An empirical framework for binary interactome mapping

Kavitha Venkatesan, Jean François Rual, Alexei Vazquez, Ulrich Stelzl, Irma Lemmens, Tomoko Hirozane-Kishikawa, Tong Hao, Martina Zenkner, Xiaofeng Xin, Kwang Il Goh, Muhammed A. Yildirim, Nicolas Simonis, Kathrin Heinzmann, Fana Gebreab, Julie M. Sahalie, Sebiha Cevik, Christophe Simon, Anne Sophie de Smet, Elizabeth Dann, Alex SmolyarArunachalam Vinayagam, Haiyuan Yu, David Szeto, Heather Borick, Amélie Dricot, Niels Klitgord, Ryan R. Murray, Chenwei Lin, Maciej Lalowski, Jan Timm, Kirstin Rau, Charles Boone, Pascal Braun, Michael E. Cusick, Frederick P. Roth, David E. Hill, Jan Tavernier, Erich E. Wanker, Albert László Barabási, Marc Vidal

Research output: Contribution to journalArticlepeer-review

687 Citations (Scopus)

Abstract

Several attempts have been made to systematically map protein-protein interaction, or 'interactome', networks. However, it remains difficult to assess the quality and coverage of existing data sets. Here we describe a framework that uses an empirically-based approach to rigorously dissect quality parameters of currently available human interactome maps. Our results indicate that high-throughput yeast two-hybrid (HT-Y2H) interactions for human proteins are more precise than literature-curated interactions supported by a single publication, suggesting that HT-Y2H is suitable to map a significant portion of the human interactome. We estimate that the human interactome contains ∼130,000 binary interactions, most of which remain to be mapped. Similar to estimates of DNA sequence data quality and genome size early in the Human Genome Project, estimates of protein interaction data quality and interactome size are crucial to establish the magnitude of the task of comprehensive human interactome mapping and to elucidate a path toward this goal.

Original languageEnglish
Pages (from-to)83-90
Number of pages8
JournalNature Methods
Volume6
Issue number1
DOIs
Publication statusPublished - 2009

Bibliographical note

Funding Information:
We thank members of CCSB and the Vidal, Barabasi, Wanker and Tavernier laboratories and S. Sahasrabuddhe, R. Bell, R. Chettier and C. Wiggins for helpful discussions; E. Smith for help generating Figure 1; and Agencourt Biosciences for sequencing assistance. This work was supported by the US National Human Genome Research Institute (2R01HG001715 and 5P50HG004233 to M.V. and F.P.R.), the US National Cancer Institute (5U54CA112952 to J. Nevins, subcontract to M.V.; and 5U01CA105423 to S.H. Orkin, project to M.V.), the US National Institutes of Health (IH U01 A1070499-01 and U56 CA113004 to A.-L.B. and postdoctoral training grant fellowship T32CA09361 to K.V.), the Ellison Foundation (to M.V.), the W.M. Keck Foundation (to M.V.), Dana-Farber Cancer Institute Institute Sponsored Research funds (to M.V.), the US National Science Foundation (ITR DMR-0926737 and IIS-0513650 to A.-L.B.), Deutsches Bundesministerium für Bildung und Forschung (NGFN2, KB-P04T01, KB-P04T03 and 01GR0471 to E.E.W. and U.S.), Deutsche Forschungsgemeinschaft (SFB 577 and SFB618 to E.E.W.), the University of Ghent and the ‘‘Fonds Wetenschappelijk Onderzoek–Vlaanderen’’ (FWO-V) G.0031.06 (GOA12051401 to J. Tavernier) and the National Cancer Institute of Canada (to C.B.). I.L. is a postdoctoral fellow with the FWO-V. M.V. is a ‘‘Chercheur Qualifié Honoraire’’ from the Fonds de la Recherche Scientifique (French Community of Belgium).

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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