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Comparative and Functional Genomics
Volume 6, Issue 7-8, Pages 388-397
Research article

Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages

1Department of Plant Breeding, 240 Emerson Hall, Cornell University, Ithaca, NY 14853, USA
2Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA
3Department of Plant Biology, Carnegie Institution of Washington, 260 Panama Street, Stanford, CA 94305, USA
4Department of Biology, University of Missouri at St. Louis, St. Louis, MO 63121, USA
5Maize Genetics Cooperation, Stock Center, Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA
6Agricultural Research Service, United States Department of Agriculture, Soil and Nutrition Laboratory Research Unit, Cornell University, Ithaca, NY 14853, USA
7Curtis Hall, University of Missouri at Columbia, Columbia, MO 65211, USA
8Missouri Botanical Garden, 4344-Shaw Boulevard, St. Louis, MO 63110, USA

Received 19 September 2005; Revised 21 October 2005; Accepted 7 November 2005

Copyright © 2005 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The Plant Ontology Consortium (POC) ( is a collaborative effort among several plant databases and experts in plant systematics, botany and genomics. A primary goal of the POC is to develop simple yet robust and extensible controlled vocabularies that accurately reflect the biology of plant structures and developmental stages. These provide a network of vocabularies linked by relationships (ontology) to facilitate queries that cut across datasets within a database or between multiple databases. The current version of the ontology integrates diverse vocabularies used to describe Arabidopsis, maize and rice (Oryza sp.) anatomy, morphology and growth stages. Using the ontology browser, over 3500 gene annotations from three species-specific databases, The Arabidopsis Information Resource (TAIR) for Arabidopsis, Gramene for rice and MaizeGDB for maize, can now be queried and retrieved.