Abstract
Galls are novel plant structures that develop in response to select biotic stressors. These structures, extended phenotypes of the inducer, usually serve to protect and feed the inducer or its progeny. This life history strategy has evolved dozens of times, and tens of thousands of species—including many bacteria, fungi, nematodes, mites, and insects—are capable of manipulating plants in this way. The variation in gall phenotypes is extraordinary across species but usually predictable for each species of inducer. We introduce here a new ontology, GallOnt, that facilitates consistent descriptions and the semantic representation of and reasoning over plant gall phenotype data. GallOnt was largely developed from ontologies in the Open Biological and Biomedical Ontology (OBO) Foundry and stands to connect plant gall phenotypes to knowledge derived from model plant systems, including genotype-phenotype and agricultural research. We also introduce the idea of a new gall data standard—Minimum Information for the Description of Galls (MIDG version 0.1)—as a starting point for discussions regarding cecidology best practices.
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ARPHA Preprints
https://doi.org/10.3897/arphapreprints.e128953 (06 Jun 2024)
https://doi.org/10.3897/arphapreprints.e128953 (06 Jun 2024)
Published in: Biodiversity Data Journal https://doi.org/10.3897/BDJ.12.e128585
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ARPHA Preprints
doi:
10.3897/arphapreprints.e128953
First posted
06 Jun 2024
Authors
Andrew R Deans
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Frost Entomological Museum, The Pennsylvania State University, University Park, United States of America
Frost Entomological Museum, The Pennsylvania State University, University Park, United States of America
Frost Entomological Museum, The Pennsylvania State University, University Park, United States of America
Conflict of interest
The authors have declared that no competing interests exist.
Supporting agencies
This material is based upon work supported by the U.S. National Science Foundation under grant nos. DEB-1856626 and DEB-2338008. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
This is an open access preprint distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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