URoL: Epigenetics 2: Learning the rules of dynamic epigenetic regulation

在真核细胞的核中，DNA基因组可以进行化学修饰，以传递额外的、所谓的表观遗传编码信息。调控生物学中一个中心悬而未决的问题是，当细胞生长和分化时，表观遗传信息是如何被解码和使用的。该项目旨在解决这个问题，首先开发实验和计算策略来预测基因组及其表观遗传修饰是如何使用的，然后测试预测的有效性。测试将通过在简单的细胞系统中进行实验，以及在可分化为人类免疫系统组成部分的细胞中进行。预计研究结果将揭示可用于设计理想的细胞结果的监管“规则”。该项目将通过与现有项目(Rainier Scholars，www.rainiercholars.org)合作，通过为低收入有色人种学生提供大学毕业途径，扩大对STEM的参与，从而产生教育影响。此外，该项目的研究成果将被纳入课程模块的开发中，以便在华盛顿大学和加州理工学院这两个参与机构教授表观遗传调节的设计原理。表观遗传调控是人类生物学各个方面的核心。然而，尽管它的中心性和已经收集的丰富的分子信息，我们仍然缺乏对表观遗传控制的预测性理解。该项目结合合成生物学、发育生物学和计算机器学习方法，开发和验证染色质状态、序列背景和特定调控因子如何共同建立基因表达状态的预测模型。这些模式将提供三个关键好处。首先，他们将提供对真核基因调控架构的基本生物学见解。其次，它们将允许设计基于染色质的合成调控系统，提供有用的功能，包括建立稳定的基因表达状态的能力。这样的合成系统将使基于细胞的治疗能够利用染色质调节机制来建立、维持和改变细胞状态，以响应环境条件，甚至在参与免疫反应和其他复杂过程的细胞中也是如此。第三，这些模型将帮助研究人员了解真核生物如何利用染色质调节来控制它们发育过程中的细胞状态转换。这一知识不仅将增强与自然细胞命运控制电路的接口能力，还将揭示优化合成染色质调节系统功能的设计原则。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

In the nucleus of a eukaryotic cell, the DNA genome can be chemically modified to confer additional, so-called epigenetic, coding information. A central unanswered question in regulatory biology is how epigenetic information is decoded and used by cells as they grow and differentiate. This project aims to address that question by first developing experimental and computational strategies to predict how the genome and its epigenetic modifications are used and then testing the validity of the predictions. The testing will be done through experiments in simple cellular systems, as well as in cells programmed to differentiate into components of the human immune system. The results are expected to reveal regulatory ‘rules’ that can be used to engineer desirable cellular outcomes. The project will have educational impact by partnering with an existing program (Rainier Scholars, www.rainiercholars.org) to broaden participation in STEM by offering a pathway to college graduation for low-income students of color. In addition, research results from this project will be incorporated in development of course modules to teach design principles of epigenetic regulation at both participating institutions, the University of Washington and California Institute of Technology. Epigenetic regulation is central to all aspects of human biology. However, despite its centrality and the wealth of molecular information already collected, we still lack a predictive understanding of epigenetic control. This project combines synthetic biology, developmental biology, and computational machine learning approaches, to develop and validate predictive models of how chromatin state, sequence context, and specific regulators together establish gene expression state. These models will provide three key benefits. First, they will provide fundamental biological insight into the architecture of eukaryotic gene regulation. Second, they will permit engineering of synthetic chromatin-based regulatory systems that provide useful functionality, including the ability to establish stable gene expression states. Such synthetic systems would enable cell-based therapies that utilize the machinery of chromatin regulation to establish, maintain, and change cellular states in response to environmental conditions, even in cells participating in immune responses and other complex processes. Third, these models will help researchers understand how eukaryotic organisms harness chromatin regulation to control cell state transitions in their development. This knowledge not only will enhance the ability to interface with the natural cell fate control circuitry, but also will reveal design principles for optimizing the function of synthetic chromatin regulatory systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.