ArticlePLoS computational biology2017
Post-transcriptional regulation across human tissues.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 139 papers, 3 of them syntheses that pooled it.
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Who cites it
139 citing papers in PubMed, 3 syntheses or guidelines pooled it, 229 citations in OpenAlex.
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- ADARs mediate distinct RNA editing activity and gene regulation in theRNA (New York, N.Y.) · 2026Article
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- Immune cell annotation in the single-cell studies: technologies, challenges, and integrative solutions.Immunologic research · 2026Review
- Single-Cell Proteomic Technologies: Tools in the Quest for Principles.Annual review of biophysics · 2026Review
- Integrating Spatial Proteogenomics in Cancer Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Simultaneous profiling of native-state proteomes and transcriptomes of neural cell types using proximity labeling.Nature communications · 2026Article
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- SR2P: an efficient stacking method to predict protein abundance from gene expression in spatial transcriptomics data.bioRxiv : the preprint server for biology · 2026Article
- Oxytocin receptor gene expression in the basal forebrain in autism: association with receptor binding levels and single nucleotide polymorphisms.Journal of neurodevelopmental disorders · 2026Article
- Maternal obesity alters adipogenic potential and mitochondrial maximal respiration in infant mesenchymal stem cells.Frontiers in endocrinology · 2026Article
- The effect of staphylococcal infection on cathelicidin and β-defensin mRNA levels in epithelial cells lining the mammary gland cistern.Frontiers in immunology · 2026Article
79 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Transcriptional and post-transcriptional regulation shape tissue-type-specific proteomes, but their relative contributions remain contested. Estimates of the factors determining protein levels in human tissues do not distinguish between (i) the factors determining the variability between the abundances of different proteins, i.e., mean-level-variability and, (ii) the factors determining the physiological variability of the same protein across different tissue types, i.e., across-tissues variability. We sought to estimate the contribution of transcript levels to these two orthogonal sources of variability, and found that scaled mRNA levels can account for most of the mean-level-variability but not necessarily for across-tissues variability. The reliable quantification of the latter estimate is limited by substantial measurement noise. However, protein-to-mRNA ratios exhibit substantial across-tissues variability that is functionally concerted and reproducible across different datasets, suggesting extensive post-transcriptional regulation. These results caution against estimating protein fold-changes from mRNA fold-changes between different cell-types, and highlight the contribution of post-transcriptional regulation to shaping tissue-type-specific proteomes.
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Registered trials
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.