Gerald Nishant, Dutta Dibyendu, Brajesh R G, Saini Supreet
Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400 076, India.
BMC Syst Biol. 2019 Feb 28;13(1):25. doi: 10.1186/s12918-019-0704-0.
Movement of populations on fitness landscapes has been a problem of interest for a long time. While the subject has been extensively developed theoretically, reconciliation of the theoretical work with recent experimental data has not yet happened. In this work, we develop a computational framework and study evolution of the simplest transcription network between a single regulator, R and a single target protein, T.
Through our simulations, we track evolution of this transcription network and comment on its dynamics and statistics of this movement. Significantly, we report that there exists a critical parameter which controls the ability of a network to reach the global fitness peak on the landscape. This parameter is the fraction of all permissible values of a biochemical parameter that can be accessed from its current value via a single mutation.
Overall, through this work, we aim to present a general framework for analysis of movement of populations (and particularly regulatory networks) on landscapes.
长期以来,群体在适应度景观上的移动一直是一个备受关注的问题。虽然该主题在理论上已得到广泛发展,但理论工作与最近的实验数据尚未实现协调统一。在这项工作中,我们开发了一个计算框架,并研究单个调节因子R和单个靶蛋白T之间最简单转录网络的进化。
通过我们的模拟,我们追踪了这个转录网络的进化,并对其动态变化以及这种移动的统计学特征进行了评论。值得注意的是,我们报告存在一个关键参数,该参数控制网络在景观上达到全局适应度峰值的能力。这个参数是生化参数所有允许值的一部分,可通过单个突变从其当前值获取。
总体而言,通过这项工作,我们旨在提出一个用于分析群体(特别是调控网络)在景观上移动的通用框架。