Abstract
Hymenoptera is an extraordinarily diverse lineage, both in terms of species numbers and morphotypes, that includes sawflies, bees, wasps, and ants. These organisms serve critical roles as herbivores, predators, parasitoids, and pollinators, with several species functioning as models for agricultural, behavioral, and genomic research. The collective anatomical knowledge of these insects, however, has been described or referred to by labels derived from numerous, partially overlapping lexicons. The resulting corpus of information—millions of statements about hymenopteran phenotypes—remains inaccessible due to language discrepancies. The Hymenoptera Anatomy Ontology (HAO) was developed to surmount this challenge and to aid future communication related to hymenopteran anatomy. The HAO was built using newly developed interfaces within mx, a Web-based, open source software package, that enables collaborators to simultaneously contribute to an ontology. Over twenty people contributed to the development of this ontology by adding terms, genus differentia, references, images, relationships, and annotations. The database interface returns an Open Biomedical Ontology (OBO) formatted version of the ontology and includes mechanisms for extracting candidate data and for publishing a searchable ontology to the Web. The application tools are subject-agnostic and may be used by others initiating and developing ontologies. The present core HAO data constitute 2,111 concepts, 6,977 terms (labels for concepts), 3,152 relations, 4,361 sensus (links between terms, concepts, and references) and over 6,000 text and graphical annotations. The HAO is rooted with the Common Anatomy Reference Ontology (CARO), in order to facilitate interoperability with and future alignment to other anatomy ontologies, and is available through the OBO Foundry ontology repository and BioPortal. The HAO provides a foundation through which connections between genomic, evolutionary developmental biology, phylogenetic, taxonomic, and morphological research can be actualized. Inherent mechanisms for feedback and content delivery demonstrate the effectiveness of remote, collaborative ontology development and facilitate future refinement of the HAO.
Highlights
Hymenoptera is an extraordinarily diverse lineage of insects, both in terms of species numbers and phenotypes, that includes sawflies (‘‘Symphyta’’), bees (Anthophila), wasps, and ants (Formicidae)
The database presently stores data from multiple ontologies, including our core data (Hymenoptera gross anatomy) and associated descriptive lexicons that are orthogonal to the Hymenoptera Anatomy Ontology (HAO)
The HAO is being developed as a foundational data source for all biologists referencing hymenopteran anatomy
Summary
Hymenoptera is an extraordinarily diverse lineage of insects, both in terms of species numbers and phenotypes, that includes sawflies (‘‘Symphyta’’), bees (Anthophila), wasps (numerous lineages), and ants (Formicidae). These insects serve critical ecological roles as herbivores, predators, parasitoids, and pollinators, with several species functioning as models for genomic (e.g., Apis mellifera, the European honey bee) [1], behavioral (eusocial Aculeata, including the honey bee), virus coevolution [2], and evolutionary genetics (e.g., Nasonia spp.) research [3]. This situation inhibits future efforts to explore biological phenomena across Hymenoptera, including 1) comparisons of gene expression patterns, e.g., mining genome annotations to understand the roles genes play in development, morphology and behavior [9]; 2) comparative morphology and phylogenetics, which is increasingly important as we attempt to include the vast amount of information from the fossil record and rare taxa from which we cannot extract DNA; 3) phenotype variability in the context of environment, e.g., responses to variations in host quality, appropriateness, or nutrition in response to global climate change; 4) descriptive taxonomy and phenomics, as the corpus of descriptive taxonomy (each description is essentially a block of statements about a species’ phenotype, often loosely following the Entity-Quality format used by annotators of genomic research [10]) cannot be efficiently queried for information to guide us on characters and species diagnosis; 5) computed reasoning, as logical, automated reasoning across our knowledge of hymenopterans requires a well-defined semantic framework
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