Assigning function to yeast proteins by integration of technologies

TitleAssigning function to yeast proteins by integration of technologies
Publication TypeJournal Article
Year of Publication2003
AuthorsHazbun, T. R., Malmström L., Anderson S., Graczyk B. J., Fox B., Riffle M., Sundin B. A., Aranda D. J., McDonald H. W., Chiu C. - H., Snydsman B. E., Bradley P., Muller E. G. D., Fields S., Baker D., Yates J. R., & Davis T. N.
JournalMolecular cell
Volume12
Issue6
Pagination1353-65
Date Published2003 Dec
ISSN1097-2765
KeywordsComputational Biology, Genome, Fungal, Oligonucleotide Array Sequence Analysis, Open Reading Frames, Primary Publication, Proteome, Saccharomyces cerevisiae Proteins, Two-Hybrid System Techniques
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.

Alternate JournalMol. Cell
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