the plant ontology consortium and plant...

Conference Review

The Plant Ontology2 Consortium and PlantOntologies

The Plant Ontology2 Consortium{Department of Agronomy, University of Missouri-Columbia, Columbia, Missouri, 65211-7020, USAE-mail: [email protected]

{A full list of authors/affiliations/web addresses appears at the end of this paper.

Received: 11 February 2002

Accepted: 12 February 2002

Abstract

The goal of the Plant Ontology2 Consortium is to produce structured controlled voca-

bularies, arranged in ontologies, that can be applied to plant-based database information

even as knowledge of the biology of the relevant plant taxa (e.g. development, anatomy,

morphology, genomics, proteomics) is accumulating and changing. The collaborators of the

Plant Ontology2 Consortium (POC) represent a number of core participant database

groups. The Plant Ontology2 Consortium is expanding the paradigm of the Gene

Ontology2 Consortium (http://www.geneontology.org). Various trait ontologies (agro-

nomic traits, mutant phenotypes, phenotypes, traits, and QTL) and plant ontologies (plant

development, anatomy [incl. morphology]) for several taxa (Arabidopsis, maize/corn/Zeamays and rice/Oryza) are under development. The products of the Plant Ontology2

Consortium will be open-source.Copyright # 2002 John Wiley & Sons, Ltd.

Keywords: Arabidopsis; controlled vocabulary; corn; database; maize; ontology; rice

Plant databases are expanding in number, size andcomplexity. This is especially true of economicallyimportant plant taxa such as maize/corn (Zeamays), rice (Oryza sativa) and soybean (Glycinemax) but is also true of taxa regarded as ‘modelorganisms’ for plant science research purposes, suchas Arabidopsis thaliana and rice (Oryza). Theseinformation-rich databases face the challenge ofaccurately and consistently documenting featuressuch as gene structures, products and functions,phenotypes, traits, developmental stages and anato-mical parts besides other information. It will beincreasingly desirable for inter-database queries tobe performed between these plant-based databasesto exploit comparative genomic strategies to eluci-date functional aspects of plant biology and con-duct studies of synteny. These databases will facilitateinterpolation and extrapolation of data that willfacilitate the development of further hypotheses tobe tested. However, terms used to describe com-parable objects within and between databases aresometimes quite variable and limit the ability toaccurately and successfully query information inand across different databases. One solution to this

problem involves the development and applicationof structured controlled vocabularies arranged inontologies.

What is an ontology?

An ontology is a classification methodology forformalizing a subject’s knowledge in a structuredway (typically for consumption by an electronicdatabase). Dictionaries and encyclopedias are exam-ples of ontologies, as are many web-based entities,such as Yahoo and Excite, and so is the schema fora database. A more formal definition of ontology isavailable from: http://www-ksl.stanford.edu/onto-std/mailarchive/0136.html. In the world of structuredinformation, ontologies, comprising structured con-trolled vocabularies, play a very important role infacilitating information retrieval. This is because therelationships between the controlled vocabularyterms, in the ontologies, must be defined in orderto query the information. If the relationshipsbetween the terms (objects) are not well structured(biologically accurate) the information retrieved will

Comparative and Functional Genomics

Comp Funct Genom 2002; 3: 137–142.Published online 15 March 2002 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002 /cfg.154

Copyright # 2002 John Wiley & Sons, Ltd.

be less valuable. Furthermore, the definitions thataccompany the controlled vocabulary terms arevery important in that they facilitate the consistentuse of the controlled vocabulary terms in databasecuration.

Biology-based ontologies

In biology-based ontologies the controlled vocabu-lary terms are arranged in such a way that theirplacement reflects the known or putative biologicalassociations between the objects represented by thecontrolled vocabulary terms. Consequently, consid-erable effort must be invested into the compilationof the controlled vocabulary terms and the defini-tions of these terms. The terms and their definitionsneed to be biologically correct and internationallyacceptable. The arrangement of the controlled voca-bulary terms in the ontology must reflect the cur-rent understanding of the biological relationshipsbetween the associated plant parts at the sub-cellular organelle level, cell level, tissue level andorgan level. If the ontology of the relationshipsbetween the terms is correct, the information retrievedvia a database search is likely to be valuable andcorrect. The converse is also likely to be true. Whileit is ideal to use terms that are internationallyacceptable this does not imply that local terms and/or synonyms cannot be used. A parsing facility,utilizing synonyms, can be used to overcome thisdifficulty.

