Gene expression analyzed by high-resolution state array analysis and quantitative proteomics

Vivian L. MacKay, Xiaohong Li, Mark R. Flory, Eileen Turcott, G. Lynn Law, Kyle A. Serikawa, X. L. Xu, Hookeun Lee, D. R. Goodlett, Ruedi Aebersold, Lue Ping Zhao, David R. Morris

Research output: Contribution to journalArticle

145 Scopus citations

Abstract

The transcriptome provides the database from which a cell assembles its collection of proteins. Translation of individual mRNA species into their encoded proteins is regulated, producing discrepancies between mRNA and protein levels. Using a new modeling approach to data analysis, a striking diversity is revealed in association of the transcriptome with the translational machinery. Each mRNA has its own pattern of ribosome loading, a circumstance that provides an extraordinary dynamic range of regulation, above and beyond actual transcript levels. Using this approach together with quantitative proteomics, we explored the immediate changes in gene expression in response to activation of a mitogen-activated protein kinase pathway in yeast by mating pheromone. Interestingly, in 26% of those transcripts where the predicted protein synthesis rate changed by at least 3-fold, more than half of these changes resulted from altered translational efficiencies. These observations underscore that analysis of transcript level, albeit extremely important, is insufficient by itself to describe completely the phenotypes of cells under different conditions.

Original languageEnglish (US)
Pages (from-to)478-489
Number of pages12
JournalMolecular and Cellular Proteomics
Volume3
Issue number5
DOIs
StatePublished - May 1 2004

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Molecular Biology

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    MacKay, V. L., Li, X., Flory, M. R., Turcott, E., Law, G. L., Serikawa, K. A., Xu, X. L., Lee, H., Goodlett, D. R., Aebersold, R., Zhao, L. P., & Morris, D. R. (2004). Gene expression analyzed by high-resolution state array analysis and quantitative proteomics. Molecular and Cellular Proteomics, 3(5), 478-489. https://doi.org/10.1074/mcp.M300129-MCP200