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Author: Rosemary Shrestha
Carolina Rivera-Amado Rosemary Shrestha (2018)
Present at CIMMYT and IWYP annual conference, 11th–14th June 2018.
Conference object
Data management Interoperability International cooperation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA
Rosemary Shrestha Glenn Hyman Elizabeth Arnaud (2012)
The Crop Ontology (CO) of the Generation Challenge Program (GCP) (http://cropontology.org/) is developed for the Integrated Breeding Platform (IBP) (https://www.integratedbreeding.net/) by several centers of The Consultative Group on International Agricultural Research (CGIAR): bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The CO provides validated trait names used by the crop communities of practice (CoP) for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB) fieldbooks are synchronized with the CO terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum, and wheat. Online curation and annotation tools facilitate (http://cropontology.org) direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology (PO) and Trait Ontology (TO). Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell) or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS). Cross-referencing and annotation will be further applied in the IBP.
Article
Crop Ontology breeding trait plant phenotype trait dictionaries breeding fieldbook data annotation integrated breeding platform crop community of practice CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA
Carolina Rivera-Amado Rosemary Shrestha Kate Dreher (2019)
Conference object
Rosemary Shrestha Elizabeth Arnaud Guy Davenport Richard Bruskiewich (2010)
Agricultural crop databases maintained in gene banks of the Consultative Group on International Agricultural Research (CGIAR) are valuable sources of information for breeders. These databases provide comparative phenotypic and genotypic information that can help elucidate functional aspects of plant and agricultural biology. To facilitate data sharing within and between these databases and the retrieval of information, the crop ontology (CO) database was designed to provide controlled vocabulary sets for several economically important plant species. Existing public ontologies and equivalent catalogues of concepts covering the range of crop science information and descriptors for crops and crop-related traits were collected from breeders, physiologists, agronomists, and researchers in the CGIAR consortium. For each crop, relationships between terms were identified and crop-specific trait ontologies were constructed following the Open Biomedical Ontologies (OBO) format standard using the OBO-Edit tool. All terms within an ontology were assigned a globally unique CO term identifier. Principal results The CO currently comprises crop-specific traits for chickpea (Cicer arietinum), maize (Zea mays), potato (Solanum tuberosum), rice (Oryza sativa), sorghum (Sorghum spp.) and wheat (Triticum spp.). Several plant-structure and anatomy-related terms for banana (Musa spp.), wheat and maize are also included. In addition, multi-crop passport terms are included as controlled vocabularies for sharing information on germplasm. Two web-based online resources were built to make these COs available to the scientific community: the ?CO Lookup Service? for browsing the CO; and the ?Crops Terminizer?, an ontology text mark-up tool. The controlled vocabularies of the CO are being used to curate several CGIAR centres' agronomic databases. The use of ontology terms to describe agronomic phenotypes and the accurate mapping of these descriptions into databases will be important steps in comparative phenotypic and genotypic studies across species and gene-discovery experiments.
Article
The plant ontology as a tool for comparative plant anatomy and genomic analyses
Laurel Cooper Christopher Mungall Daniel Lang Tanya Berardini Elizabeth Arnaud Rosemary Shrestha (2012)
The Plant Ontology (PO; http://www.plantontology.org/) is a publicly-available, collaborative effort to develop and maintain a controlled, structured vocabulary (?ontology?) of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded to include all green plants. The PO was the first multi-species anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontology that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. As of Release #18 (July 2012), there are about 2.2 million annotations linking PO terms to over 110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and Quantitative Traits Loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users, and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs.
Article
plant anatomyontology Comparative genomics genome annotation Bioinformatics terpene synthase CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA
Sustainable Wheat & Maize Production in Afghanistan (ACIAR funded, Project number: CIM/2011/026)
Susanne Dreisigacker Rajiv Sharma Eric Huttner Aziz Karimov Carolina Sansaloni Rosemary Shrestha Kai Sonder Hans-Joachim Braun (2019)
Since 2012, Australian support has resulted in the release of 23 wheat varieties by Afghanistan’s National Varietal Release Committee (NVRC). These varieties deliver both improved yield and disease tolerance. A 2015/16 farmer survey confirmed that farmers were indeed sharing seed with an average of three relatives/neighbours – although with no indication of how much seed was shared. This uncertainty regarding the adoption of new varieties has been intended to resolve by a recent DNA assessments of seed collected in 2015/16 that shows the general prevalence of the new varieties across 600 surveyed farms.
Dataset
The Ontologies Community of Practice: a CGIAR initiative for big data in agrifood systems
Elizabeth Arnaud Marie-Angélique Laporte Soonho Kim Laurel Cooper Pankaj Jaiswal Gideon Kruseman Rosemary Shrestha Christopher Mungall Abhishek Rathore Cyril Pommier Leroy Mwanzia Brian Chiputwa ESTHER DZALE YEUMO Medha Devare (2020)
Article
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DATA AGRICULTURAL RESEARCH ONTOLOGY AGRIFOOD SYSTEMS
Developing data interoperability using standards: a wheat community use case
Michael Alaux Elizabeth Arnaud Sophie Aubin Ute Baumann Patrice Buche Laurel Cooper Robert Davey Clement Jonquet Marie-Angélique Laporte Pierre Larmande Cyril Pommier Vassilis Protonotarios Carmen Reverté Rosemary Shrestha Aravind Venkatesan Hadi Quesneville (2017)
Article
Standards Interoperability Data management CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA