In this work we analyzed the effect of a moderate heat shock on different mRNA parameters at the whole genome level using the GRO approach. From the TR and RA experimental data, changes in mRNA stability during stress have been inferred. Thus, a global trend for mRNA stabilization is predicted upon such a stress as a general increase of RA is observed to reach levels which are then maintained at later times (). In contrast, Pol II-mediated TR experiences only a transient increase immediately upon stress. Therefore, mRNA stabilization effects seem to contribute to reach and maintain the increased global RA value during the time course of the experiments described herein. These data contrast with the general destabilization behavior predicted to take place as a part of the yeast response against moderate oxidative stress 
. On the other hand, the calculation of individual gene profiles for RA and TR allows a clustering analysis using both time courses (). This kind of analysis permits the classification of genes according to the whole transcriptional response because it captures the changes in both mRNA synthesis (TR) and mRNA degradation. The use of TR profiles has been demonstrated to be a better tool to detect regulons 
. In that study, the independent meta-analysis of our previously published data on carbon-source change 
, oxidative stress 
and osmotic stress 
responses demonstrated that nascent TR datasets predict transcriptional co-regulation better than RA profiles. In the current work, we used the RA-TR profiles and discovered that the behavior of Msn2/4-dependent genes follows a different response pattern (cluster 12A, and ) than those genes regulated by heat shock-specific factor Hsf1 (cluster 11A, and ). The average kD
profile for clusters 11 and 12 (Fig. S1
) also shows how initial destabilization distinguishes cluster 11 from cluster 12. This may be an unrelated but characteristic effect of Hsf1-dependent genes, or it may be a secondary effect of a transcription factor on the fate of synthesized mRNA as has been suggested for Msn2/4-dependent genes 
A general view of the 16 clusters shown in indicates that half of the S. cerevisiae
genes for which data have been obtained are grouped in two main clusters (11 and 12). The concentration of genes in fewer clusters than in the previous GRO study on the oxidative stress response 
, demonstrates that S. cerevisiae
cells display a more homogeneous response for heat stress than for oxidative stress. In the oxidative stress response, an opposed effect of mRNA stability versus RA trend has been shown 
. This apparently paradoxical behavior has been interpreted as a way to modulate the speed of the response, as previously predicted 
. In the same study, however, the response to DNA damage stress was seen to follow homodirectional changes for RA and mRNA stability 
. In our current results the accelerating effect of mRNA destabilization can be seen in clusters 3–5. In these clusters, genes related with translation reduce their mRNA level rapidly (Fig. S3
), perhaps to prevent unnecessary expenditures in this energetically-demanding process 
. A homodirectional response has also been found in osmotic stress 
. In this case the authors argue that the change in mRNA stability precedes the change in RA. Using our GRO protocol in this work, we can further explore these behaviors because we obtain separate data for TR (the transcriptional response itself) and RA (the consequence of the transcriptional response modulated by changes in mRNA stability). We see here that this stress induces mainly homodirectional changes because all the upregulated genes show mRNA stabilization profiles (clusters 11–16), and most of the downregulated genes (clusters 2–6 and 10) present mRNA destabilization. Thus, we confirm that most of the homodirectional changes (as suspected) between RA and mRNA stability are due to the homodirectional behaviors of TR and mRNA stability. However, in about one quarter of the genes, clusters 7–10, mRNA degradation counteracts the TR trend, provoking even an opposite profile between TR and RA (cluster 10). In relation to the anticipation of the mRNA stability response seen by Molin et al 
in osmotic stress, our current data show that the destabilization peak in most clusters of the upper branch takes place between 15 and 20 min (Fig. S1
), whereas the minimum in RA appears later (). In the genes of the lower part of the tree (), mRNA stabilization peaks at min 5–10, clearly before the RA (which peaks at the end of the time course, or even later). This agrees with the proposal of Molin et al 
. However, it should be considered that an advance of the TR peak over the RA one may naturally result from kinetic laws and does not necessarily mean an advanced cell response.
