基因转录调控中的输入输出关系研究

Input-Output Analysis for Gene Transcription Regulation:A Computational Approach

细胞对环境变化的感知和响应是生命活动的核心。基因转录是细胞将外部信号转化为基因表达输出的关键环节,是理解细胞行为的关键。为了解析转录动力学和建立动态的输入输出关系,研究者提出多种转录模型来探究基因对动态调控信号的响应机制。本文将介绍常见的转录模型,展示其计算框架,并详细阐述对应的mRNA数量和转录事件持续时间的分布,这对于深入理解输入输出关系和探索潜在的响应机制有重要意义。本文综述不同类型的启动子、同一启动子在不同染色质环境中以及不同网络基序下的响应策略,揭示其调控输入输出关系的规律。对于信道容量接近理论值的系统,信息论的最优解可以揭示转录因子浓度的动态范围、输入输出关系以及基因表达分布的对应关系。通过这些多角度的分析,本文揭示了调控动态输入输出关系的关键因素,促进人们更好地理解基因对转录因子信号的响应机制。定量研究输入输出关系可以识别关键的调控因子、预测基因表达模式的变化,并设计干预措施以调节细胞的功能和行为。

Living cells constantly sense and respond to environmental changes.Transcription,the process by which DNA is transcribed into RNA,serves as a critical bridge between external signals and gene expression,ultimately shaping cellular behavior.To unravel the transcription dynamics and the relationship between input signals and gene expression output,various transcription models have been developed.This review explores these common models,their computational frameworks,and the resulting distributions for mRNA number and transcriptional event duration,which offer valuable insights into input-output relationships and underlying response mechanisms.We further analyze how different promoter types,chromatin environments,and network motifs influence these relationships.Finally,we probe how information theory can be applied to systems with near-maximum channel capacity to reveal the dynamic range of transcription factor concentrations,input-output dynamics,and the link between these factors and gene expression distribution.Through these multifaceted analyses,we identify key regulators of dynamic input-output relationships and gain deeper insights into how genes respond to transcription factor signals.Quantitative studies of inputoutput relationships hold promises for identifying key regulatory factors,predicting changes in gene expression patterns,and designing interventions to manipulate cellular functions and behavior.