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

Haiyuan Yu(Harvard University), Pascal Falter‐Braun(Harvard University), Muhammed A. Yıldırım(Harvard University), Irma Lemmens(Harvard University), K. Venkatesan(Harvard University), Julie M. Sahalie(Harvard University), Tomoko Hirozane-Kishikawa(Harvard University), Fana Gebreab(Harvard University), Na Li(Harvard University), Nicolas Simonis(Harvard University), Tong Hao(Harvard University), Jean‐François Rual(Harvard University), Amélie Dricot(Harvard University), Alexei Vázquez(Harvard University), Ryan R. Murray(Harvard University), Christophe Simon(Harvard University), Leah Tardivo(Harvard University), Stanley Tam(Harvard University), Nenad Svrzikapa(Harvard University), Changyu Fan(Harvard University), A. De Smet(Harvard University), Adriana Motyl(Harvard University), Michael E. Hudson(Harvard University), Juyong Park(Northeastern University), Xiaofeng Xin(Harvard University), Michael E. Cusick(Harvard University), Troy Moore(Harvard University), Charlie Boone(Harvard University), M Snyder(Harvard University), Frederick P. Roth(Harvard University), Albert-Ĺaszló Barabási(Northeastern University), Jan Tavernier(Harvard University), David E. Hill(Harvard University), Marc Vidal(Harvard University)
Science
August 21, 2008
Cited by 1,426Open Access
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Abstract

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 approximately 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.


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