Research article
Gene expression profiling in susceptible interaction of grapevine with its fungal pathogen Eutypa lata: Extending MapMan ontology for grapevine
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* Corresponding authors: Ana Rotter ana.rotter@nib.si - Björn Usadel usadel@mpimp-golm.mpg.de
1 National Institute of Biology, Department of Biotechnology and Systems Biology, Večna pot 111, 1000 Ljubljana, Slovenia
2 Institute of Vine and Wine Sciences (ISVV), University Victor Segalen Bordeaux II, Unite Mixte de Recherches Ecophysiology and Grape Functional Genomics, INRA, 71 Avenue Edouard, Bourlaux 33883, BP 81, Villenave d'Ornon, France
3 Max Planck Institute of Molecular Plant Physiology Am Mühlenberg 1, 14476 Golm, Germany
4 Department of Genetics and Molecular Biology, IASMA Research Center, Via E. Mach 1, 38010 S, Michele a/Adige (TN), Italy
5 Laboratoire de Physiologie et Biochimie Végétales, UMR CNRS 6161, Université de Poitiers, Bâtiment Botanique, 40 Avenue du Recteur Pineau, 86022 Poitiers Cedex, France
BMC Plant Biology 2009, 9:104 doi:10.1186/1471-2229-9-104
Published: 5 August 2009Abstract
Background
Whole genome transcriptomics analysis is a very powerful approach because it gives an overview of the activity of genes in certain cells or tissue types. However, biological interpretation of such results can be rather tedious. MapMan is a software tool that displays large datasets (e.g. gene expression data) onto diagrams of metabolic pathways or other processes and thus enables easier interpretation of results. The grapevine (Vitis vinifera) genome sequence has recently become available bringing a new dimension into associated research. Two microarray platforms were designed based on the TIGR Gene Index database and used in several physiological studies.
Results
To enable easy and effective visualization of those and further experiments, annotation of Vitis vinifera Gene Index (VvGI version 5) to MapMan ontology was set up. Due to specificities of grape physiology, we have created new pictorial representations focusing on three selected pathways: carotenoid pathway, terpenoid pathway and phenylpropanoid pathway, the products of these pathways being important for wine aroma, flavour and colour, as well as plant defence against pathogens. This new tool was validated on Affymetrix microarrays data obtained during berry ripening and it allowed the discovery of new aspects in process regulation. We here also present results on transcriptional profiling of grape plantlets after exposal to the fungal pathogen Eutypa lata using Operon microarrays including visualization of results with MapMan. The data show that the genes induced in infected plants, encode pathogenesis related proteins and enzymes of the flavonoid metabolism, which are well known as being responsive to fungal infection.
Conclusion
The extension of MapMan ontology to grapevine together with the newly constructed pictorial representations for carotenoid, terpenoid and phenylpropanoid metabolism provide an alternative approach to the analysis of grapevine gene expression experiments performed with Affymetrix or Operon microarrays. MapMan was first validated on an already published dataset and later used to obtain an overview of transcriptional changes in a susceptible grapevine – Eutypa lata interaction at the time of symptoms development, where we showed that the responsive genes belong to families known to be involved in the plant defence towards fungal infection (PR-proteins, enzymes of the phenylpropanoid pathway).