Sensitivity of the power-law exponent in gene expression distribution to mRNA decay rate

Large-scale acquisition technologies in mRNA abundance (gene expression) have provided new opportunities to better understand many complex biological processes. Lately, it has been reported that the observed gene expression data in several organisms significantly deviates from a Poisson distribution and follows a power-law or fat-tailed distribution. Here, we show that a simple stochastic model of gene expression with intrinsic and extrinsic noise derives the stationary power-law distribution using the Stratonovich calculus. Furthermore, we connect the experimental measure of the power-law exponent with the value of the mRNA decay. Finally, we compare the results with other models where stochastic equations were used within the Ito interpretation.

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