Based on large-scale data for the yeast Saccharomyces cerevisiae (protein and mRNA abundance, translational status, transcript length), we investigate the relation of transcription, translation, and protein turnover on a genome-wide scale. We elucidate variations between different spatial cell compartments and functional modules by comparing protein-to-mRNA ratios, translational activity, and a novel descriptor for protein-specific degradation (protein half-life descriptor). This analysis helps to understand the cell's strategy to use transcriptional and posttranscriptional regulation mechanisms for managing protein levels. For instance, it is possible to identify modules that are subject to suppressed translation under normal conditions ("translation on demand"). In order to reduce inconsistencies between the datasets, we compiled a new reference mRNA abundance dataset and we present a novel approach to correct large microarray signals for a saturation bias. Accounting for ribosome density based on transcript length rather than ORF length improves the correlation of observed protein levels to translational activity. We discuss potential causes for the deviations of these correlations. Finally, we introduce a quantitative descriptor for protein degradation (protein half-life descriptor) and compare it to measured half-lives. The study demonstrates significant post-transcriptional control of protein levels for a number of different compartments and functional modules, which is missed when exclusively focusing on transcript levels. Molecular & Cellular Proteomics 3:1083-1092, 2004.Recent publication of high-throughput data of the yeast Saccharomyces cerevisiae (1-3) opens the possibility to analyze the relationship between protein abundance, mRNA levels, and translational status on a genome-wide scale. Often mRNA abundance is used as a surrogate for protein amounts. Most studies employing cDNA microarrays assume that a high transcription of an ORF correlates with a high abundance of the corresponding protein. Previous studies either could not find a correlation between protein and mRNA abundance (4) or the correlation was only weak (5-8). Greenbaum and coworkers (7) discuss three potential reasons for the lack of a perfect correlation between mRNA and protein levels: i) translational regulation, ii) difference of in vivo protein half-lives, and iii) the significant amount of experimental error including differences with respect to the experimental conditions. Understanding post-transcriptional regulation is crucial for correctly interpreting gene expression data. A full understanding of cell responses to external stimuli includes both transcription and translation regulation (6, 9, 10). It is important to distinguish processes regulating the overall translation (such as the total number or activity of available ribosomes) from protein-specific mechanisms of translation regulation (11-13). In addition to these translation-related mechanisms, selective degradation of proteins (protein turnover) regulates the cellula...