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Abstract
Gene expression is inherently noisy due to fluctuations occurring at the molecular level. From a top-down perspective, noise has been traditionally decomposed into an intrinsic component that scales inversely with the mean expression level and an extrinsic component that is constant in absence of regulatory changes. Here, we adopt a bottom-up approach to reveal that extrinsic noise, by itself, can follow the aforementioned decomposition, which entails that one component of it can be confounded with intrinsic noise. Analytical expressions of the noise-mean relationship were derived for different scenarios, which were in part supported by numerical simulations.
Highlights
Genes are the fundamental, information-encoding pieces into which the DNA of every living organism is divided, and their expression is inherently stochastic [1]
We follow a bottom-up approach to derive a general model based on stochastic differential equations (SDEs) in which the extrinsic noise arises as a consequence of fluctuations in the different kinetic parameters that shape gene expression
These reactions can be modeled if we know the different kinetic parameter values
Summary
Information-encoding pieces into which the DNA of every living organism is divided, and their expression +B [9,10,11], where the first term accounts for the intrinsic noise (i.e., the variability generated in the gene of study) and the second for the extrinsic noise (i.e., the variability generated at a global scale, shared by different genes) [2] In this simple but effective model, while the extrinsic noise is constant (B, this holds for nonregulated genes or invariant regulatory activity), the intrinsic noise scales inversely with the mean expression level We follow a bottom-up approach to derive a general model based on stochastic differential equations (SDEs) in which the extrinsic noise arises as a consequence of fluctuations in the different kinetic parameters that shape gene expression.
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