用单细胞熵描述诱导多能干细胞重编程和分化的动力学
Using single-cell entropy to describe the dynamics of reprogramming and differentiation of induced pluripotent stem cells
摘要：
诱导多能干细胞（iPSCs）为研究干细胞的重编程和分化过程提供了一个很好的模型。单细胞RNA测序（scRNA-seq）使我们能够在单细胞水平上研究重编程过程。在这里，我们引入单细胞熵（scEntropy）作为宏观变量，以量化iPSC重编程和分化过程中scRNA-seq数据的细胞转录组。scEntropy测量细胞命运变化过程中单细胞水平上基因组转录的相对序参量，其在分化期间显示增加，并且在重编程时显示减少。此外，基于scEntropy动力学，我们构建了iPSC分化过程中细胞状态转换的唯象随机微分方程模型和相应的Fokker-Plank方程，为推断细胞命运变化和干细胞分化提供了理论依据.本研究首次将scEntropy这一新概念引入iPSC的生物学过程，并提出scEntropy可以为描述干细胞分化和重编程过程中的细胞命运转变提供合适的量化指标。
英文摘要：
Induced pluripotent stem cells (iPSCs) provide a great model to study the process of reprogramming and differentiation of stem cells. Single-cell RNA sequencing (scRNA-seq) enables us to investigate the reprogramming process at single-cell level. Here, we introduce single-cell entropy (scEntropy) as a macroscopic variable to quantify the cellular transcriptome from scRNA-seq data during reprogramming and differentiation of iPSCs. scEntropy measures the relative order parameter of genomic transcriptions at single cell level during the cell fate change process, which shows increasing during differentiation, and decreasing upon reprogramming. Moreover, based on the scEntropy dynamics, we construct a phenomenological stochastic differential equation model and the corresponding Fokker-Plank equation for cell state transitions during iPSC differentiation, which provide insights to infer cell fates changes and stem cell differentiation. This study is the first to introduce the novel concept of scEntropy to the biological process of iPSC, and suggests that the scEntropy can provide a suitable quantify to describe cell fate transition in differentiation and reprogramming of stem cells.
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