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Published on August 3, 2007; 10.1104/pp.107.103465


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Received June 5, 2007
Accepted July 27, 2007

A Predicted Interactome for Arabidopsis

Jane Geisler-Lee , Nicholas O'Toole , Ron Ammar , Nicholas J. Provart , A. Harvey Millar , and Matt Geisler *

Department of Plant Biology, Southern Illinois University Carbondale, Carbondale Illinois, 62901, USA; ARC Centre of Excellence in Plant Energy Biology, University of Western Australia, Crawley WA 6009, Australia; Department of Cell & Systems Biology, University of Toronto, Toronto Ontario, M5S 3B2, Canada

* Corresponding author; email: mgeisler{at}plant.siu.edu.

The complex cellular functions of an organism frequently rely on physical interactions between proteins. A map of all protein-protein interactions, an interactome, is thus an invaluable tool. We present an interactome for Arabidopsis thaliana predicted from interacting orthologs in yeast, worm, fruit fly and human. As an internal quality control, a confidence value was generated based on the amount of supporting evidence for each interaction. A total of 1159 high confidence, 5913 medium confidence and 12907 low confidence interactions were identified for 3617 conserved Arabidopsis proteins. There was significant co-expression of genes whose proteins were predicted to interact, even amongst low confidence interactions. Interacting proteins were also significantly more likely to be found within the same subcellular location, and significantly less likely to be found in conflicting localizations than randomly paired proteins. A notable exception was that proteins located in the Golgi were more likely to interact with Golgi, vacuolar, or ER sorted proteins, indicating possible docking or trafficking interactions. These predictions can aid researchers by extending known complexes and pathways with candidate proteins. In addition we have predicted interactions for many previously unknown proteins in known pathways and complexes. We present this interactome, and an online web interface the Arabidopsis Interactions Viewer, as a first step towards understanding global signaling in Arabidopsis, and to whet the appetite for those who are awaiting results from high throughput experimental approaches.




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