Regulation of biological processes occurs at the transcriptional, translational and post-translational level. Optimal control is only achieved by coordinated regulation at all levels. Yet, important information on functional characteristics on many biological processes can already be obtained by analyzing transcriptional regulation. While measurements of differential gene expression indicate which genes are regulated on the transcriptional level in a specific condition, we show in this study that analysis of RNA decay and turnover can provide insights on transcriptional regulation on a more general level.
RNA decay has been studied in a wide range of species: E. coli
), yeast (31
) and human (8
). These studies were based on measurements of RNA decay after transcriptional arrest. In this article, we showed that these RNA half-lives, although quite accurate for short half-lives, are unreliable for medium to long half-lives. Contrary to that, measurements of RNA de novo
transcription provide reliable and precise results on the whole range of RNA half-lives. Probe set quality scores determined for every probe set based on the combined analysis of newly transcribed, unlabeled pre-existing RNA and total cellular RNA further improved data quality.
One potential bias, which might affect half-life measurements based on newly transcribed RNA, is insufficient capture of short transcripts due to their low number of uracil residues. This would result in underestimation of newly transcribed/total RNA ratios and overestimation of corresponding half-lives. Such a bias was noted in a recent study by Miller et al.
) which used 4-thiouracil (4tU) instead of 4-thiouridine (4sU) which we used in our study. By correlating uracil number of transcripts with newly transcribed/total RNA ratios we demonstrated that 4sU labeling for both human B-cells and murine fibroblasts resulted in sufficient 4sU incorporation to ensure efficient capture of transcript even with rather few (<100) uracil residues. Note that 4sU incorporation into nascent RNAs can be easily enhanced by increasing the applied 4sU concentration in the cell culture medium and, thus, transcript size bias can be experimentally controlled. In contrast, 4tU labeling requires the co-expression of uracil phosphoribosyltransferase (UPRT) of the protozoa Toxoplasma gondii (18
). We found 4tU/UPRT based labeling to be strongly dependent on UPRT expression levels as well as the cell type under study but not on the concentration of 4tU (unpublished data). Therefore, labeling efficiency can not be significantly increased by simply adding more 4tU but transcript length bias needs to be controlled for by bioinformatic means (30
Using our new approach, we determined precise RNA half-lives for more than 8000 genes in both human B-cells and mouse fibroblasts. By choosing two completely unrelated cell types, we focused on regulatory mechanisms not specific for only individual cell types. For about 5000 orthologous genes, we obtained RNA half-lives in both species and cell types. For the large majority of these orthologous genes, transcript half-lives are conserved across species and cell types. Only 18 out of the 4825 genes compared, i.e. only ~0.37%, actually showed a significant difference in transcript half-life between the two species. Furthermore, variation between species was correlated to the variation observed in the individual experiments for each species. This suggests that to a large degree the observed variations between species were due to variations within the individual experiments and do not constitute important inter-species differences. This does not imply that RNA decay is a static process and that no significant differences in transcript half-life exist in between these two cell lines or species. Our results only show that for conserved genes expressed in both cell lines, transcript half-life is also conserved.
Fast transcript decay allows rapid alterations of steady-state RNA concentrations due to transcriptional changes. At the same time, these changes can also be rapidly reversed. Thus, a short transcript half-life is important for efficient regulation at transcriptional level. Assuming that protein levels and transcript levels are correlated, protein levels of these genes can be efficiently regulated by alteration in transcription rates alone. In contrast, up- or down-regulation of stable transcripts takes a very long time to result in altered total RNA levels which, once established, also persist much longer. Consistent with previous reports, we confirmed a shift towards short half-lives for genes involved in the regulation of transcription and observed this also for regulators of signal transduction. However, a similar shift for genes involved in the regulation of cell cycle or apoptosis as proposed earlier (8
) or regulating genes in general (apart from transcriptional and signal transduction regulators) could not be confirmed. Thus, a short transcript half-life is not characteristic for regulators as such but only for regulators of transcription and signal transduction. The most stable transcripts were found for genes encoding for energy metabolism and protein translation and degradation. Interestingly, we observed that RNA half-lives of genes involved in translation cluster in the medium- to long-lived range and decrease in frequency on either side. This indicates that a greater degree of transcriptional control may be required for constituents of the translational machinery than for transcripts coding for proteins involved in protein degradation and energy metabolism. As measurements of RNA decay rates based on transcriptional arrest are inherently imprecise for medium- to long-lived transcripts, it is not surprising that this has been missed by previous studies.
