Abstract
Cells respond to changes in the environment by modifying the concentration of specific proteins. Paradoxically, the cellular response is usually examined by measuring variations in transcript abundance by high throughput RNA sequencing (RNA-Seq), instead of directly measuring protein concentrations. This happens because RNA-Seq-based methods provide better quantitative estimates, and more extensive gene coverage, than proteomics-based ones. However, variations in transcript abundance do not necessarily reflect changes in the corresponding protein abundance. How can we close this gap? Here we explore the use of ribosome profiling (Ribo-Seq) to perform differentially gene expression analysis in a relatively well-characterized system, oxidative stress in baker yeast. Ribo-Seq is an RNA sequencing method that specifically targets ribosome-protected RNA fragments, and thus is expected to provide a more accurate view of changes at the protein level than classical RNA-Seq. We show that gene quantification by Ribo-Seq is indeed more highly correlated with protein abundance, as measured from mass spectrometry data, than quantification by RNA-Seq. The analysis indicates that, whereas a subset of genes involved in oxidation-reduction processes is detected by both types of data, the majority of the genes that happen to be significant in the RNA-Seq-based analysis are not significant in the Ribo-Seq analysis, suggesting that they do not result in protein level changes. The results illustrate the advantages of Ribo-Seq to make inferences about changes in protein abundance in comparison with RNA-Seq.
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@article{Blevins2018,
title = {Using ribosome profiling to quantify differences in protein expression: a case study in Saccharomyces cerevisiae oxidative stress conditions},
author = {William R Blevins, Teresa Tavella, Simone G Moro, Bernat Blasco-Moreno, Adrià Closa-Mosquera, Juana Díez, Lucas B Carey, M. Mar Albà},
url = {https://doi.org/10.1101/501478 },
year = {2018},
date = {2018-12-19},
journal = {bioRxiv, Dec 19},
volume = { },
abstract = {Cells respond to changes in the environment by modifying the concentration of specific proteins. Paradoxically, the cellular response is usually examined by measuring variations in transcript abundance by high throughput RNA sequencing (RNA-Seq), instead of directly measuring protein concentrations. This happens because RNA-Seq-based methods provide better quantitative estimates, and more extensive gene coverage, than proteomics-based ones. However, variations in transcript abundance do not necessarily reflect changes in the corresponding protein abundance. How can we close this gap? Here we explore the use of ribosome profiling (Ribo-Seq) to perform differentially gene expression analysis in a relatively well-characterized system, oxidative stress in baker yeast. Ribo-Seq is an RNA sequencing method that specifically targets ribosome-protected RNA fragments, and thus is expected to provide a more accurate view of changes at the protein level than classical RNA-Seq. We show that gene quantification by Ribo-Seq is indeed more highly correlated with protein abundance, as measured from mass spectrometry data, than quantification by RNA-Seq. The analysis indicates that, whereas a subset of genes involved in oxidation-reduction processes is detected by both types of data, the majority of the genes that happen to be significant in the RNA-Seq-based analysis are not significant in the Ribo-Seq analysis, suggesting that they do not result in protein level changes. The results illustrate the advantages of Ribo-Seq to make inferences about changes in protein abundance in comparison with RNA-Seq.},
keywords = {Ribo-Seq}
}
