The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics

Abstract

The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others. The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. We provide integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site (https://github.com/Planteome) for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser (http://browser.planteome.org/amigo) and our data repository.

Chloe: Flexible, Efficient Data Provenance and Management

“…Ontologies for subsets of experimental procedures, such as the Ontology for Biomedical Investigations (OBI), Biological Imaging Methods Ontology (FBbi), Measurement Method Ontology (MMO), and Chemical Methods Ontology, cover specimen preparation for microscopy, clinical, or biochemical analyses [2,13,14,16]. Similarly, ontologies for plant phenotypes (Phenotype and Trait Ontology (PATO), Plant Trait Ontology (TO), Plant Phenology Ontology (PPO), and Cotton Trait Ontology), genes and genomics (Planteome, reference 4), plant morphology (Plant Ontology (PO)), and agronomy (Agronomy Ontology (AGRO)) cover only portions of Chloe or are specialized for particular species [4,5,7]. Building a new ontology coordinated with these is a much more complicated task than simply generating metadata and must be community-driven to be genuinely useful.…”

“…I am favoring geek vernacular here over more precise computational jargon: in Prolog, facts are a particular type of rule; the most general term is predicate 4. A common example of extension is the annotation of genes by the Gene Ontology[1,6]: the annotation is individual to each gene because we don't yet know the classification rules with sufficient accuracy.…”

Dealing with multi‐source and multi‐scale information in plant phenomics: the ontology‐driven Phenotyping Hybrid Information System

“…The Smart layer allows data to be interpretable for other communities by referring to external resources such as standardized semantic resources and reference or species-specific ontologies as described in the Planteome project (Cooper et al, 2018). References are managed using the Simple Knowledge Organization System (Miles & Bechhofer, 2009) that allows support of standardized and advanced queries by using ontologies.…”

Computational aspects underlying genome to phenome analysis in plants

“…Therefore, typical candidate approaches, in which genes underlying a QTL region are investigated manually, could be extended by selecting candidate genes, based on their phenotypes and/or based on where in a phenotype network they reside. Indeed, the Planteome project tries to assess and integrate some of these data already with clever use of biomedical ontologies (Cooper et al ., ).…”