We present a maximum entropy framework to separate the intrinsic and the extrinsic contributions to noisy gene expression solely from the profile of expression. We express the experimentally accessible histogram of mRNA copy numbers by accounting for possible variations in global extrinsic factors. The distribution of extrinsic factors is estomated using the maximum entropy principle. Our results show that extrinsic factors quantitatively and qualitatively affect the histogram. Specifically, we{\it   suggest that the cell to cell variation in extrinsic factors accounts for the wider that Poisson{\it  distribution of mRNA copy numbers. We successfully test our framework on a numerical simulation of a simple gene expression scheme that accounts for the variation in extrinsic factors. We also make falsifiable predictions, some of which are tested on previous experiments in {\it E. coli while others need verification. Application of the current method to understanding noise in mRNA production in eukaryotes and protein production is also discussed.
We present a maximum entropy framework to separate intrinsic and extrinsic contributions to noisy gene expression solely from the profile of expression. We express the experimentally accessible probability distribution of the copy number of the gene product (mRNA or protein) by accounting for possible variations in extrinsic factors. The distribution of extrinsic factors is estimated using the maximum entropy principle. Our results show that extrinsic factors qualitatively and quantitatively affect the probability distribution of the gene product. We work out, in detail, the transcription of mRNA from a constitutively expressed promoter in{\it E. coli . We suggest that the variation in extrinsic factors may account for the observed{\it wider than Poisson distribution of mRNA copy numbers. We successfully test our framework on a numerical simulation of a simple gene expression scheme that accounts for the variation in extrinsic factors. We also make falsifiable predictions, some of which are tested on previous experiments in {\it E. coli while others need verification. Application of the current framework to more complex situations is also discussed.
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the intrinsic and the
intrinsic and
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histogram of mRNA copy numbers
probability distribution of the copy number of the gene product (mRNA or protein)
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global
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estomated
estimated
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quantitatively and qualitatively affect the histogram. Specifically, we
qualitatively and quantitatively affect the probability distribution of the gene product. We work out, in detail, the transcription of mRNA from a constitutively expressed promoter in
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E. coli
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. We
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cell to cell
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accounts for the wider that Poisson
may account for the observed
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wider than Poisson
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method to understanding noise in mRNA production in eukaryotes and protein production
framework to more complex situations