So far, the biological processes and sequence features determining RNA decay are only poorly understood. Previous studies have suggested that certain RNA motifs in untranslated regions (8
) or miRNA binding and the presence of introns (5
) may play a role. Our approach now allows the analysis of RNA sequence features and motifs which determine fast and slow but also intermediate fast RNA decay. Therefore, the method and data we provide in this study will be valuable for more systematic studies on the mechanisms governing RNA decay.
We identified many biological processes in which closely related members of the same protein family with overlapping function differ significantly in RNA half-life. Here, differences in transcript half-life likely correspond to differences in regulation and, accordingly, functional roles of the corresponding genes. This is best exemplified by hexokinase I and II as well as the pro-apoptotic proteins BAX and BAK. These examples show that transcript half-lives are fine-tuned to support the regulation of cooperative but non-redundant roles of closely related family members. Based on these results, we predict similar regulatory patterns and provide a database for a large number of functionally less characterized genes and processes.
Most proteins function by interacting with other proteins in protein complexes. In this study, we confirmed previous observations in yeast that transcript half-lives for subunits of protein complexes are very similar (31
). Furthermore, decay of transcripts for these subunits was found to be generally slow. This implies that most protein complexes are pre-dominantly regulated at the post-translational level. Nevertheless, for more than 150 complexes with overall long transcript half-lives in both human and mouse we identified individual key subunits with a short transcript half-life which deviate significantly from the remaining subunits in all complexes they are part of. For almost a third of these proteins, we found this pattern to be conserved across species. The probability of finding the same complexes and subunits in both species by chance is negligibly small. Therefore, we propose a generalized mechanism employed by cells to facilitate regulation of protein complexes in an efficient and targeted way. For complexes depending on the availability of specific essential components, regulation of complex activity is accomplished by regulating the abundance of only one or few of these key subunits. Thereby, complex activity can be regulated both faster—as most subunits are available and may have already assembled—and more energy efficient than by regulating all complex members. With the two examples of the PBAF complex and the E3 ubiquitin ligase complex, we demonstrated how transcriptional regulation of individual key subunits which are e.g. critical for either complex formation and stability (for the PBAF complex) or specificity (for the E3 ubiquitin ligase complex) can support efficient regulation of complex activity at the transcriptional level. A similar observation was made by de Lichtenberg et al.
) for protein complexes of the yeast cell cycle. As most of these complexes contained both periodically and constitutively expressed subunits, they suggested a ‘just-in-time assembly’ (instead of ‘just-in-time synthesis’) in which the timing of the complex assembly is regulated by transcriptional regulation of only some subunits. Our results indicate that this may not be specific for the cell cycle but a general mechanism by which the function of large protein complex is regulated.
Based on this concept, we predict altogether about 100 key regulatory subunits in more than 150 complexes for both human and mouse. This list can be further extended by 85 and 67 proteins in human and mouse, respectively, which show a significantly shorter RNA half-life in at least one complex but not all complexes they are contained in. In these cases, their short transcript half-life may be explained by the fact that they are part of a complex for which all subunits have to be regulated strongly on the transcriptional level and, accordingly, have short transcript half-lives. Although these subunits were not included in the predictions for key regulatory subunits, they probably also have an important regulative function within the other complexes they are part of. Further studies on the regulatory subunits we predict in this study are required for a better understanding of the regulation of the involved protein complexes and the biological processes they govern.