An essential step to understand the function of a protein is to identify other proteins with which it interacts. One of the most effective methods for identifying and measuring biologically important protein-protein interactions is the yeast two-hybrid system. The goal of this project is to implement a high-throughput yeast two-hybrid approach to identify the binary interactions among most of the proteins encoded by the Drosophila genome. The resulting protein interaction map will be a valuable resource for generating and testing hypotheses about protein and pathway function. Because many molecular pathways are evolutionarily conserved, the Drosophila interaction map will provide a foundation for understanding homologous protein networks in humans and other organisms. To construct the map, the protein-coding regions of most Drosophila genes will be amplified using gene-specific primer pairs. The resulting set of PCR products will provide a starting point for efficient transfer of the open reading frames (ORFs) into a number of useful vectors. and thus will be a valuable resource for a variety of projects. For this project, the Drosophila ORFs will be transferred into two yeast two-hybrid vectors, one for expressing DNA-binding domain (DBD) fusions and one for expressing activation domain (AD) fusions. The constructs will be introduced into specialized yeast strains to create two arrays of yeast. To test for interactions between members of the two arrays, reporter gene activity will be assessed after the arrays are mated using a high-throughput strategy developed in this laboratory. The protein interaction data will be placed into a publicly accessible database, designed specifically to enable extraction of useful biological information from yeast two-hybrid data. When combined with sequence information and data from other functional genomics approaches, the interaction data will provide a powerful resource to help researchers understand how groups of genes work together to mediate complex biological processes.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
3R01HG001536-08S1
Application #
7158927
Study Section
Genome Study Section (GNM)
Program Officer
Feingold, Elise A
Project Start
1996-03-01
Project End
2006-06-30
Budget Start
2004-01-01
Budget End
2006-06-30
Support Year
8
Fiscal Year
2006
Total Cost
$131,618
Indirect Cost
Name
Wayne State University
Department
Genetics
Type
Schools of Medicine
DUNS #
001962224
City
Detroit
State
MI
Country
United States
Zip Code
48202
Atikukke, Govindaraja; Albosta, Paul; Zhang, Huamei et al. (2014) A role for Drosophila Cyclin J in oogenesis revealed by genetic interactions with the piRNA pathway. Mech Dev 133:64-76
Murali, Thilakam; Pacifico, Svetlana; Finley Jr, Russell L (2014) Integrating the interactome and the transcriptome of Drosophila. BMC Bioinformatics 15:177
Mairiang, Dumrong; Zhang, Huamei; Sodja, Ann et al. (2013) Identification of new protein interactions between dengue fever virus and its hosts, human and mosquito. PLoS One 8:e53535
Guest, Stephen T; Yu, Jingkai; Liu, Dongmei et al. (2011) A protein network-guided screen for cell cycle regulators in Drosophila. BMC Syst Biol 5:65
Murali, Thilakam; Pacifico, Svetlana; Yu, Jingkai et al. (2011) DroID 2011: a comprehensive, integrated resource for protein, transcription factor, RNA and gene interactions for Drosophila. Nucleic Acids Res 39:D736-43
Friedman, Adam A; Tucker, George; Singh, Rohit et al. (2011) Proteomic and functional genomic landscape of receptor tyrosine kinase and ras to extracellular signal-regulated kinase signaling. Sci Signal 4:rs10
Liu, Dongmei; Finley Jr, Russell L (2010) Cyclin Y is a novel conserved cyclin essential for development in Drosophila. Genetics 184:1025-35
Liu, Dongmei; Guest, Stephen; Finley Jr, Russell L (2010) Why cyclin Y? A highly conserved cyclin with essential functions. Fly (Austin) 4:278-82
Yu, Jingkai; Finley Jr, Russell L (2009) Combining multiple positive training sets to generate confidence scores for protein-protein interactions. Bioinformatics 25:105-11
Schwartz, Ariel S; Yu, Jingkai; Gardenour, Kyle R et al. (2009) Cost-effective strategies for completing the interactome. Nat Methods 6:55-61

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