  Regulation of intrinsic noise in gene expression is essential for many
cellular functions. Correspondingly, there is considerable interest in
understanding how different molecular mechanisms of gene expression impact
variations in protein levels across a population of cells. In this work, we
analyze a stochastic model of bursty gene expression which considers general
waiting-time distributions governing arrival and decay of proteins. By mapping
the system to models analyzed in queueing theory, we derive analytical
expressions for the noise in steady-state protein distributions. The derived
results extend previous work by including the effects of arbitrary probability
distributions representing the effects of molecular memory and bursting. The
analytical expressions obtained provide insight into the role of
transcriptional, post-transcriptional and post-translational mechanisms in
controlling the noise in gene expression.
