The ability to induce galls on plants has evolved independently many times across the phylogeny of Life, with evidence of this kind of interaction dating back at least to the Middle Devonian (385 million years ago; Labandeira (2021)). Despite a long evolutionary history, the prevalence of this phenomenon in nature (Fig. 1), and broad research interest, progress towards understanding the physiological mechanisms of gall induction has been incremental (Hearn et al. 2019Korgaonkar et al. 2021, Hearn et al. 2019). However, interest in researching the mechanisms of gall induction and development remains high, and general interest in gall biology is surging. Research-grade records of gall inducers in iNaturalist, for example, are growing exponentially (see GBIF occurrences for iNaturalist records of gall-inducing wasps in the superfamily Cynipoidea; https://doi.org/10.15468/dl.e4wud2), and a new resource has been established to facilitate the identification of gall-inducers in North America (Gallformers Contributors 2024).

Figure 1.  

Some of the galls formed by plants in response to manipulation by gall wasps (Hymenoptera, Cynipoidea). Clockwise from the spiny gall at the top: Diplolepis bicolor leaf galls on Rosa sp.; Holocynips maxima "root" gall on Quercus montana; Melikaiella tumifica mid-rib gall on Quercus rubra; undescribed mid-rib gall cluster on Quercus montana; Andricus quercusstrobilanus bud gall cluster on Quercus bicolor; Callirhytis quercusoperator catkin gall on Quercus rubra; Callirhytis piperoideas mid-rib gall cluster on Quercus velutina; Andricus chinquapin stalked leaf gall on Quercus alba; (middle) Disholcaspis quercusmamma gall cluster on Quercus bicolor stem. All photos (CC BY 4.0) by Andrew R. Deans.

We provide here another resource, a structured glossary of gall phenotype terms, that facilitates natural language and semantic descriptions of gall forms and can forge connections to knowledge generated through model organism research. As proposed in other systems (Deans et al. 2015), genotype-phenotype data from plant models, may shed light on the mechanisms of gall induction and the subsequent, predicable morphology we observe in the extended phenotypes of gall inducers. The logic inherent in this ontology also allows for computation across phenotype datasets, which may reveal hidden patterns in gall traits across a broad array of gall-inducing species. Similar approaches are used already in taxonomy (Balhoff et al. 2013) and evolutionary developmental biology (Edmunds et al. 2015).

Through this paper, we aim to announce this new ontology, which was developed using Open Biological and Biomedical Ontology (OBO) Foundary principles (Jackson et al. 2021) and with community input; demonstrate its utility as a controlled vocabulary and as a computational tool; and provide some examples of its use in describing and referring to gall phenotypes.

The development process largely transitioned through three main phases: (1) glossary development, i.e. gathering relevant concepts and terms, with community input; (2) structuring the glossary as an ontology, using established best practices; and (3) demonstrating the computational nature of the ontology, by reasoning over phenotype data.

Glossary development

Ontology development

Reasoning

We extracted gall phenotypes from natural language descriptions of galls that are induced on white oak, Quercus alba Linnaeus, 1753, as listed at the Gallformers website (https://gallformers.org). For example, Weld (1944) described the gall of Zopheroteras cuneatum Weld, 1944 (Fig. 2) as: "Conical, red, 3.0–4.4 mm long by 1.5 mm broad at base, attached to the very base of the petiole in fall just as the leaves are turning. On young trees or sprouts from stumps". We parsed that description into six characters, which we translated into semantic phenotypes that were applied to a mock specimen (individual) for that species. Table 1 provides examples of how descriptive data were translated into semantic statements. We attempted to translate each natural language phrase into semantic statements in Protégé (version 5.6.3; Musen (2015)), following protocols outlined by Balhoff et al. (2013) and Mikó et al. (2014). The resulting dataset was then queried using descriptive logic (DL), with the ELK reasoner (version 0.4.3; Kazakov et al. (2012)) implemented in Protégé. Suppl. material 2 lists all the natural language phenotypes we attempted to capture, with links to original sources of those phenotype descriptions.

