BackgroundAlternative transcription is common in eukaryotic cells and plays important role in regulation of cellular processes. Alternative polyadenylation results from ambiguous PolyA signals in 3′ untranslated region (UTR) of a gene. Such alternative transcripts share the same coding part, but differ by a stretch of UTR that may contain important functional sites.MethodsThe methodoogy of this study is based on mathematical modeling, analytical solution, and subsequent validation by datamining in multiple independent experimental data from previously published studies.ResultsIn this study we propose a mathematical model that describes the population dynamics of alternatively polyadenylated transcripts in conjunction with rhythmic expression such as transcription oscillation driven by circadian or metabolic oscillators. Analysis of the model shows that alternative transcripts with different turnover rates acquire a phase shift if the transcript decay rate is different. Difference in decay rate is one of the consequences of alternative polyadenylation. Phase shift can reach values equal to half the period of oscillation, which makes alternative transcripts oscillate in abundance in counter-phase to each other. Since counter-phased transcripts share the coding part, the rate of translation becomes constant. We have analyzed a few data sets collected in circadian timeline for the occurrence of transcript behavior that fits the mathematical model.ConclusionAlternative transcripts with different turnover rate create the effect of rectifier. This “molecular diode” moderates or completely eliminates oscillation of individual transcripts and stabilizes overall protein production rate. In our observation this phenomenon is very common in different tissues in plants, mice, and humans. The occurrence of counter-phased alternative transcripts is also tissue-specific and affects functions of multiple biological pathways. Accounting for this mechanism is important for understanding the natural and engineering the synthetic cellular circuits.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3958-1) contains supplementary material, which is available to authorized users.
MicroRNAs are important modulators of gene expression. There is anecdotal evidence that the abundance of some microRNAs varies in circadian or approximately daily rhythm. In this study, using publicly available data we attempt a systematic analysis of co-expression between microRNAs and their prospective mRNA targets. An advanced analysis of periodicity with the application of digital filters in phase continuum revealed a baseline rhythmic oscillation on over 80% of both mRNA and microRNA populations. This computational observation adds evidence to the theory that microRNAs play an active role in modulation of rhythmic expression as a general rule rather than special exemption. We also explore the immediate implications of inferred oscillatory behavior for modeling of mRNA-miRNA dynamics.
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