title: Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA.
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.
authors: Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.
authors: Carlus
authors: C
authors: Deneke
authors: Reinhard
authors: R
authors: Lipowsky
authors: Angelo
authors: A
authors: Valleriani
mesh_terms: D006868:Hydrolysis; D008390:Markov Chains; D012333:RNA, Messenger / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D013269:Stochastic Processes
chemical_list: D012333:RNA, Messenger