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

在真核细胞的细胞核中，DNA基因组可以被化学修饰以赋予额外的，所谓的表观遗传编码信息。调控生物学中一个悬而未决的核心问题是细胞在生长和分化过程中如何解码和使用表观遗传信息。这个项目旨在通过首先发展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来解决这个问题。测试将通过在简单的细胞系统中进行实验，以及在被编程分化为人类免疫系统组成部分的细胞中进行实验。研究结果有望揭示可用于设计理想细胞结果的监管“规则”。该项目将通过与现有项目（雷尼尔学者，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，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控的设计原理。表观遗传调控是人类生物学各个方面的核心。然而，尽管它的中心地位和丰富的分子信息已经收集，我们仍然缺乏对表观遗传控制的预测性理解。该项目结合了合成生物学、发育生物学和计算机器学习方法，开发并验证了染色质状态、序列背景和特定调节因子如何共同建立基因表达状态的预测模型。这些模型将提供三个关键的好处。首先，他们将为真核生物基因调控的结构提供基本的生物学见解。其次，它们将允许基于合成染色质的调节系统的工程，提供有用的功能，包括建立稳定的基因表达状态的能力。这种合成系统将使基于细胞的疗法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其发育过程中的细胞状态转变。这些知识不仅将增强与自然细胞命运控制电路接口的能力，而且将揭示优化合成染色质调节系统功能的设计原则。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.