2b. Grain yield           Grain yield Kg     Grain yield Kg_FieldWt     Grain yield Kg_GrainWt     Grain yield tons     Grain yield tons_FieldWt     Grain yield tons GrainWtGCP crop-specific ontologyRiceMaizeWheatMusaSorghumChickpeaPotatoII. Importance of deploying the GCP crop ontologyData related to phenotype and genotype available in CGIAR databases cannot be annotated by current ontologies because necessary terms are missing.Free text is used for complex descriptions of phenotypes and trait names which is almost impossible to index and search in a meaningful way (Figure 3).AVAILABILITYThe GCP ontology and platform are described on the pantheon website (http://pantheon.generationcp.org) (Figure 5).The CropForge software project management site (http://cropforge.org/projects/gcpontology) provides both the latest releases and previous versions of ontology flat files, which describe the terms, relationships, definitions, software tools, forums, and mailing lists for communication among collaborators. Additional documentation for scientific end users of the GCP ontology is being established (http://mcclintock.generationcp.org/). Decomposing complex trait names into several simple terms and allocating these terms into various ontology domains (Figure 4) is necessary to properly annotate available data related to crop phenotypes.Figure 2. GCP mandate crops for developing crop-specific ontology. Genotype Germplasm PhenotypeMolecular expressionEnvironment•  Inventory•  Identification (passport)•  Genealogy•  Genetic maps•  Physical maps•  DNA sequence•  Functional annotation•  Molecular variation   (natural or induced)•  Location (GIS)•  Climate•  Day length•  Ecosystem•  Agronomy•  Stresses•  Transcripteome•  Proteome•  Metabolome•  Physiologyhas hasdeterminesdeterminesaffectsFigure 1. Integration needs across diverse crop dataFigure 3. An example of complex trait names and variations in measurement encountered during the ontology development process.Figure 4. Schematic diagram representing the concept method for dissection of complex phenotyping trait terms and several factors that affect phenotyping of crops. Red fonts represent the ontology terms decomposed from the complex term “ leaf chlorophyll content V3 stage two weeks after irrigation”  that are embedded into respective ontology domains. http://pantheon.generationcp.org/index.phpNature Precedings : doi:10.1038/npre.2009.3087.1 : Posted 19 Apr 2009

Development of GCP ontology for sharing crop information.

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Development of GCP ontology for sharing crop information.

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