School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia.
School of Biosciences, University of Melbourne, Parkville, VIC 3010, Australia.
Cell Syst. 2022 Jan 19;13(1):83-102.e6. doi: 10.1016/j.cels.2021.09.002. Epub 2021 Oct 8.
The Waddington epigenetic landscape has become an iconic representation of the cellular differentiation process. Recent single-cell transcriptomic data provide new opportunities for quantifying this originally conceptual tool, offering insight into the gene regulatory networks underlying cellular development. While many methods for constructing the landscape have been proposed, by far the most commonly employed approach is based on computing the landscape as the negative logarithm of the steady-state probability distribution. Here, we use simple models to highlight the complexities and limitations that arise when reconstructing the potential landscape in the presence of stochastic fluctuations. We consider how the landscape changes in accordance with different stochastic systems and show that it is the subtle interplay between the deterministic and stochastic components of the system that ultimately shapes the landscape. We further discuss how the presence of noise has important implications for the identifiability of the regulatory dynamics from experimental data. A record of this paper's transparent peer review process is included in the supplemental information.
Waddington 的表观遗传景观已成为细胞分化过程的标志性表示。最近的单细胞转录组学数据为定量分析这个最初的概念工具提供了新的机会,使我们能够深入了解细胞发育背后的基因调控网络。虽然已经提出了许多构建景观的方法,但到目前为止,应用最广泛的方法是基于将景观计算为稳态概率分布的负对数。在这里,我们使用简单的模型来突出在存在随机波动的情况下重建潜在景观时出现的复杂性和局限性。我们考虑了在不同的随机系统下景观如何变化,并表明系统的确定性和随机性成分之间的微妙相互作用最终决定了景观的形状。我们进一步讨论了噪声的存在如何对从实验数据中识别调节动力学产生重要影响。本论文的透明同行评审过程记录包含在补充信息中。