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Towards a proteome-scale map of the human protein-protein interaction network
Authors:Rual Jean-François  Venkatesan Kavitha  Hao Tong  Hirozane-Kishikawa Tomoko  Dricot Amélie  Li Ning  Berriz Gabriel F  Gibbons Francis D  Dreze Matija  Ayivi-Guedehoussou Nono  Klitgord Niels  Simon Christophe  Boxem Mike  Milstein Stuart  Rosenberg Jennifer  Goldberg Debra S  Zhang Lan V  Wong Sharyl L  Franklin Giovanni  Li Siming  Albala Joanna S  Lim Janghoo  Fraughton Carlene  Llamosas Estelle  Cevik Sebiha  Bex Camille  Lamesch Philippe  Sikorski Robert S  Vandenhaute Jean  Zoghbi Huda Y  Smolyar Alex  Bosak Stephanie  Sequerra Reynaldo  Doucette-Stamm Lynn  Cusick Michael E  Hill David E  Roth Frederick P  Vidal Marc
Institution:Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, 44 Binney Street, Boston, Massachusetts 02115, USA.
Abstract:Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.
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