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Gene‐specific correlation of RNA and protein levels in human cells and tissues
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Gene‐specific correlation of RNA and protein levels in human cells and tissues
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Journal Article
Gene‐specific correlation of RNA and protein levels in human cells and tissues
2016
Overview
An important issue for molecular biology is to establish whether transcript levels of a given gene can be used as proxies for the corresponding protein levels. Here, we have developed a targeted proteomics approach for a set of human non‐secreted proteins based on parallel reaction monitoring to measure, at steady‐state conditions, absolute protein copy numbers across human tissues and cell lines and compared these levels with the corresponding mRNA levels using transcriptomics. The study shows that the transcript and protein levels do not correlate well unless a gene‐specific RNA‐to‐protein (RTP) conversion factor independent of the tissue type is introduced, thus significantly enhancing the predictability of protein copy numbers from RNA levels. The results show that the RTP ratio varies significantly with a few hundred copies per mRNA molecule for some genes to several hundred thousands of protein copies per mRNA molecule for others. In conclusion, our data suggest that transcriptome analysis can be used as a tool to predict the protein copy numbers per cell, thus forming an attractive link between the field of genomics and proteomics.
Synopsis
A comparison of absolute protein copy numbers with mRNA levels across human tissues and cell lines shows that protein levels correlate well with transcript levels, if a gene‐specific and cell/tissue‐independent RNA‐to‐protein (RTP) conversion factor is introduced.
A targeted proteomics approach based on spike‐in of stable isotope‐labeled protein fragments is developed to measure absolute protein copy numbers across human tissues and cell lines.
Transcript and protein levels within a sample do not correlate well, unless a gene‐specific RNA‐to‐protein (RTP) factor is introduced.
The RTP‐ratio varies significantly between genes, ranging from thousands to millions of protein copies per mRNA molecule, but does not vary across tissues.
Transcriptome analysis can be used as a tool to predict protein copy numbers per cell, thus forming an attractive link between genomics and proteomics.
Graphical Abstract
A comparison of absolute protein copy numbers with mRNA levels across human tissues and cell lines shows that protein levels correlate well with transcript levels, if a gene‐specific and cell/tissue‐independent RNA‐to‐protein (RTP) conversion factor is introduced.
