On the Dependency of Cellular Protein Levels on mRNA Abundance Yansheng Liu, Andreas Beyer, Ruedi Aebersold  Cell  Volume 165, Issue 3, Pages 535-550 (April 2016) DOI: 10.1016/j.cell.2016.03.014 Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 1 Different Types of Correlations between Protein and mRNA Levels Need to Be Distinguished (A) Variation of one protein can be correlated with the variation of its coding mRNA across different conditions, tissues, individuals, or time points. This type of analysis addresses the question to what extent variation of protein levels is determined by variation of the corresponding mRNA for a specific gene. (B) Concentrations of several proteins measured under the same condition can be correlated with their coding mRNAs. Here, each dot represents a single protein-mRNA pair. This type of analysis addresses the question to what extent concentration differences between transcripts from different genes show up at the level of proteins. Cell 2016 165, 535-550DOI: (10.1016/j.cell.2016.03.014) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 2 Sequential Mechanisms Controlling Gene Expression and Thus the Relationship between mRNA and Proteins Mechanisms, types of molecules, methods for their respective quantitative measurement, and the properties measured by the respective methods are indicated. Abbreviations: NET-seq, native elongating transcript sequencing; RATE-seq, RNA approach to equilibrium sequencing; Ribo-seq, ribosome profiling; pSILAC, pulsed stable isotope labeling by amino acids in cell culture; PUNCH-P, puromycin-associated nascent chain proteomics; AHA, azidohomoalanine labeling; RNAPII, RNA polymerase II; and for other abbreviations, please refer to Table 1. Cell 2016 165, 535-550DOI: (10.1016/j.cell.2016.03.014) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 3 Importance of Dynamics for the Relationship between mRNA and Proteins (A) mRNA levels primarily determine protein amounts at steady state. During transition from the first to the second steady state, there is a delayed synthesis between mRNA and protein, which results in poor mRNA-protein correlations. The correlation returns to a higher level again at the second steady state. (B and C) For short-time adaption, the mechanism of delayed transcription and translation (B) can be too slow, where the “translation on demand” by regulation of translation rate (C) ensures that proteins are rapidly available in response to signals without having to constitutively express them. (D) At the single-cell scale, the stochasticity of transcription (transcriptional bursting) becomes visible. Delayed export of transcripts into the cytoplasm and the usually longer half-lives of proteins stabilize protein levels over time. Due to the delay between transcription and translation, it cannot be assumed that protein and RNA levels are synchronized at the single-cell level. For certain processes such as cell cycle, the delay between mRNA and protein production in the single cell can be averaged out when the cell population is measured. (E) The energy and concentration constraints determine the ribosome usage for differential transcripts at a certain time point. (F) The absolute protein number variation is mainly determined by translational mechanisms. This is extremely efficient for high abundant proteins as the same fold change of these proteins involves a much larger number of molecules compared to low abundant proteins. (G) The correlation between mRNA and protein can be compartmental in a cell due to the localization of both molecules. Cell 2016 165, 535-550DOI: (10.1016/j.cell.2016.03.014) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 4 Protein Level Buffering of Expression Variability at Multiple Scales (A) Buffering of protein levels against mRNA variation can occur at multiple scales, including intra- and inter-individual genomic variation, as well as inter-species variation. (B) Buffering of protein levels against mRNA through molecular biological layers. The buffering of protein levels allows the cells to cope with external environmental noise and internal noise of genetic variation such as copy number variation (CNV) and single-nucleotide polymorphism (SNP). Quantitative trait loci (QTL) can be detected—e.g., at transcription level by RNA-seq (expression QTL, eQTL), translational level by ribosome profiling (rQTL), and protein level by proteomic measurement (protein QTL, pQTL), which reveals the extent of variation at each layer and confirms the existence of buffering of unsolicited mRNA variation at protein levels. Cell 2016 165, 535-550DOI: (10.1016/j.cell.2016.03.014) Copyright © 2016 Elsevier Inc. Terms and Conditions