Human ORFeome Version 1.1: A Platform for Reverse Proteomics

Jean‐François Rual(Dana-Farber Cancer Institute), Tomoko Hirozane-Kishikawa(Harvard University), Tong Hao(Harvard University), Nicolas Bertin(Centre National de la Recherche Scientifique), Siming Li(Harvard University), Amélie Dricot(Harvard University), Ning Li(Harvard University Press), Jennifer Rosenberg(Harvard University), Philippe Lamesch(Harvard University), Pierre‐Olivier Vidalain(Harvard University), Tracey R. Clingingsmith(Harvard University), James L. Hartley(Harvard University), Dominic Esposito(National Cancer Institute), David L. Cheo, Troy Moore, Blake A. Simmons, Reynaldo Sequerra(Akston Biosciences (United States)), Stephanie Bosak(Akston Biosciences (United States)), Lynn Doucette‐Stamm(Akston Biosciences (United States)), Christian Le Peuch(Centre de Recherche en Biologie cellulaire de Montpellier), Jean Vandenhaute(University of Namur), Michael E. Cusick(Harvard University), Joanna S. Albala(Lawrence Livermore National Laboratory), David E. Hill(Harvard University), Marc Vidal(Harvard University)
Genome Research
October 15, 2004
10.1101/gr.2973604
Cited by 252Open Access
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Abstract

The advent of systems biology necessitates the cloning of nearly entire sets of protein-encoding open reading frames (ORFs), or ORFeomes, to allow functional studies of the corresponding proteomes. Here, we describe the generation of a first version of the human ORFeome using a newly improved Gateway recombinational cloning approach. Using the Mammalian Gene Collection (MGC) resource as a starting point, we report the successful cloning of 8076 human ORFs, representing at least 7263 human genes, as mini-pools of PCR-amplified products. These were assembled into the human ORFeome version 1.1 (hORFeome v1.1) collection. After assessing the overall quality of this version, we describe the use of hORFeome v1.1 for heterologous protein expression in two different expression systems at proteome scale. The hORFeome v1.1 represents a central resource for the cloning of large sets of human ORFs in various settings for functional proteomics of many types, and will serve as the foundation for subsequent improved versions of the human ORFeome.

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