W463 Annotating Gene Expression in Physcomitrella patens using the Plant Ontology: Facilitating Cross-Taxa Comparisons

Date: Saturday, January 14, 2012
Time: 5:10 PM
Room: Sunrise
Laurel Cooper , Oregon State University, Corvallis, OR
Ramona Walls , New York Botanical Garden, Bronx, NY
Justin L. Elser , Oregon State University, Corvallis, OR
Justin Preece , Oregon State University, Corvallis, OR
Barry Smith , Department of Philosophy, University at Buffalo, Buffalo, NY
Chris Mungall , Lawrence Berkeley National Lab, Berkeley, CA
Stefan Rensing , Faculty of Biology, University of Freiburg, Germany
Manuel Hiss , Faculty of Biology, University of Freiburg, Germany
Péter Szövényi , Swiss Institute of Bioinformatics, Switzerland
Daniel Lang , University of Freiburg Plant Biotechnology
Marie A. Gandolfo , Department of Plant Biology, Cornell University, Ithaca, NY
Dennis Wm. Stevenson , New York Botanical Garden, Bronx, NY
Pankaj Jaiswal , Oregon State University, Corvallis, OR
The Plant Ontology (PO: http://www.plantontology.org) is a structured vocabulary and database resource for all plant scientists that links plant anatomy, morphology and development to the rapidly expanding field of plant genomics.  Recent changes in the PO include the addition of more than 80 new terms to accommodate non-seed plants, with an emphasis on those needed to annotate gene expression from the Physcomitrella patens genome.  The primary purpose of the PO is to facilitate cross-database querying and to foster consistent use of vocabularies in annotation.  The use of ontologies ensures consistent annotations within and across species, enabling both prediction of gene function and cross-species comparisons of gene expression.  An essential, powerful feature of the PO is the set of links from terms to associated annotations, which are structure- or development-specific genes, proteins and phenotypes sourced from numerous plant genomics datasets.  Currently, the PO includes over 2 million annotations associated with over 1,300 terms.  We will give a brief tutorial on how to access the PO and associated data, and demonstrate the utility of linking Physcomitrella gene expression data to PO terms.   The combination of ontology terms and the annotation of diverse gene expression and phenotype data sets facilitates diverse analyses, including assessing the similarity between genes of inter- or intra-specific origin and the exploration of structural homologies among organs, tissues and cell types.