Quantifying origins of cell-to-cell variations in gene expression.

A general dynamic description of protein synthesis was employed to quantify different sources of gene expression noise in cellular systems. To test our approach, we use time-resolved expression data of individual human cells and, from this information, predict the stationary cell-to-cell variation in protein levels in a clonal population. For three of the four human genes investigated, the cellular variations in expression level are not due to fluctuations in promoter activity or transcript copy number, but are almost exclusively a consequence of long-term variations of gene regulatory factors or the global cellular state. Moreover, we show that a dynamic description is much more reliable to discriminate extrinsic and intrinsic sources of noise than it is on grounds of cell-cycle averaged descriptions. The excellent agreement between the theoretical predictions and the experimentally measured noise strengths shows that a quantitative description of gene expression noise is indeed possible on the basis of idealized stochastic processes.

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