Quantifying heterogeneity of stochastic gene expression

JOURNAL OF THEORETICAL BIOLOGY

卷:465

Article

Iida, Keita¹  Obata, Nobuaki²  Kimura, Yoshitaka¹ 

[1] Tohoku Univ, Grad Sch Med, Sendai, Miyagi 9808575, Japan

[2] Tohoku Univ, Grad Sch Informat Sci, Sendai, Miyagi 9808579, Japan

关键词: Stochastic process;    Master equation;    Lac operon;    Metropolis algorithm;   

DOI  :  10.1016/j.jtbi.2019.01.003

来源: Elsevier

【 摘 要 】

The heterogeneity of stochastic gene expression, which refers to the temporal fluctuation in a gene product and its cell-to-cell variation, has attracted considerable interest from biologists, physicists, and mathematicians. The dynamics of protein production and degradation have been modeled as random processes with transition probabilities. However, there is a gap between theory and phenomena, particularly in terms of analytical formulation and parameter estimation. In this study, we propose a theoretical framework in which we present a basic model of a gene regulatory system, derive a steady-state solution, and provide a Bayesian approach for estimating the model parameters from single-cell experimental data. The proposed framework is demonstrated to be applicable for various scales of single-cell experiments at both the mRNA and protein levels and is useful for comparing kinetic parameters across species, genomes, and cell strains. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free