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Enhanced stability and polyadenylation of select mRNAs support rapid thermogenesis in the brown fat of a hibernator.

Grabek KR, Diniz Behn C, Barsh GS, Hesselberth JR, Martin SL - Elife (2015)

Bottom Line: A cohort of transcripts increased during torpor, paradoxical because transcription effectively ceases at these low temperatures.We show that this increase occurs not by elevated transcription but rather by enhanced stabilization associated with maintenance and/or extension of long poly(A) tails.This subset was enriched in a C-rich motif and genes required for BAT activation, suggesting a model and mechanism to prioritize translation of key proteins for thermogenesis.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell and Developmental Biology, University of Colorado School of Medicine, Aurora, United States.

ABSTRACT
During hibernation, animals cycle between torpor and arousal. These cycles involve dramatic but poorly understood mechanisms of dynamic physiological regulation at the level of gene expression. Each cycle, Brown Adipose Tissue (BAT) drives periodic arousal from torpor by generating essential heat. We applied digital transcriptome analysis to precisely timed samples to identify molecular pathways that underlie the intense activity cycles of hibernator BAT. A cohort of transcripts increased during torpor, paradoxical because transcription effectively ceases at these low temperatures. We show that this increase occurs not by elevated transcription but rather by enhanced stabilization associated with maintenance and/or extension of long poly(A) tails. Mathematical modeling further supports a temperature-sensitive mechanism to protect a subset of transcripts from ongoing bulk degradation instead of increased transcription. This subset was enriched in a C-rich motif and genes required for BAT activation, suggesting a model and mechanism to prioritize translation of key proteins for thermogenesis.

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Results for Mechanism 2.When lower rates of degradation were implemented for the subset of protectedtranscripts, the relative abundances of this subset were increased over thetorpor–arousal cycle compared to baseline levels. This increase isillustrated by representative transcript time traces for raw and normalizedabundance of 50 protected transcripts (A, B;G, H) and 1,400 bulk transcripts(D, E; J, K) wherelog mean mu for the distribution of half-lives is 5.5 for the protectedtranscripts compared to 2.5 for the bulk transcripts. This increase was morepronounced when the lower degradation rate was compensated by a lowertranscription rate (A–F) compared tocompensations in steady state abundance(G–L). To quantify the dependence ondegradation rate, we varied the log mean mu for the distribution ofhalf-lives from 3.5 hr to 7.5 hr (baseline mu value for bulk population was2.5 hr). This corresponded to a change in average degradation rate from3.63e-04 mRNAs/min to 6.69e-06 mRNAs/min. For lower degradation ratescompensated by lower transcription rates, fold increase over baseline forprotected transcripts showed a saturating dose dependent relationship withmu (C). This mechanism had a minimal effect on bulk transcripts(F). For lower degradation rates compensated by high steadystate, fold increase over baseline for protected transcripts showed aninverted U-dependence on mu (I): although this mechanism couldproduce large increases in the subset of protected transcripts, this effectwas attenuated as small degradation rates caused large steady stateabundances since degradation, but not transcription, is proportional tosteady state values. The fold change in bulk transcripts decreaseddose-dependently for this mechanism (L). For mechanism 2, thedifferential Q10 effect enhanced the effect of the decreased degradationrate at low body temperature.DOI:http://dx.doi.org/10.7554/eLife.04517.015
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fig5s2: Results for Mechanism 2.When lower rates of degradation were implemented for the subset of protectedtranscripts, the relative abundances of this subset were increased over thetorpor–arousal cycle compared to baseline levels. This increase isillustrated by representative transcript time traces for raw and normalizedabundance of 50 protected transcripts (A, B;G, H) and 1,400 bulk transcripts(D, E; J, K) wherelog mean mu for the distribution of half-lives is 5.5 for the protectedtranscripts compared to 2.5 for the bulk transcripts. This increase was morepronounced when the lower degradation rate was compensated by a lowertranscription rate (A–F) compared tocompensations in steady state abundance(G–L). To quantify the dependence ondegradation rate, we varied the log mean mu for the distribution ofhalf-lives from 3.5 hr to 7.5 hr (baseline mu value for bulk population was2.5 hr). This corresponded to a change in average degradation rate from3.63e-04 mRNAs/min to 6.69e-06 mRNAs/min. For lower degradation ratescompensated by lower transcription rates, fold increase over baseline forprotected transcripts showed a saturating dose dependent relationship withmu (C). This mechanism had a minimal effect on bulk transcripts(F). For lower degradation rates compensated by high steadystate, fold increase over baseline for protected transcripts showed aninverted U-dependence on mu (I): although this mechanism couldproduce large increases in the subset of protected transcripts, this effectwas attenuated as small degradation rates caused large steady stateabundances since degradation, but not transcription, is proportional tosteady state values. The fold change in bulk transcripts decreaseddose-dependently for this mechanism (L). For mechanism 2, thedifferential Q10 effect enhanced the effect of the decreased degradationrate at low body temperature.DOI:http://dx.doi.org/10.7554/eLife.04517.015