Ontology structure

It is relatively easy to design an ontology based onconcrete facts such as names, birth dates etc.However, it is considerably more difficult to designan ontology based on knowledge that is incompleteor not yet well understood, or that as yet doesnot have unanimous support. However, the PlantOntology2 Consortium is attempting to developvarious plant ontologies that will represent ourcurrent and future understanding of relationshipsamong various plant-based knowledge domainse.g. anatomy and morphology, development, traits.These ontologies will provide open-source, com-mon vocabularies of defined terms. The relation-ships between concepts (represented by controlledvocabulary terms) within and between ontologies isrepresented by the use of Directed Acyclic Graphs

(DAGs). A DAG is similar to a hierarchical struc-ture but is superior because terms (representingconcepts) within a DAG structure have the abilityto have one or more than one ‘parent’. DAGs areable to represent biological relationships morereadily than typical hierarchical structures. Con-sider the following simple example: a protein thatboth binds DNA and hydrolyses ATP. This proteincan be equally described as a ‘DNA bindingprotein’ and as a ‘catalyst’ (enzyme). Consequently,this protein should be a ‘child’ of both ‘parents’within an ontology. The presence of such multiple‘parent’ situations in biology requires that they beaccurately represented in a conceptual framework.DAGs, and their associated semantic relationshipsbetween the constituent nodes, meet this need.

Some of the structured controlled vocabulariesbeing developed should be generic enough tofacilitate inter-database queries for related organ-isms (e.g. monocots and dicots). Other ontologieswould be taxon-specific but would still be able to beinterrogated for inter-taxon comparisons. Forexample, an inter-database query for phenotypesinvolving the inflorescence should produce ‘tassel’and ‘ear’ phenotypes in maize, ‘panicle’ phenotypesin rice and comparable inflorescence phenotypes inArabidopsis. The relevant associated genomic infor-mation can then be obtained from each databasefor further analysis.

There is little doubt that the world-wide plantscience community could benefit from having struc-tured controlled vocabularies of terms arranged inontologies. Furthermore, these controlled vocabul-aries of terms and their associated definitions willcontribute towards consistent data curation and socontribute to the information management needs ofthe plant sciences.

Extending the gene ontology2 paradigm

The Plant Ontology2 (PO) Consortium is extendinga paradigm developed by the Gene Ontology2

Consortium [2]. The Gene Ontology2 (GO) Con-sortium (http://www.geneontology.org) has beendeveloping ontologies and associated controlledvocabularies for several years. The objective of theGO consortium has been the development of onto-logies and controlled vocabularies for three knowl-edge domains: the molecular function, biologicalprocess and cellular component of gene products.These ontologies are being developed for a generic

138 The Plant Ontology Consortium

Copyright # 2002 John Wiley & Sons, Ltd. Comp Funct Genom 2002; 3: 137–142.

eukaryotic cell. The Gene Ontology2 Consortium isa paradigm for how diverse groups of researchersand database curators can share controlled voca-bularies – both in terms of development (using theDAG methodology) and data sharing. Representingknowledge of biology necessitates a flexible struc-ture – a structure that is able to change as ourknowledge of biology changes. The GO paradigmreadily accommodates additions and restructuringas new information is obtained. Information onnew molecular functions, biological processes andcellular components can be added or updated.Several research groups have been annotating theirdatabases according to the controlled vocabulariescontained in the ontologies produced by the GOconsortium. Consequently, the Plant Ontology2

Consortium is adopting and extending the GOparadigm in an effort to faithfully represent ourcurrent understanding of biology even as it changes.

