Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Zurich, 8093, Switzerland.
Laboratoire de Biologie et Modélisation de la Cellule, École Normale Supérieure de Lyon, CNRS, Université Claude Bernard Lyon 1, F69364, France.
F1000Res. 2023 Jul 20;12:426. doi: 10.12688/f1000research.131861.2. eCollection 2023.
Single-cell studies have demonstrated the presence of significant cell-to-cell heterogeneity in gene expression. Whether such heterogeneity is only a bystander or has a functional role in the cell differentiation process is still hotly debated. In this study, we quantified and followed single-cell transcriptional uncertainty - a measure of gene transcriptional stochasticity in single cells - in 10 cell differentiation systems of varying cell lineage progressions, from single to multi-branching trajectories, using the stochastic two-state gene transcription model. By visualizing the transcriptional uncertainty as a landscape over a two-dimensional representation of the single-cell gene expression data, we observed universal features in the cell differentiation trajectories that include: (i) a peak in single-cell uncertainty during transition states, and in systems with bifurcating differentiation trajectories, each branching point represents a state of high transcriptional uncertainty; (ii) a positive correlation of transcriptional uncertainty with transcriptional burst size and frequency; (iii) an increase in RNA velocity preceding the increase in the cell transcriptional uncertainty. Our findings suggest a possible universal mechanism during the cell differentiation process, in which stem cells engage stochastic exploratory dynamics of gene expression at the start of the cell differentiation by increasing gene transcriptional bursts, and disengage such dynamics once cells have decided on a particular terminal cell identity. Notably, the peak of single-cell transcriptional uncertainty signifies the decision-making point in the cell differentiation process.
单细胞研究表明,基因表达存在显著的细胞间异质性。这种异质性是偶然现象还是在细胞分化过程中具有功能作用,仍存在激烈争论。在这项研究中,我们使用随机双态基因转录模型,在 10 种不同细胞谱系进展的细胞分化系统中,对单细胞转录不确定性进行了量化和跟踪——这是衡量单细胞中基因转录随机性的一个指标。通过将单细胞基因表达数据的二维表示可视化作为转录不确定性的景观,我们观察到细胞分化轨迹中的普遍特征,包括:(i)在过渡状态期间,单细胞不确定性达到峰值,在具有分叉分化轨迹的系统中,每个分支点代表高转录不确定性的状态;(ii)转录不确定性与转录爆发大小和频率呈正相关;(iii)在细胞转录不确定性增加之前,RNA 速度增加。我们的发现表明,在细胞分化过程中可能存在一种普遍机制,即干细胞在细胞分化开始时通过增加基因转录爆发来参与基因表达的随机探索性动力学,一旦细胞决定了特定的终末细胞身份,就会停止这种动力学。值得注意的是,单细胞转录不确定性峰值标志着细胞分化过程中的决策点。