Gene‐specific correlation of
            <scp>RNA</scp>
            and protein levels in human cells and tissues

Edfors, Fredrik; Danielsson, Frida; Hallström, Björn M.; Käll, Lukas; Lundberg, Emma; Pontén, Fredrik; Forsström, Björn; Uhlén, Mathias

doi:10.15252/msb.20167144

Cited by 399 publications

(370 citation statements)

References 37 publications

(45 reference statements)

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“…The correlation between the absolute mRNA and protein levels of different genes and across different tissue-types has been used to estimate the level at which the protein levels are regulated [20, 22]. …”

Section: Resultsmentioning

confidence: 99%

Post-transcriptional regulation across human tissues

2017

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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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Section: Resultsmentioning

confidence: 99%

Post-transcriptional regulation across human tissues

2017

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“…(Edfors et al., 2016). These authors reported a gene‐specific linear correlation between mRNA and protein levels across a wide range of tissues, including muscle, while we showed that changes in transcript levels are minor compared to those in protein levels.…”

Section: Discussionmentioning

confidence: 99%

Running‐wheel activity delays mitochondrial respiratory flux decline in aging mouse muscle via a post‐transcriptional mechanism

et al. 2017

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SummaryLoss of mitochondrial respiratory flux is a hallmark of skeletal muscle aging, contributing to a progressive decline of muscle strength. Endurance exercise alleviates the decrease in respiratory flux, both in humans and in rodents. Here, we dissect the underlying mechanism of mitochondrial flux decline by integrated analysis of the molecular network.Mice were given a lifelong ad libitum low‐fat or high‐fat sucrose diet and were further divided into sedentary and running‐wheel groups. At 6, 12, 18 and 24 months, muscle weight, triglyceride content and mitochondrial respiratory flux were analysed. Subsequently, transcriptome was measured by RNA‐Seq and proteome by targeted LC‐MS/MS analysis with 13C‐labelled standards. In the sedentary groups, mitochondrial respiratory flux declined with age. Voluntary running protected the mitochondrial respiratory flux until 18 months of age. Beyond this time point, all groups converged. Regulation Analysis of flux, proteome and transcriptome showed that the decline of flux was equally regulated at the proteomic and at the metabolic level, while regulation at the transcriptional level was marginal. Proteomic regulation was most prominent at the beginning and at the end of the pathway, namely at the pyruvate dehydrogenase complex and at the synthesis and transport of ATP. Further proteomic regulation was scattered across the entire pathway, revealing an effective multisite regulation. Finally, reactions regulated at the protein level were highly overlapping between the four experimental groups, suggesting a common, post‐transcriptional mechanism of muscle aging.

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“…() and Edfors et al . () demonstrated that the predictability of protein copy numbers from RNA levels could be enhanced if a gene‐specific RNA‐to ‐ protein conversion factor, which was shown to be independent of the eukaryotic tissue cell type, was introduced. Furthermore, it has been demonstrated that a differential expression of a gene under different conditions is accompanied by a higher likelihood of a corresponding change in protein levels (Koussounadis et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Environment‐driven changes of mRNA and protein levels in Pseudomonas aeruginosa

Erdmann

Preuße

Khaledi

et al. 2018

Environmental Microbiology

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Summary Systems biology approaches address the challenge of translating sequence information into function. In this study, we described the Pseudomonas aeruginosa PA14 proteomic landscape and quantified environment‐driven changes in protein levels by the use of LC–MS techniques. Previously recorded mRNA data allowed a comparison of RNA to protein ratios for each individual gene and, thus, to explore the relationship between an mRNA being differentially expressed between environmental conditions and the mRNA‐protein correlation for that gene. We developed a Random Forest‐based predictor for protein levels and found that the mRNA to protein correlation was higher for genes/proteins that undergo dynamic changes. One example of a discrepancy between protein and predicted protein levels was observed for a phage‐related gene cluster, which was translated into low protein levels under standard growth conditions. However, under SOS‐inducing conditions more protein was produced and the prediction of protein levels based on mRNA abundancy became more accurate. In conclusion, our systems biology approach sheds light on complex mRNA to protein level relationships and uncovered condition‐dependent post‐transcriptional regulatory events.

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Gene‐specific correlation of RNA and protein levels in human cells and tissues

Cited by 399 publications

References 37 publications

Post-transcriptional regulation across human tissues

Post-transcriptional regulation across human tissues

Running‐wheel activity delays mitochondrial respiratory flux decline in aging mouse muscle via a post‐transcriptional mechanism

Environment‐driven changes of mRNA and protein levels in Pseudomonas aeruginosa

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