Development of plant ontologies andtrait ontologies

Members of the Plant Ontology2 Consortium, andassociates, are in the process of developing struc-tured controlled vocabularies in ontologies for twolarge knowledge domains, namely: Plant Ontologiesand Trait Ontologies. Each of these domains willcomprise several sub-domains. The sub-domains, ofnecessity, will have components that are taxon-specific. However, while there will be taxon-specificcomponents of ontologies, there will also be termsthat will be common to all plants. For example, anontology of anatomy for maize would includebulliform cells in the leaf, while in Arabidopsis,‘pavement cells’ in the epidermis would be includedin that taxon-specific ontology. However, both onto-logies would contain the terms leaf, leaf epidermis,mesophyll etc. which are common anatomicaltissues to all plants.

Consideration is being given to the use ofontogenetic and phylogenetic data and concepts inthe elucidation and development of ontologicalrelationships and the testing of the True Path Rulein the plant ontologies. The true path rule statesthat the pathway from a child term all the way upto its top level parent(s) must always be biologicallyaccurate. For further information on the True PathRule consult the General GO Guidelines in http://www.geneontology.org/GO.usage.html.

Ontologies being developed

Within the Traits Ontology (TO, see Figure 1) willbe included the following domains: agronomictraits, mutant phenotypes, phenotypes, traits, andQTL (quantitative trait loci). Genetic traits (maplocations of loci of genes for each chromosome ofthe taxon in question) may be associated with thetraits ontology.

Within the Plant Ontology (PO) will be includedthe following ontologies:

$ Plant Development - This ontology will be basedon published growth stage descriptors: initiallyfor Arabidopsis thaliana, maize (Zea mays) andrice (Oryza sativa).

$ Anatomy (incl. morphology) - This ontologydeals with the cell types and tissue types inthe plant body, their anatomical structure, func-tion and location in the plant body (roots,stems, leaves, inflorescences, fruits, seeds). Whilethe cell types and tissue types in the plant bodyreveal a definite structural and functional orga-nization, their arrangement in various parts ofthe plant body is variable. The principal tissuesof a vascular plant are grouped, on the basisof topographic continuity, into three tissuesystems- the dermal, the vascular and the funda-mental (or ground) system. The structuraland functional specialization of plant anatomy,expressed in the plant’s phenotype as morpho-logy and micromorphology, is included withinthe anatomy ontology. This ontology will beinitially based on Arabidopsis thaliana but othertaxa will be included, resulting in a range oftaxon-specific ontologies and subsequently onto-logies that will be applicable to a genericassemblage of plants.

To explore the developing traits ontology (TO)consult the Ontology Search link at Gramene (http://www.gramene.org/plant_ontology/). An example ofPlant Ontology (PO) for maize/corn leaf morpho-logy, and specifically the ligule, is shown inFigure 2.

Current members and associates

The Plant Ontology2 consortium is a collabora-tion between representatives of model organismdatabases and currently comprises the following

The Plant Ontology2 Consortium and Plant Ontologies 139


participants: Gramene: A Resource for Compara-tive Grass Genomics – http://www.gramene.org; theInternational Rice Research Institute (IRRI – http://www.irri.org) associated with The InternationalCrop Information System (ICIS) database (http://www.cgiar.org/icis/); MaizeDB (http://www.agron.missouri.edu) and the Maize Mapping Project(http://www.cafnr.missouri.edu/mmp/). The Arabi-dopsis Information Resource (TAIR - http://www.arabidopsis.org/) is closely associated with thecollaborative efforts of the Plant Ontology2 Con-sortium. These collaborations are focusing on usingand extending the GO paradigm to the verypressing need for ontology and controlled vocabu-lary development for plant-based databases. TheGO paradigm is effectively described in the GeneralDocumentation at http://www.geneontology.org/GO.doc.html, and in The Gene Ontology Consortium

2000 [1], available at: http://www.geneontology.org/GO_nature_genetics_2000.pdf. A similar ‘GeneralDocumentation’ document is in the process ofbeing developed by the Plant Ontology2 Consor-tium.

