Exact distributions for stochastic models of gene expression with arbitrary regulation

作     者：Zihao Wang Zhenquan Zhang Tianshou Zhou Zihao Wang;Zhenquan Zhang;Tianshou Zhou

作者机构：School of Mathematics Sun Yat-sen University 

出 版 物：《Science China Mathematics》 (中国科学：数学（英文版）)

年 卷 期：2020年第63卷第3期

页      面：485-500页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0711[理学-系统科学] 07[理学] 08[工学] 

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 11931019  11775314 and 91530320) 

主　　题：gene expression ON-OFF model feedback regulation chemical master equation stationary distribution 

摘      要：Stochasticity in gene expression can result in fluctuations in gene product levels. Recent experiments indicated that feedback regulation plays an important role in controlling the noise in gene expression.A quantitative understanding of the feedback effect on gene expression requires analysis of the corresponding stochastic model. However, for stochastic models of gene expression with general regulation functions, exact analytical results for gene product distributions have not been given so far. Here, we propose a technique to solve a generalized ON-OFF model of stochastic gene expression with arbitrary(positive or negative, linear or nonlinear) feedbacks including posttranscriptional or posttranslational regulation. The obtained results, which generalize results obtained previously, provide new insights into the role of feedback in regulating gene expression. The proposed analytical framework can easily be extended to analysis of more complex models of stochastic gene expression.