ArticlePLoS genetics2015
Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast.
Article in PLoS genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers, 1 of them a synthesis that pooled it.
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Who cites it
111 citing papers in PubMed, 1 synthesis or guideline pooled it, 199 citations in OpenAlex.
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- Twenty-Five Years of the Environmental Stress Response and the Enduring Power of Yeast in Stress Biology.Yeast (Chichester, England) · 2026Review
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- An integrated transcriptomic and proteomic map of the mouse hippocampus at synaptic resolution.Nature communications · 2025Article
- Proteomic compensation by paralogs preserves protein interaction networks after gene loss in cancer.Molecular systems biology · 2025Article
- Chronology of transcriptome and proteome expression during early Arabidopsis flower development.Journal of experimental botany · 2025Article
- Regulation of the expression of ferrochelatase in a murine model of diabetes mellitus type I.Biochemistry and biophysics reports · 2025Article
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- Macroevolutionary divergence of gene expression driven by selection on protein abundance.Science (New York, N.Y.) · 2025Article
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- Multi-omics analysis of aggregative multicellularity.iScience · 2024Article
- Single-molecule fluorescence multiplexing by multi-parameter spectroscopic detection of nanostructured FRET labels.Nature nanotechnology · 2024Article
51 more citing papers are in PubMed but not listed here.
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5 authors at 2 institutions in 1 country.
Funding
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.
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