Others interested

Database representatives of other plant-based data-bases (e.g. UK CropNet – http://ukcrop.net; NationalInstitute of Agrobiological Sciences – http://www.nias.affrc.go.jp/index_e.html; Max Planck Instituteof Molecular Plant Physiology – http://www.mpimp-golm.mpg.de; International Potato Center –http://www.cipotato.org; Virginia BioinformaticsInstitute – http://www.vbi.vt.edu; John Innes Centre– http://www.jic.bbsrc.ac.uk) and plant scientists

Figure 1. Example of trait ontology (TO) for sterility related trait (TO : 0000485) from Gramene (http://www.gramene.org).Note that this trait illustrates the occurrence of multiple parents, a feature provided by the DAG structuring that isbiologically very meaningful. Selecting any node within the ontology (online) will reveal the associated trait(s) associated withthat node in the DAG structure. The [i] represents a class of semantic relationship between the concepts represented by theterms at the nodes. The [i] represents the is a relationship (‘is an instance of’). The is a relationship is one of subsumption.This relationship permits refinements of concepts (represented by terms) and definitions. Other nodes in the TO atGramene represent part of relationships – another class of semantic relationship between nodes and abbreviated to [p] in theonline trait ontology



associated with various taxa (e.g. Medicago trunca-tula, soybean (Glycine max), common bean (Pha-seolus vulgaris), cassava (Manihot esculenta) andSolanaceae (Lycopersicon and Solanum)) and com-panies involved in genomics, have expressed interestin becoming involved in the collaborative efforts ofthe Plant Ontology2 Consortium.

Online access

A website for the Plant Ontology2 Consortium is tobe developed. The URL is: http://www.plantontology.org. Besides the development of taxon-specific datarepositories for associated controlled vocabulariesand ontologies (e.g. Gramene, MaizeDB, TAIR),

Figure 2. Example of plant ontology (PO) for the ligule of Zea mays, providing the term name, synonym (none for ligule),definition and references for the definition. Note that the ontology has been expanded to reveal the current ontology forsome of the various other nodes associated with the leaf. The [i] and [p] represent classes of semantic relationship betweenthe concepts represented by the terms at the nodes. The [i] represents the is a relationship (‘is an instance of’) as describedin Figure 1. The [p] represents part of relationships (‘is a part of’), another class of semantic relationship between nodes [2].

The Plant Ontology2 Consortium and Plant Ontologies 141


the SPRIG site at http://bioinformatics.org is alsoto be developed as a public repository for plantontology data. [SPRIG=Specialized Plant Resour-ces for Informatics and Genomics]

The Plant Ontology Consortium(Alphabetical list)

Richard Bruskiewich, International Rice ResearchInstitute (IRRI)http://www.irri.orgEdward H. Coe, MaizeDBhttp://www.agron.missouri.edu

Maize Mapping Projecthttp://www.cafnr.missouri.edu/mmp/Pankaj Jaiswal, Cornell University/Gramene: AResource for Comparative Grass Genomicshttp://www.gramene.orgSusan McCouch, Cornell University/Gramene: AResource for Comparative Grass Genomicshttp://www.gramene.org

Mary Polacco, MaizeDBhttp://www.agron.missouri.eduMaize Mapping Projecthttp://www.cafnr.missouri.edu/mmp/Lincoln Stein, Cold Spring Harbor Laboratoryhttp://www.cshl.orgLeszek Vincent, MaizeDBhttp://www.agron.missouri.eduMaize Mapping Projecthttp://www.cafnr.missouri.edu/mmp/Doreen Ware, Cold Spring Harbor Laboratoryhttp://www.cshl.org

References

1. The Gene Ontology Consortium. 2000. Gene Ontology: tool

for the unification of biology. Nature Genet 25: 25-29.

2. The Gene Ontology Consortium. 2001. Creating the gene

ontology resource: design and implementation. Genome Res

11: 1425-1433.



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