Mentions: In the 50-transcript subset, we implemented either fixed or temperature-dependentalterations to degradation and synthesis rates to determine the resulting protectiveeffects on normalized transcript abundance following 10 days of torpor. We found that atemperature-dependent mechanism that protected a subset of transcripts relative to bulkRNA degradation (Figure 5A,B) was most consistentwith the increased abundances observed experimentally. For a body temperature thresholdof 10°C and degradation set to 3% of its rate in the warm animal, the relativeabundance of the protected transcripts increased over twofold (Figure 5C,D), best reflecting the experimental data. This effectwas dose-dependent with the level of protection and was relatively insensitive tothresholds above 10°C (Figure 5E). Althoughtemperature-independent decreases in degradation rates also led to increases in therelative abundance of protected transcripts, this mechanism required implausiblecompensatory changes to either steady state RNA abundance or transcription rates in thewarm animal (Figure 5—figure supplement2). Due to the differential Q10 effects on transcription and degradation,increasing transcription rate did not produce relative abundance increases (Figure 5—figure supplement 3). Thus, inagreement with RT-qPCR data, mathematical modeling supports enhanced stabilization of asubset of transcripts via a temperature-dependent protective mechanism; this, ratherthan increased transcription, leads to the observed increase in their relativeabundances at the low body temperature of torpor.10.7554/eLife.04517.013Figure 5.Mathematical modeling dynamics for 1,400 bulk and 50 protectedtranscripts simulated over the 12-day torpor–arousal cycle.


Enhanced stability and polyadenylation of select mRNAs support rapid thermogenesis in the brown fat of a hibernator.

Grabek KR, Diniz Behn C, Barsh GS, Hesselberth JR, Martin SL - Elife (2015)

Results for Mechanism 2.When lower rates of degradation were implemented for the subset of protectedtranscripts, the relative abundances of this subset were increased over thetorpor–arousal cycle compared to baseline levels. This increase isillustrated by representative transcript time traces for raw and normalizedabundance of 50 protected transcripts (A, B;G, H) and 1,400 bulk transcripts(D, E; J, K) wherelog mean mu for the distribution of half-lives is 5.5 for the protectedtranscripts compared to 2.5 for the bulk transcripts. This increase was morepronounced when the lower degradation rate was compensated by a lowertranscription rate (A–F) compared tocompensations in steady state abundance(G–L). To quantify the dependence ondegradation rate, we varied the log mean mu for the distribution ofhalf-lives from 3.5 hr to 7.5 hr (baseline mu value for bulk population was2.5 hr). This corresponded to a change in average degradation rate from3.63e-04 mRNAs/min to 6.69e-06 mRNAs/min. For lower degradation ratescompensated by lower transcription rates, fold increase over baseline forprotected transcripts showed a saturating dose dependent relationship withmu (C). This mechanism had a minimal effect on bulk transcripts(F). For lower degradation rates compensated by high steadystate, fold increase over baseline for protected transcripts showed aninverted U-dependence on mu (I): although this mechanism couldproduce large increases in the subset of protected transcripts, this effectwas attenuated as small degradation rates caused large steady stateabundances since degradation, but not transcription, is proportional tosteady state values. The fold change in bulk transcripts decreaseddose-dependently for this mechanism (L). For mechanism 2, thedifferential Q10 effect enhanced the effect of the decreased degradationrate at low body temperature.DOI:http://dx.doi.org/10.7554/eLife.04517.015
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4383249&req=5

