期刊论文详细信息
G3: Genes, Genomes, Genetics
Predicting the Fission Yeast Protein Interaction Network
Andreas Beyer2  Jürg Bähler1  Ömer S. Saraç2  Janel R. McLean3  Vera Pancaldi1  Charalampos Rallis1  Kathleen Gould3  Martin Převorovský1 
[1] Department of Genetics, Evolution, and EnvironmentUCL Cancer Institute, University College London, London WC1E 6BT, United KingdomDepartment of Genetics, Evolution, and EnvironmentDepartment of Genetics, Evolution, and EnvironmentUCL Cancer Institute, University College London, London WC1E 6BT, United KingdomUCL Cancer Institute, University College London, London WC1E 6BT, United KingdomDepartment of Genetics, Evolution, and EnvironmentUCL Cancer Institute, University College London, London WC1E 6BT, United Kingdom;Cellular Networks and Systems Biology, Biotechnology Center, Dresden University of Technology (TU Dresden), Dresden 01307, GermanyCellular Networks and Systems Biology, Biotechnology Center, Dresden University of Technology (TU Dresden), Dresden 01307, GermanyCellular Networks and Systems Biology, Biotechnology Center, Dresden University of Technology (TU Dresden), Dresden 01307, Germany;Howard Hughes Medical InstituteDepartment of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee 37232Howard Hughes Medical InstituteHoward Hughes Medical InstituteDepartment of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee 37232Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee 37232Howard Hughes Medical InstituteDepartment of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee 37232
关键词: Cbf11;    TOR;    Mak1/2/3;    support vector machine;    random forest;   
DOI  :  10.1534/g3.111.001560
学科分类:生物科学(综合)
来源: Genetics Society of America
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【 摘 要 】

A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein–protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70–80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt).

【 授权许可】

Unknown   

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