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Assigning function to yeast proteins by integration of technologies.

Type Information
Nr 5 (Research article)
Authors Hazbun, Tony; Malmström, Lars; Anderson, Scott; Graczyk, Beth; Fox, Bethany; Riffle, Michael; Sundin, Bryan; Aranda, J; McDonald, W; Chiu, Chun-Hwei; Snydsman, Brian; Bradley, Phillip; Muller, Eric; Fields, Stanley; Baker, David; Yates, John; Davis, Trisha
Title Assigning function to yeast proteins by integration of technologies.
Journal Mol Cell (2003) 12 1353-65
DOI 10.1016/s1097-2765(03)00476-3
Citations 311 citations (journal impact: 16.84)
Abstract Interpreting genome sequences requires the functional analysis of thousands of predicted proteins many of which are uncharacterized and without obvious homologs. To assess whether the roles of large sets of uncharacterized genes can be assigned by targeted application of a suite of technologies we used four complementary protein-based methods to analyze a set of 100 uncharacterized but essential open reading frames ORFs of the yeast Saccharomyces cerevisiae. These proteins were subjected to affinity purification and mass spectrometry analysis to identify copurifying proteins two-hybrid analysis to identify interacting proteins fluorescence microscopy to localize the proteins and structure prediction methodology to predict structural domains or identify remote homologies. Integration of the data assigned function to 48 ORFs using at least two of the Gene Ontology GO categories of biological process molecular function and cellular component 77 ORFs were annotated by at least one method. This combination of technologies coupled with annotation using GO is a powerful approach to classifying genes.