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Common Reference Ontologies for Plant Biology (cROP): A Platform for Integrative Plant Genomics

TitleCommon Reference Ontologies for Plant Biology (cROP): A Platform for Integrative Plant Genomics
Publication TypeConference Presentation
Presenting AuthorCooper, L
Secondary AuthorsElser, JL, Preece, J, Arnaud, E, Todorovic, S, Zhang, E, Mungall, C, Smith, B, Stevenson, DW, Jaiswal, P
Conference NamePlant and Animal Genome XXII Meeting
Conference LocationSan Diego, CA

Around the world, a small number of plant species serve as the primary source of food for the human population, yet these crops are vulnerable to multiple stressors, such as diseases, nutrient deficiencies and unfavorable environmental conditions. Traditional breeding methods for plant improvement may be combined with next-generation methods such as automated scoring of traits and phenotypes to develop improved varieties. Linking these analyses to the growing corpus of genomics data generated by high-throughput sequencing, transcriptomics, proteomics, phenomics and genome annotation projects requires common, interoperable, reference vocabularies (ontologies) for the description of the data. The ‘Common Reference Ontologies for Plant Biology’ (cROP) initiative is building the needed suite of reference ontologies, together with enhanced data storage and visualization technologies. The cROP will assume the further development of the existing Plant Ontology (PO), Plant Trait Ontology (TO), and Plant Environment Ontology (EO) and will develop the Plant Stress Ontology (PSO) for abiotic and biotic stresses. It will also include relevant aspects of ontologies such as Gene Ontology (GO), Cell Type (CL), Chemical Entities of Biological Interest (ChEBI), Protein Ontology (PRO) and the Phenotypic Qualities Ontology (PATO). It will include a centralized platform where reference ontologies for plants will be used to access cutting-edge data resources for plant traits, phenotypes, diseases, genomes and semantically-queried gene expression and genetic diversity data across a wide range of plant species. cROP will unify and streamline a fragmented semantic framework and will support allele discovery, advance the understanding of crop evolution, and facilitate crop development.

Presenting Author Address

Oregon State University

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