fig5s2: Results for Mechanism 2.When lower rates of degradation were implemented for the subset of protectedtranscripts, the relative abundances of this subset were increased over thetorpor–arousal cycle compared to baseline levels. This increase isillustrated by representative transcript time traces for raw and normalizedabundance of 50 protected transcripts (A, B;G, H) and 1,400 bulk transcripts(D, E; J, K) wherelog mean mu for the distribution of half-lives is 5.5 for the protectedtranscripts compared to 2.5 for the bulk transcripts. This increase was morepronounced when the lower degradation rate was compensated by a lowertranscription rate (A–F) compared tocompensations in steady state abundance(G–L). To quantify the dependence ondegradation rate, we varied the log mean mu for the distribution ofhalf-lives from 3.5 hr to 7.5 hr (baseline mu value for bulk population was2.5 hr). This corresponded to a change in average degradation rate from3.63e-04 mRNAs/min to 6.69e-06 mRNAs/min. For lower degradation ratescompensated by lower transcription rates, fold increase over baseline forprotected transcripts showed a saturating dose dependent relationship withmu (C). This mechanism had a minimal effect on bulk transcripts(F). For lower degradation rates compensated by high steadystate, fold increase over baseline for protected transcripts showed aninverted U-dependence on mu (I): although this mechanism couldproduce large increases in the subset of protected transcripts, this effectwas attenuated as small degradation rates caused large steady stateabundances since degradation, but not transcription, is proportional tosteady state values. The fold change in bulk transcripts decreaseddose-dependently for this mechanism (L). For mechanism 2, thedifferential Q10 effect enhanced the effect of the decreased degradationrate at low body temperature.DOI:http://dx.doi.org/10.7554/eLife.04517.015
Mentions: In the 50-transcript subset, we implemented either fixed or temperature-dependentalterations to degradation and synthesis rates to determine the resulting protectiveeffects on normalized transcript abundance following 10 days of torpor. We found that atemperature-dependent mechanism that protected a subset of transcripts relative to bulkRNA degradation (Figure 5A,B) was most consistentwith the increased abundances observed experimentally. For a body temperature thresholdof 10°C and degradation set to 3% of its rate in the warm animal, the relativeabundance of the protected transcripts increased over twofold (Figure 5C,D), best reflecting the experimental data. This effectwas dose-dependent with the level of protection and was relatively insensitive tothresholds above 10°C (Figure 5E). Althoughtemperature-independent decreases in degradation rates also led to increases in therelative abundance of protected transcripts, this mechanism required implausiblecompensatory changes to either steady state RNA abundance or transcription rates in thewarm animal (Figure 5—figure supplement2). Due to the differential Q10 effects on transcription and degradation,increasing transcription rate did not produce relative abundance increases (Figure 5—figure supplement 3). Thus, inagreement with RT-qPCR data, mathematical modeling supports enhanced stabilization of asubset of transcripts via a temperature-dependent protective mechanism; this, ratherthan increased transcription, leads to the observed increase in their relativeabundances at the low body temperature of torpor.10.7554/eLife.04517.013Figure 5.Mathematical modeling dynamics for 1,400 bulk and 50 protectedtranscripts simulated over the 12-day torpor–arousal cycle.

Bottom Line: A cohort of transcripts increased during torpor, paradoxical because transcription effectively ceases at these low temperatures.We show that this increase occurs not by elevated transcription but rather by enhanced stabilization associated with maintenance and/or extension of long poly(A) tails.This subset was enriched in a C-rich motif and genes required for BAT activation, suggesting a model and mechanism to prioritize translation of key proteins for thermogenesis.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell and Developmental Biology, University of Colorado School of Medicine, Aurora, United States.

ABSTRACT
During hibernation, animals cycle between torpor and arousal. These cycles involve dramatic but poorly understood mechanisms of dynamic physiological regulation at the level of gene expression. Each cycle, Brown Adipose Tissue (BAT) drives periodic arousal from torpor by generating essential heat. We applied digital transcriptome analysis to precisely timed samples to identify molecular pathways that underlie the intense activity cycles of hibernator BAT. A cohort of transcripts increased during torpor, paradoxical because transcription effectively ceases at these low temperatures. We show that this increase occurs not by elevated transcription but rather by enhanced stabilization associated with maintenance and/or extension of long poly(A) tails. Mathematical modeling further supports a temperature-sensitive mechanism to protect a subset of transcripts from ongoing bulk degradation instead of increased transcription. This subset was enriched in a C-rich motif and genes required for BAT activation, suggesting a model and mechanism to prioritize translation of key proteins for thermogenesis.

Show MeSH
Related in: MedlinePlus