Stochastic gene expression is the random variation in the level of gene expression among genetically identical cells under the same conditions.Stochastic gene expression is the variability of mRNA and protein levels in genetically identical cells under the same conditions, caused by random molecular events. The main sources of noise: intrinsic (biochemical fluctuations during transcription and translation) and extrinsic (differences in the number of ribosomes, polymerases, growth factors between cells). This phenomenon underlies cellular heterogeneity and has evolutionary significance, allowing populations to survive in a changing environment.
Classical observations of phenotypic heterogeneity in isogenic populations (e.g., fluctuations of β-galactosidase in E. coli, Novick and Weiner, 1957) were long considered an artifact. In the 1990s, with the development of single-cell fluorescence microscopy (e.g., the work of Elowitz and Leibler, 2000), it became possible to quantitatively study noise. Theoretical foundations were laid by Delbrück (1940), and later by Berg (1978), McAdams, Arkin (1997). Modern high-throughput methods (single-cell sequencing) confirm the ubiquity of stochastic expression.
Transcription is initiated by the binding of RNA polymerase and transcription factors to the promoter, a stochastic process due to the low probability of molecular collisions in the cell volume. After initiation, mRNA synthesis occurs in bursts, and degradation of mRNA and proteins is exponential, creating Poisson noise. Negative and positive feedback loops in regulatory networks can suppress or amplify noise. Evolutionarily selected circuits—for example, bistable switches—use noise for random cell fate decisions.
Understanding stochastic expression helps explain the resistance of cancer cells to therapy and develop more reliable genetic engineering constructs for biotechnology.
In the same pancreatic tissue, different cells can produce insulin with a hundredfold difference, even with identical glucose stimulation.



