Table 1.

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Examples of gall traits of Zopheroteras cuneatum Weld, 1944 as originally described by the author (column 1), translated into semantic statements that are composed from multiple ontologies (column 2). Weld (1944) describes the spectrum of phenotypes he observed (column 1), but we are generating an example dataset of instances, in this case, mock specimens. See notes (column 3) for explanation.

original description	phenotype	notes
red	'has quality' some red
3.0–4.4 mm long	hasHeightInMm 4.4	We are generating a mock dataset comprised of individuals; therefore, we chose to represent just the maximum value from the range, for the "specimen" that represents this taxon.
attached to the very base of the petiole	'part of' some petiole
in fall	'has seasonal maturity' value autumn	'has seasonal maturity' is an object property created for GallOnt
conical	'has quality' some conical
1.5 mm broad at base	hasDiameterInMm 1.5	hasDiameterInMm and hasHeightInMm are data properties created for GallOnt
Host.—Quercus alba	'has host' some 'Quercus alba'	Taxon names mostly come from the NCBI Taxonomy
	'host of' some 'Zopheroteras cuneatum (agamic)'	'Zopheroteras cuneatum (agamic)' was created as a child of Zopheroteras cuneatum and designated as an asexual organism
	'plant gall'	to declare that this is a gall

Figure 2.  

Zopheroteras cuneatum gall on white oak (Quercus alba), from an observation in iNaturalist (https://www.inaturalist.org/observations/96124447) by Jeff Clark (CC BY 4.0)

The final version of the gall glossary yielded 136 concepts (classes) that are directly relevant to gall morphology. We assigned each class a primary label, sometimes called a "preferred term" (Yoder et al. 2010) and matched an additional 56 synonymous terms to their respective classes. For example, some galls have multiple chambers within them, each of which contains a larva of the inducer. We refer to this type of gall as "polythalamous" (the primary label) and define this phenotype as "an internal gall trait in which more than one larval chamber is present for the inducer species" (the Aristotelian definition). Synonyms (secondary labels) assigned to this class include "multichambered", "multilocular" and "multi-celled".

The size and complexity of the resulting ontology, version 2024-04-19, is reported in Table 2. Of the 394 classes, 53 are unique to GallOnt. The remaining 341 were derived from other ontologies, including 161 from PATO, 120 from PO, 31 from NCBITaxon, 14 from BFO, six from GO, three from CARO and one each from FLOPO, IAO, ENVO, OBI, UBERON and NCI_Thesaurus. GallOnt has 132 object properties, three of which originate in GallOnt: induced_by (to designate the organism responsible for inducing the gall), has_seasonal_maturity and has_seasonal_emergence (to represent seasonal elements of plant gall life cycles). Remaining properties are from the Relation Ontology (RO; Smith et al. (2005)). The ontology is available in three formats through the OBO Foundry (https://obofoundry.org/ontology/gallont.html): OWL, OBO and JSON.

The reasoning dataset was created as a separate test ontology (see Suppl. material 1), to which we added 72 individual galls and gall clusters, each with an average of about nine phenotypes (x̄ = 8.96; 645 total for the dataset) and one measurement (x̄ = 0.93; 67 total data property assertions for the dataset). We formulated several questions a biologist could ask, regarding galls on Quercus, as recorded in this dataset and generated DL queries for each. The results are presented in Table 3.

We demonstrate above and in the supplementary files how this ontology can be used to compose semantic phenotypes for plant galls. The ontology also stands as a controlled vocabulary for describing gall morphology. We recommend using a character:character state or entity:quality format, for example in a spreadsheet or as rendered in many contemporary taxonomic descriptions (e.g. see species descriptions in Mikó et al. (2014)). This syntax is intuitive for human readers and lends itself to further processing, for example, to generate semantic statements using a script (Tarasov et al. 2022). As described above, we include human readable, logical definitions in the ontology, as well as links to exemplar galls in iNaturalist, for most of the classes, to aid in understanding each concept. One can browse the ontology directly by loading the OWL file in Protégé or through several online ontology sites (e.g. EMBL-EBI Ontology Lookup Service (OLS), Ontobee and BioPortal).

