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从单细胞基因表达轨迹构建多阶段状态转换的动态模型

Yukai You^1,2, Cristian Caranica^1,2, Mingyang Lu^1,2

¹Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA.

bioRxiv : the preprint server for biology

|December 19, 2025

概括

一种新的计算方法NetDes揭示了基因调节网络,驱动多步骤的细胞状态转换. 它使用单细胞基因表达数据模拟复杂的生物过程,如分化.

科学领域:

计算生物学计算生物学
系统生物学系统生物学
基因组学就是基因组学.

背景情况:

多阶段细胞状态转换在生物学中至关重要 (例如,分化,疾病),但它们的调节机制尚不清楚.
从单细胞数据推断基因调节网络和建模动态过程具有重大挑战.

研究的目的:

介绍NetDes,一种用于推断转录因子监管网络的新型计算方法.
从单细胞基因表达轨迹开发基于ODE的动态模型,以了解细胞状态过渡.
为复杂生物过程中基因调节的机制建模提供一个可概括的框架.

主要方法:

NetDes集成了自上而下的和自下而上的系统生物学方法.
它推断核心转录因子调节网络,并使用单细胞RNA测序 (scRNA-seq) 时间序列数据构建动态模型.
基准测试涉及in-silico时间轨迹,基因电路模拟,以及对人类诱导多能干细胞 (iPSC) 分化数据的应用.

主要成果:

NetDes成功地预测了调控相互作用,并重现了基因表达动态.
该方法在单个动态模型中捕捉了连续的状态转换,优于现有的方法.
网络模拟和粗粒分析阐明了基因在驱动细胞状态转换中的调节作用.

结论:

在复杂的细胞状态转换过程中,NetDes提供了一个强大的,可通用的框架,用于对复杂细胞状态转换过程中的基因调节的机制建模.
计算方法提升了我们对细胞分化等生物过程的监管基础的理解.
这种方法可以使用scRNA-seq数据更准确地预测和建模动态生物系统.

关键词:

GRN 的推理推理.细胞状态过渡的转变.动态模型动态模型基因调节电路的基因调节电路 iPSC 的差异化差异化.

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