Comparing protein abundance and mRNA expression levels on a genomic scale

Area of Science:

• Proteomics and Genomics
• Yeast Molecular Biology

Background:

• Direct correlation between protein abundance and mRNA expression is often inconsistent.
• Understanding this relationship is crucial for systems biology and drug discovery.

Purpose of the Study:

• To review and analyze existing studies correlating protein and mRNA expression levels, with a focus on yeast.
• To develop a comprehensive understanding of the protein-mRNA correlation in yeast by integrating multiple datasets.

Main Methods:

• Survey of experimental techniques for protein abundance determination, including two-dimensional gel electrophoresis and mass spectrometry.
• Integration of multiple yeast protein abundance datasets into a single 'meta-dataset'.
• Statistical analysis to identify correlations between protein and mRNA expression at global and sub-category levels.

Main Results:

• The study confirms variable success in correlating protein and mRNA levels across different studies.
• Analysis of the integrated yeast 'meta-dataset' reveals specific patterns and categories with stronger or weaker correlations.
• Identification of factors influencing the protein-mRNA correlation within yeast.

Conclusions:

• A consolidated analysis of yeast data enhances the understanding of the complex relationship between protein and mRNA expression.
• The findings provide a more robust foundation for future research in yeast functional genomics and proteomics.
• This integrated approach highlights the importance of meta-analysis in systems biology.