Our small survey of gall descriptions also revealed inconsistencies and incompleteness of the phenotypes that were represented, making it difficult to confidently query published knowledge of galls. For example, only 33 descriptions out of 67 reported whether the gall was mono- or polythalamous (highlighted rows in Table 3). As a starting point for future conversations, we propose that cecidologists consider including the following minimum information for the description of galls (MIDG version 0.1), in future publications:

• host plant species
• location of gall on the plant (part of <some plant anatomical entity>);
• maximum diameter in mm (measured in the axis that is perpendicular to the axis of attachment to the plant);
• maximum height in mm, from point of attachment to the plant or length in mm, if describing a non-deciduous gall (i.e. measured along the axis of the plant part affected);
• internal qualities, including
  • whether the gall is mono- or polythalamous (for galls induced by Cynipoidea or Cecidomyiidae)
  • whether the gall is solid, hollow, spongy, succulent etc.;
• date of appearance on the plant if known;
• date of emergence of the inducer if known;
• surface texture;
• shape;
• colour pattern;
• shedability;
• spatial pattern (confluent, clustered, scattered or solitary).

GallOnt likely is not yet sufficient for describing every type of gall nor all the complex phenotypes exhibited in these structures. For example, the ontology does not yet include many classes needed to represent histological traits (tissue qualities) nor temporal changes in gall morphology (i.e. stages of gall development). During the initial development, we also focused almost exclusively on phenotypes expressed in galls found in North America, as induced by cynipoid wasps. Expanding the ontology to cover galls induced by thrips (Thysanoptera), mites (especially Eriophyidae), gall midges and other flies (Diptera) and non-arthropod inducers, in other parts of the world, will undoubtedly require additional classes and new versions of MIDG. New classes and other modifications to the ontology can be proposed using the GitHub issue tracker linked above and ongoing development in relevant ontologies (see below) will likely facilitate more sophisticated representation of gall phenotypes.

GallOnt can be used in generating Gene Ontology annotation files (GAFs; The Gene Ontology Consortium et al. (2023)), when reporting on gene expression studies of galls (for example, Hearn et al. (2019)Martinson et al. (2022)). We are actively developing sections of the Plant Trait Ontology (TO) and Plant Stress Ontology (PSO) (Cooper et al. 2018) that refer to gall development and inducer-plant interactions, to more fully integrate plant gall concepts with tools used for discovery in model plant systems. Relatedly, GallOnt is also available in AgroPortal (https://agroportal.lirmm.fr/ontologies/GALLONT; Jonquet et al. (2018)), to facilitate gall research related to agriculture. Several species of gall-inducers are important pests, including Dryocosmus kuriphilus Yasumatsu, 1951 (Cynipidae, Cynipini) on sweet chestnut trees (Fagaceae, Castanea sativa Mill.), Hessian fly (Cecidomyia destructor Say, 1817) on cereals and many related gall midges (Diptera, Cecidomyiidae; see volumes by Horace Francis Barnes (1902–1960), starting with Barnes (1946)). Other species of gall inducer, especially Agrobacterium spp. (Alphaproteobacteria, Rhizobiaceae), have application in transforming plants (Nester 2015). These research areas could benefit from future refinements to GallOnt.

We provide here the first ontology designed to represent plant gall phenotypes. The ontology was developed with the latest tools, to be extensible, accessible and persistent, and we demonstrate its utility as a reasoning tool. We invite potential users and contributors to view the documentation at the GallOnt site (https://adeans.github.io/gallont/), to provide new terms and other refinements and to offer additional use cases.

Jim Balhoff, Laurel Cooper, Pankaj Jaiswal and members of the OBO community more broadly assisted with troubleshooting and encouragement. Adam Kranz, Heather Hines, Denise Montelongo, John Tooker, Antoine Guiguet, Antonio Casadei, Cecil Smith and Laura Porturas provided invaluable input regarding terminology, unusual gall phenotypes and future applications of this resource.