Quantitative profiling of proteins, the direct effectors of nearly all biological functions, will undoubtedly complement technologies for the measurement of mRNA. Systematic proteomic measurement of the cell cycle is now possible by using stable isotopic labeling with isotope-coded affinity tag reagents and software tools for high-throughput analysis of LC-MS/MS data. We provide here the first such study achieving quantitative, global proteomic measurement of a time-course gene expression experiment in a model eukaryote, the budding yeast Saccharomyces cerevisiae, during the cell cycle. We sampled 48% of all predicted ORFs, and provide the data, including identifications, quantitations, and statistical measures of certainty, to the community in a sortable matrix. We do not detect significant concordance in the dynamics of the system over the time-course tested between our proteomic measurements and microarray measures collected from similarly treated yeast cultures. Our proteomic dataset therefore provides a necessary and complementary measure of eukaryotic gene expression, establishes a rich database for the functional analysis of S. cerevisiae proteins, and will enable further development of technologies for global proteomic analysis of higher eukaryotes.
|Evidence ID||Analyze ID||Interactor||Interactor Systematic Name||Interactor||Interactor Systematic Name||Type||Assay||Annotation||Action||Modification||Phenotype||Source||Reference||Note|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Gene Ontology Term||Gene Ontology Term ID||Qualifier||Aspect||Method||Evidence||Source||Assigned On||Annotation Extension||Reference|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Phenotype||Experiment Type||Experiment Type Category||Mutant Information||Strain Background||Chemical||Details||Reference|
|Evidence ID||Analyze ID||Regulator||Regulator Systematic Name||Target||Target Systematic Name||Experiment||Assay||Construct||Conditions||Strain Background||Reference|