ArticlePeerJ2014
System wide analyses have underestimated protein abundances and the importance of transcription in mammals.
Article in PeerJ, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 164 papers.
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Who cites it
164 citing papers in PubMed, 300 citations in OpenAlex.
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- Body-Wide Expression Profiles of Commonly Assessed Cardiac Biomarkers in a Large Cohort of Human Tissue Donors.Cardiology · 2026Article
- Coupling mechanisms coordinating mRNA translation with stages of the mRNA lifecycle.RNA biology · 2025Review
- mRNABERT: advancing mRNA sequence design with a universal language model and comprehensive dataset.Nature communications · 2025Article
- RNADecayCafe, a uniformly processed atlas of RNA half-life estimates across multiple human cell lines.bioRxiv : the preprint server for biology · 2025Article
- Single-cell spatial proteomics.Histology and histopathology · 2025Review
- Acute neuroendocrine challenge elicits enhanced cortisol response and parallel transcriptomic changes in patients with migraine.Pain reports · 2025Article
- Quantifying Transcriptome Turnover on Phylogenies by Modeling Gene Expression as a Binary Trait.Molecular biology and evolution · 2025Article
- Gene Signatures and Oncology Treatment Implications.Hematology/oncology clinics of North America · 2025Review
- Macroevolutionary divergence of gene expression driven by selection on protein abundance.Science (New York, N.Y.) · 2025Article
- Integrating transcriptomic and proteomic analyses reveals impaired carbohydrate metabolism in tobacco cytoplasmic male sterility.Frontiers in plant science · 2025Article
- Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet.Genome biology · 2024Article
- MiREx: mRNA levels prediction from gene sequence and miRNA target knowledge.BMC bioinformatics · 2023Article
- Gene expression flux analysis reveals specific regulatory modalities of gene expression.iScience · 2023Article
- An integrated proteome and transcriptome of B cell maturation defines poised activation states of transitional and mature B cells.Nature communications · 2023Article
- Biology-inspired graph neural network encodes reactome and reveals biochemical reactions of disease.Patterns (New York, N.Y.) · 2023Article
104 more citing papers are in PubMed but not listed here.
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3 authors at 2 institutions in 1 country.
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Abstract
Large scale surveys in mammalian tissue culture cells suggest that the protein expressed at the median abundance is present at 8,000-16,000 molecules per cell and that differences in mRNA expression between genes explain only 10-40% of the differences in protein levels. We find, however, that these surveys have significantly underestimated protein abundances and the relative importance of transcription. Using individual measurements for 61 housekeeping proteins to rescale whole proteome data from Schwanhausser et al. (2011), we find that the median protein detected is expressed at 170,000 molecules per cell and that our corrected protein abundance estimates show a higher correlation with mRNA abundances than do the uncorrected protein data. In addition, we estimated the impact of further errors in mRNA and protein abundances using direct experimental measurements of these errors. The resulting analysis suggests that mRNA levels explain at least 56% of the differences in protein abundance for the 4,212 genes detected by Schwanhausser et al. (2011), though because one major source of error could not be estimated the true percent contribution should be higher. We also employed a second, independent strategy to determine the contribution of mRNA levels to protein expression. We show that the variance in translation rates directly measured by ribosome profiling is only 12% of that inferred by Schwanhausser et al. (2011), and that the measured and inferred translation rates correlate poorly (R(2) = 0.13). Based on this, our second strategy suggests that mRNA levels explain ∼81% of the variance in protein levels. We also determined the percent contributions of transcription, RNA degradation, translation and protein degradation to the variance in protein abundances using both of our strategies. While the magnitudes of the two estimates vary, they both suggest that transcription plays a more important role than the earlier studies implied and translation a much smaller role. Finally, the above estimates only apply to those genes whose mRNA and protein expression was detected. Based on a detailed analysis by Hebenstreit et al. (2012), we estimate that approximately 40% of genes in a given cell within a population express no mRNA. Since there can be no translation in the absence of mRNA, we argue that differences in translation rates can play no role in determining the expression levels for the ∼40% of genes that are non-expressed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.