A multi-stage stochastic model of regulatory control in pluripotentstem cells

基因调控网络的模型对于从机械论的角度理解细胞过程至关重要。目前胚胎干细胞自我更新和分化的模型主要集中在关键的多潜能因子之间的转录调控。然而，最近的报告准确地指出了额外的调控层，最重要的是通过microRNAs进行染色质重塑和转录后调控。这些不同层面的监管控制之间的联系及其对多能性的影响还远未被理解。在这里，我们提出了一个多能性模型，该模型通过对基因表达的多阶段随机描述，明确地考虑了DNA活性和mRNA稳定性的调节。我们将借助主办实验室在基因表达随机建模(Swain)和多能性分子基础(Chambers)方面的专业知识，以及申请者S在分析调控方面的背景，建立一个详细的生物化学激励模型。我们将通过马尔可夫跳跃过程模拟系统来分析噪声的影响。利用Ian Chambers实验室的表达数据，我们希望估计系统参数并识别不同时间尺度上的过程。这些观察结果证明了系统分析描述中的近似性是合理的。我们将用分析方法描绘分子丰度和分布，并将它们与数据进行比较。最后，我们希望预测特定系统扰动的影响，并设计实验来验证我们的预测。通过这种跨学科的努力，我们希望深入了解对多能性的多层监管控制。

Models of gene regulatory networks are essential to understand cellular processes from a mechanistic perspective. Present models of self-renewal and differentiation of embryonic stem cells focus on the transcriptional regulation between the key pluripotency factors. However, recent reports pinpoint additional layers of regulatory control, most importantly chromatin remodeling and post-transcriptional regulation via microRNAs. The linkage of these different layers of regulatory control and its implications on pluripotency are far from understood. Here, we propose the development of a model of pluripotency, which explicitly considers the regulation of DNA activity and mRNA stability via a multi-stage stochastic description of gene expression. With the expertise of the host laboratories in stochastic modeling of gene expression (Swain) and in the molecular foundations of pluripotency (Chambers) and the applicant"s background in analyzing regulatory control, we will set up a detailed, biochemically motivated model. We will analyze the effects of noise by simulating the system with Markov jump processes. With expression data from Ian Chambers" laboratory, we want to estimate systemic parameters and identify processes on different time scales. These observations justify approximations in the analytical description of the system. We will delineate molecular abundances and distributions with analytical methods and compare them to the data. Finally, we want to anticipate the effects of specific system perturbations and design experiments to test our predictions. With this interdisciplinary effort we want to get insights into the multi-layered regulatory control of pluripotency.