ArticlePlant physiology2007
A predicted interactome for Arabidopsis.
Article in Plant physiology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 144 papers, 2 of them syntheses that pooled it.
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Who cites it
144 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Interactomics in plant defence: progress and opportunities.Molecular biology reports · 2023Pooled it
- A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens.PloS one · 2012Pooled it
- Chemical Genetics with SP600125 Reveals That Mps1 Protein Kinase Works as a Regulatory Element in Post-embryonic Development of theACS omega · 2025Article
- An Introduction to Network Analysis in Plant Biology.Plant direct · 2025Article
- 20 years of the Bio-Analytic Resource for Plant Biology.Nucleic acids research · 2025Article
- Decoding the Hayward kiwi (Frontiers in plant science · 2025Article
- TurboID-based proteomic profiling reveals proxitome of ASK1 and CUL1 of the SCF ubiquitin ligase in plants.The New phytologist · 2024Article
- Review
- Homologous mapping yielded a comprehensive predicted protein-protein interaction network for peanut (Arachis hypogaea L.).BMC plant biology · 2024Article
- Reconstruction ofCurrent issues in molecular biology · 2024Article
- Structure-based prediction of protein-protein interaction network in rice.Genetics and molecular biology · 2024Article
- Article
- Short Interrupted Repeat Cassette (SIRC)-Novel Type of Repetitive DNA Element Found inInternational journal of molecular sciences · 2023Article
- Use ofHeliyon · 2023Article
- SUMO E3 ligase SIZ1 connects sumoylation and reactive oxygen species homeostasis processes in Arabidopsis.Plant physiology · 2022Article
- An interolog-based barley interactome as an integration framework for immune signaling.Genetics · 2022Article
- CPIELA: Computational Prediction of Plant Protein-Protein Interactions by Ensemble Learning Approach From Protein Sequences and Evolutionary Information.Frontiers in genetics · 2022Article
- Deep learning frameworks for protein-protein interaction prediction.Computational and structural biotechnology journal · 2022Review
- The key clock component ZEITLUPE (ZTL) negatively regulates ABA signaling by degradation of CHLH in Arabidopsis.Frontiers in plant science · 2022Article
- Actin and Microtubules Differently Contribute to Vacuolar Targeting Specificity during the Export from the ER.Membranes · 2021Article
84 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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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