A Stochastic model for RNA splicing

We present a general framework for studying intrinsic fluctuations in gene expression that arise from RNA post-transcriptional splicing. In particular, we decompose the coefficient of variation for the full system into terms that capture the effects from the various stochastic processes that make up the model. Our analysis reveals that the pre-mRNA conversion to mature mRNA stochastically deletes the steady state correlation between the involved chemical species. Moreover, the noise decomposition suggests that under constitutive gene expression the pre-mRNA conversion is capable to restore the Poissonian limit of the downstream chemical species. Finally, interesting biological insights were found suggesting the role of splicing factors in altering the stochastic noise of the chemical species.