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Originally published in Science Express on 21 August 2008
Science 3 October 2008:
Vol. 322. no. 5898, pp. 104 - 110
DOI: 10.1126/science.1158684
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Reports

High-Quality Binary Protein Interaction Map of the Yeast Interactome Network

Haiyuan Yu,1,2* Pascal Braun,1,2* Muhammed A. Yildirim,1,2,3* Irma Lemmens,4 Kavitha Venkatesan,1,2 Julie Sahalie,1,2 Tomoko Hirozane-Kishikawa,1,2 Fana Gebreab,1,2 Na Li,1,2 Nicolas Simonis,1,2 Tong Hao,1,2 Jean-François Rual,1,2 Amélie Dricot,1,2 Alexei Vazquez,5 Ryan R. Murray,1,2 Christophe Simon,1,2 Leah Tardivo,1,2 Stanley Tam,1,2 Nenad Svrzikapa,1,2 Changyu Fan,1,2 Anne-Sophie de Smet,4 Adriana Motyl,6 Michael E. Hudson,6 Juyong Park,1,7 Xiaofeng Xin,8 Michael E. Cusick,1,2 Troy Moore,9 Charlie Boone,8 Michael Snyder,6 Frederick P. Roth,1,10 Albert-László Barabási,1,7 Jan Tavernier,4 David E. Hill,1,2 Marc Vidal1,2{dagger}

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a "second-generation" high-quality, high-throughput Y2H data set covering ~20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.

1 Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02115, USA.
2 Department of Cancer Biology, Dana-Farber Cancer Institute, and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
3 School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
4 Department of Medical Protein Research, VIB, and Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, 9000 Ghent, Belgium.
5 The Simons Center for Systems Biology, Institute for Advanced Studies, Princeton, NJ 08540, USA.
6 Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06620, USA.
7 Center for Complex Network Research and Departments of Physics, Biology, and Computer Science, Northeastern University, Boston, MA 02115, USA.
8 Banting and Best Department of Medical Research and Department of Medical Genetics and Microbiology, Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada.
9 Open Biosystems, Huntsville, AL 35806, USA.
10 Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA.

* These authors contributed equally to this work.

{dagger} To whom correspondence should be addressed. E-mail: marc_vidal{at}dfci.harvard.edu

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