Among the genes which accumulate mRNA as a result of heat shock (clusters 11–16), different TR kinetics are observed. Thus, the small number of genes included in clusters 15 and 16 displays stable or decreased TR, indicating that RA upregulation results exclusively from mRNA stabilization effects. This situation would have remained unnoticed in standard DNA microarray analyses. Remarkable stabilization is also predicted for the genes of cluster 14, for which RA upregulation (about 4- or 5-fold) is much higher than that predicted from its TR profile (). Other previously undetected behaviors correspond to those genes with a stable RA profile whose transcription, however, has clearly altered, as in clusters 1–2 and 7–9. They represent apparent futile behaviors in which changes in mRNA stability are devoted to compensate changes in TR (as mentioned above). This behavior was also observed in our previous work on the oxidative stress response 
. To date, we can provide no explanation for it, but it is interesting to point that another kind of apparent futile pathway has been observed by Warringer et al 
, who found that some transcriptionally induced mRNAs are not translated at all during the osmotic stress response. These results suggest the existence of still unknown gene regulatory strategies which are not just the straightforward ones 
. In any case, and as previously suggested 
, the increases in both the transcription and degradation rates for mRNA can be a way to speed the response. On the other hand, the simultaneous decrease in both rates can be used to save energy dispenses. Therefore, we conclude that the heat shock response seems to be contributed both by mRNA transcription and stabilization effects. This is particularly relevant in the case of genes involved in protein refolding ().
It has been proposed that the existence of genes commonly regulated at the mRNA stability level (post-transcriptional regulons, 
] is due to the existence of RBPs that affect the stability of their mRNA targets 
. Those proteins have been experimentally studied by performing immunoprecipitation and microarray analysis of the RNA bound fraction 
. Their RNA sequence binding motifs have been determined either experimentally in vitro
or in vivo 
or by computer searches using newly developed algorithms 
. Here we have performed, for the first time, a search for overrepresented RBPs motifs in clusters of genes that are characterized by having a common mRNA stability profile during a time course. We have found that some of the gene clusters include statistically overrepresented Pub1, Npl3, Puf3 and Puf4 targets (). This is an additional proof of the existence of post-transcriptional regulons with an overlapping effect on gene regulation with classical transcription regulons. Our analysis has found some putative new binding motifs in other possible post-transcriptional regulons and thereby opens new paths for further research.
However, not all the genes are modulated at an important level by mRNA stability. Clusters 2 and 11 (with 35% of the analyzed genes) show almost identical experimental and theoretical RA profiles (). The number of genes with a high positive correlation between the theoretical RA (assuming no stability changes, see M & M) and the experimental RA (Fig. S2
) is large, supporting that TR changes are the main cause of RA changes upon heat stress.
Finally, we wish to point out that the discrepancies between the profiles of RNA polymerase activity (TR obtained by run-on labeling) in genes, and the RA during the stress response, mainly reflect the post-transcriptional effect of mRNA stability. Our current and previous results 
, as well as the results from many other laboratories 
, demonstrate that changes in mRNA stability are a strong component of the stress response. However, a recent publication 
indicate that the discrepancies between changes in the mRNA and Pol II presence (based on immunoprecipitation experiments) in genes are due to non productive (cryptic) transcription. Kim et al. 
argue that the genes for which an excess of mRNA is produced, regarding the presence of the Pol II molecule, were often associated with the existence of overlapping non coding mid-log-expressed transcripts. Although this is statistically shown in their analysis, this work does not demonstrate the existence of a cause-effect relationship. Their argument also involves additional speculation that non productive transcription is repressed during the stress response, which has not been demonstrated. In fact, we have found that the presence of cryptic transcription has little effect on a gene in the discrepancy between the experimental and theoretical RA profiles (JG-M and JEP-O in preparation). Although the effect can be more important for particular genes with a high proportion of antisense transcripts, it cannot account for most of the discrepancies detected between mRNA and Pol II changes. Therefore, it seems more straightforward and more experimentally supported to consider the discrepancies between the TR and RA profiles to the result of the delay required by kinetic laws, and also of the changes in mRNA stability.