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• W2115102378 startingPage "1192" @default.
• W2115102378 abstract "The process of eukaryotic gene expression involves a diverse number of steps including transcription, RNA processing, transport, translation, and mRNA turnover. A critical step in understanding this process will be the development of mathematical models that quantitatively describe and predict the behavior of this complex system. We have simulated eukaryotic mRNA turnover in a linear multicomponent model based on the known mRNA decay pathways in yeast. Using rate constants based on experimental data for the yeast unstable MFA2 and stable PGK1 transcripts, the computational modeling reproduces experimental observations after minor adjustments. Subsequent analysis and a series of in silico experiments led to several conclusions. First, we demonstrate that mRNA half-life as commonly measured underestimates the average life span of an mRNA. Second, due to the properties of the pathways, the measurement of a half-life can predominantly measure different steps in the decay network. A corollary of this fact is that different mRNAs will be affected differentially by changes in specific rate constants. Third, the way to obtain the largest change of levels of mRNA for the smallest changes in rate is by changing the rate of deadenylation, where a large amount of regulation of mRNA decay occurs. Fourth, the 3'-to-5' degradation of mRNA shows mRNA-specific rates of degradation that are dependent on the 5' structure of the mRNA. These programs can be run over the Web, are adaptable to other eukaryotes, and provide outputs as graphs and virtual northern gels, which can be directly compared to experimental data. Therefore, this model constitutes a useful tool for the quantitative analysis of the process and control of mRNA degradation in eukaryotic cells." @default.
• W2115102378 created "2016-06-24" @default.
• W2115102378 creator A5014796446 @default.
• W2115102378 creator A5052964199 @default.
• W2115102378 date "2001-09-01" @default.
• W2115102378 modified "2023-09-27" @default.
• W2115102378 title "Computational modeling of eukaryotic mRNA turnover" @default.
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• W2115102378 doi "https://doi.org/10.1017/s1355838201010330" @default.
• W2115102378 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/1370166" @default.
• W2115102378 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/11565744" @default.
• W2115102378 hasPublicationYear "2001" @default.
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