Literature DB >> 17675552

A predicted interactome for Arabidopsis.

Jane Geisler-Lee1, Nicholas O'Toole, Ron Ammar, Nicholas J Provart, A Harvey Millar, Matt Geisler.   

Abstract

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 (Arabidopsis thaliana) predicted from interacting orthologs in yeast (Saccharomyces cerevisiae), nematode worm (Caenorhabditis elegans), fruitfly (Drosophila melanogaster), and human (Homo sapiens). As an internal quality control, a confidence value was generated based on the amount of supporting evidence for each interaction. A total of 1,159 high confidence, 5,913 medium confidence, and 12,907 low confidence interactions were identified for 3,617 conserved Arabidopsis proteins. There was significant coexpression of genes whose proteins were predicted to interact, even among 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 endoplasmic reticulum 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 toward 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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Year:  2007        PMID: 17675552      PMCID: PMC2048726          DOI: 10.1104/pp.107.103465

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  42 in total

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2.  BIND: the Biomolecular Interaction Network Database.

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Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

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6.  Towards a proteome-scale map of the human protein-protein interaction network.

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9.  A map of the interactome network of the metazoan C. elegans.

Authors:  Siming Li; Christopher M Armstrong; Nicolas Bertin; Hui Ge; Stuart Milstein; Mike Boxem; Pierre-Olivier Vidalain; Jing-Dong J Han; Alban Chesneau; Tong Hao; Debra S Goldberg; Ning Li; Monica Martinez; Jean-François Rual; Philippe Lamesch; Lai Xu; Muneesh Tewari; Sharyl L Wong; Lan V Zhang; Gabriel F Berriz; Laurent Jacotot; Philippe Vaglio; Jérôme Reboul; Tomoko Hirozane-Kishikawa; Qianru Li; Harrison W Gabel; Ahmed Elewa; Bridget Baumgartner; Debra J Rose; Haiyuan Yu; Stephanie Bosak; Reynaldo Sequerra; Andrew Fraser; Susan E Mango; William M Saxton; Susan Strome; Sander Van Den Heuvel; Fabio Piano; Jean Vandenhaute; Claude Sardet; Mark Gerstein; Lynn Doucette-Stamm; Kristin C Gunsalus; J Wade Harper; Michael E Cusick; Frederick P Roth; David E Hill; Marc Vidal
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10.  Global landscape of protein complexes in the yeast Saccharomyces cerevisiae.

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Journal:  Nature       Date:  2006-03-22       Impact factor: 49.962

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  129 in total

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5.  Rational association of genes with traits using a genome-scale gene network for Arabidopsis thaliana.

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6.  Web-based Arabidopsis functional and structural genomics resources.

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7.  Genome-wide computational function prediction of Arabidopsis proteins by integration of multiple data sources.

Authors:  Yiannis A I Kourmpetis; Aalt D J van Dijk; Roeland C H J van Ham; Cajo J F ter Braak
Journal:  Plant Physiol       Date:  2010-11-22       Impact factor: 8.340

8.  HOS15 Interacts with the Histone Deacetylase HDA9 and the Evening Complex to Epigenetically Regulate the Floral Activator GIGANTEA.

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Journal:  Plant Cell       Date:  2019-01-03       Impact factor: 11.277

9.  VirtualPlant: a software platform to support systems biology research.

Authors:  Manpreet S Katari; Steve D Nowicki; Felipe F Aceituno; Damion Nero; Jonathan Kelfer; Lee Parnell Thompson; Juan M Cabello; Rebecca S Davidson; Arthur P Goldberg; Dennis E Shasha; Gloria M Coruzzi; Rodrigo A Gutiérrez
Journal:  Plant Physiol       Date:  2009-12-09       Impact factor: 8.340

10.  CORNET: a user-friendly tool for data mining and integration.

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