Accounting for Experimental Noise Reveals That mRNA Levels, Amplified by Post-Transcriptional Processes, Largely Determine Steady-State Protein Levels in Yeast

Abstract

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.

Improved Ribosome-Footprint and mRNA Measurements Provide Insights into Dynamics and Regulation of Yeast Translation

“…Although the range of IEs was marginally wider than that of TEs (1–99 percentile spanning 21 fold, Figure S6B), it was still substantially smaller than the range of TEs initially reported (Ingolia et al, 2009). The relatively narrow range of IEs in our data was also reflected by the high correlation between mRNA abundance and protein-synthesis rate ( R = 0.948; Figure 5B), supporting the conclusion that protein-synthesis rates are largely dictated by mRNA abundances (Csárdi et al 2015). Interestingly, the slope of the regression between mRNA and protein-synthesis rates was >1 on the log-scale, indicating that translation regulation mostly amplifies the effect of differential mRNA abundances rather than buffering it (Csardi et al, 2015).…”

“…The relatively narrow range of IEs in our data was also reflected by the high correlation between mRNA abundance and protein-synthesis rate ( R = 0.948; Figure 5B), supporting the conclusion that protein-synthesis rates are largely dictated by mRNA abundances (Csárdi et al 2015). Interestingly, the slope of the regression between mRNA and protein-synthesis rates was >1 on the log-scale, indicating that translation regulation mostly amplifies the effect of differential mRNA abundances rather than buffering it (Csardi et al, 2015). Further indicating that mRNA abundance (when accurately measured) is a strong predictor of total protein production, mass-spectrometry-based measurements of steady-state protein abundance (de Godoy et al, 2008) correlated as well with mRNA abundances as they did with protein-synthesis rates (Figure 5C).…”

“…Variation in protein abundances observed in yeast cells largely reflects variation in mRNA abundances, indicating that much of gene regulation occurs at the level of mRNA synthesis and decay (Greenbaum et al, 2003; Csardi et al, 2015). However, differences in translation rates also contribute.…”

Stress-Triggered Phase Separation Is an Adaptive, Evolutionarily Tuned Response

“…We used Pab1 at 15μM. Pab1 is not induced during heat shock, and has a log-phase concentration of roughly 20μM, ~120,000 molecules per cell (Csárdi et al, 2015) almost entirely in the cytosol (Wallace et al, 2015) assuming a cytosolic volume of 10 fL.…”

Reduced changes in protein compared to mRNA levels across non-proliferating tissues

“…We can infer the Pearson correlation between the latent variables φ and ψ, given N measurements of φ, marked x 1 , …,  x N , and M measurements of ψ, marked y 1 , …,  y M . The following estimator for the Pearson correlation between φ and ψ is then used [12]: …”