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Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA.

Deneke C, Lipowsky R, Valleriani A - PLoS ONE (2013)

Bottom Line: Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified.Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation.We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs.

View Article: PubMed Central - PubMed

Affiliation: Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.

ABSTRACT
Experimental studies on mRNA stability have established several, qualitatively distinct decay patterns for the amount of mRNA within the living cell. Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified. The central aim of this paper is to bring together both the experimental evidence about the decay patterns and the biochemical knowledge about the multi-step nature of mRNA degradation in a coherent mathematical theory. We first introduce a mathematical relationship between the mRNA decay pattern and the lifetime distribution of individual mRNA molecules. This relationship reveals that the mRNA decay patterns at steady state expression level must obey a general convexity condition, which applies to any degradation mechanism. Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation. We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs. Thereby, we show how to extract single-molecule properties of an mRNA, such as the age-dependent decay rate and the residual lifetime. Finally, we analyze the decay patterns of the whole translatome of yeast cells and show that yeast mRNAs can be grouped into three broad classes that exhibit three distinct decay patterns. This paper provides both a method to accurately analyze non-exponential mRNA decay patterns and a tool to validate different models of degradation using decay data.

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Related in: MedlinePlus

Experimental mRNA decay patterns.The relative mRNA number  defined in Eq. (1) can be measured at different time points after the interruption of transcription for S. cerevisiae as adapted from [23]. In this semi-log plot we show only those decay patterns that are monotonically decreasing and satisfy the convexity properties according to the general condition derived in Eq. (18). From the 51 decay patterns shown here, 21 curves show a cross-over from fast to slow decay (red) while 4 curves show a cross-over from slow to fast decay (blue). This indicates that the purely exponential decay is only one of several possible decay patterns.
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pone-0055442-g001: Experimental mRNA decay patterns.The relative mRNA number defined in Eq. (1) can be measured at different time points after the interruption of transcription for S. cerevisiae as adapted from [23]. In this semi-log plot we show only those decay patterns that are monotonically decreasing and satisfy the convexity properties according to the general condition derived in Eq. (18). From the 51 decay patterns shown here, 21 curves show a cross-over from fast to slow decay (red) while 4 curves show a cross-over from slow to fast decay (blue). This indicates that the purely exponential decay is only one of several possible decay patterns.

Mentions: Fig. 1 reproduces some of the measured decay curves for S. cerevisiae from Ref. [23]. We highlighted those patterns that strongly deviate from an exponential decay. The red patterns show a marked cross-over from a quick decay at short time scales to a slow decay at larger time scales. The blue patterns, instead, show the opposite behavior with a cross-over from a slower decay at short time scales to a quicker decay at large time scales. In the background, the gray lines show those decay patterns that are approximately exponential. In particular, the analysis of the data shows that short-lived mRNA species tend to belong to the set of the red decay patterns while long-lived mRNAs tend to belong to the set of the blue patterns in Fig. 1.


Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA.

Deneke C, Lipowsky R, Valleriani A - PLoS ONE (2013)

Experimental mRNA decay patterns.The relative mRNA number  defined in Eq. (1) can be measured at different time points after the interruption of transcription for S. cerevisiae as adapted from [23]. In this semi-log plot we show only those decay patterns that are monotonically decreasing and satisfy the convexity properties according to the general condition derived in Eq. (18). From the 51 decay patterns shown here, 21 curves show a cross-over from fast to slow decay (red) while 4 curves show a cross-over from slow to fast decay (blue). This indicates that the purely exponential decay is only one of several possible decay patterns.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3569439&req=5

pone-0055442-g001: Experimental mRNA decay patterns.The relative mRNA number defined in Eq. (1) can be measured at different time points after the interruption of transcription for S. cerevisiae as adapted from [23]. In this semi-log plot we show only those decay patterns that are monotonically decreasing and satisfy the convexity properties according to the general condition derived in Eq. (18). From the 51 decay patterns shown here, 21 curves show a cross-over from fast to slow decay (red) while 4 curves show a cross-over from slow to fast decay (blue). This indicates that the purely exponential decay is only one of several possible decay patterns.
Mentions: Fig. 1 reproduces some of the measured decay curves for S. cerevisiae from Ref. [23]. We highlighted those patterns that strongly deviate from an exponential decay. The red patterns show a marked cross-over from a quick decay at short time scales to a slow decay at larger time scales. The blue patterns, instead, show the opposite behavior with a cross-over from a slower decay at short time scales to a quicker decay at large time scales. In the background, the gray lines show those decay patterns that are approximately exponential. In particular, the analysis of the data shows that short-lived mRNA species tend to belong to the set of the red decay patterns while long-lived mRNAs tend to belong to the set of the blue patterns in Fig. 1.

Bottom Line: Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified.Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation.We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs.

View Article: PubMed Central - PubMed

Affiliation: Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.

ABSTRACT
Experimental studies on mRNA stability have established several, qualitatively distinct decay patterns for the amount of mRNA within the living cell. Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified. The central aim of this paper is to bring together both the experimental evidence about the decay patterns and the biochemical knowledge about the multi-step nature of mRNA degradation in a coherent mathematical theory. We first introduce a mathematical relationship between the mRNA decay pattern and the lifetime distribution of individual mRNA molecules. This relationship reveals that the mRNA decay patterns at steady state expression level must obey a general convexity condition, which applies to any degradation mechanism. Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation. We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs. Thereby, we show how to extract single-molecule properties of an mRNA, such as the age-dependent decay rate and the residual lifetime. Finally, we analyze the decay patterns of the whole translatome of yeast cells and show that yeast mRNAs can be grouped into three broad classes that exhibit three distinct decay patterns. This paper provides both a method to accurately analyze non-exponential mRNA decay patterns and a tool to validate different models of degradation using decay data.

Show MeSH
Related in: MedlinePlus