Cells respond to their environment by modulating protein levels
through mRNA transcription and post-transcriptional control. Modest observed
correlations between global steady-state mRNA and protein measurements
have been interpreted as evidence that mRNA levels determine
roughly 40% of the variation in protein levels, indicating dominant
post-transcriptional effects. However, the techniques underlying these
conclusions, such as correlation and regression, yield biased results
when data are noisy, missing systematically, and collinear—properties
of mRNA and protein measurements—which motivated us to revisit this
subject. Noise-robust analyses of 24 studies of budding yeast reveal
that mRNA levels explain more than 85% of the variation in steady-state
protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.
Code is available on GitHub (see sidebar).
git clone email@example.com:dad/mrna-prot.git