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Mammalian gene expression shows modest correlation between transcript and protein levels, with transcripts better predicting clinical traits than proteins. This impacts high-throughput research applications.

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Area of Science:

  • Genomics
  • Proteomics
  • Systems Biology

Background:

  • The correlation between messenger RNA (mRNA) transcript levels and their corresponding protein levels is crucial for understanding gene expression regulation.
  • Previous studies in yeast and plants indicated a modest correlation, but comprehensive analysis in mammals was lacking.

Purpose of the Study:

  • To investigate the relationship between transcript and protein levels in mammals using natural genetic variation.
  • To identify factors influencing this relationship and its impact on clinical trait associations.

Main Methods:

  • Quantified over 22,000 transcripts via microarray and over 5,000 peptides via Liquid Chromatography-Mass Spectrometry in 97 mouse strains.
  • Focused on highly heritable transcripts and reliable proteins.
  • Utilized genome-wide association analyses to map regulatory loci.

Main Results:

  • A significant correlation between transcript and protein levels was observed for only about half of the genes, with an average correlation of 0.27.
  • Correlation strength varied by gene's cellular location and biological function.
  • Little overlap was found between loci controlling transcript levels and those controlling protein levels.
  • Transcript levels showed a stronger correlation with clinical traits (e.g., adiposity) than protein levels.

Conclusions:

  • The transcript-protein correlation in mammals is modest and gene-specific.
  • Genetic loci influencing transcript and protein levels are largely distinct.
  • Transcript levels may be more informative than protein levels for certain clinical trait predictions in high-throughput studies.