URoL: Epigenetics 1: Control by Noncoding RNA

生物体的遗传信息是由其DNA序列编码的，然而基因的活性，如它们是否表达或沉默，是由染色质上的表观遗传标记或DNA和组蛋白的修饰控制的。表观遗传标记是稳定的，可以世代遗传。它们也可能被干扰，导致正常沉默的基因被激活，正常活跃的基因被沉默，其结果可能是发育异常和其他复杂的疾病。众所周知，DNA、组蛋白蛋白和其他调控因子如组蛋白修饰酶、转录因子和调控非编码RNA之间的相互作用决定了包括DNA和组蛋白修饰在内的表观遗传标记，从而改变了核小体的三维堆积和基因活性。这个项目为表观遗传学提供了新的综合数学建模框架，以促进我们对表观遗传学不同层次的耦合的基础知识的了解。参与该项目的研究人员，包括研究生、本科生和高中生，将在表观遗传学调控的生物系统的数学建模方面接受扎实的跨学科培训，包括模型构建/验证、敏感性分析和确定性/随机模拟。非编码RNA作为RNA结合蛋白的结合支架来招募表观遗传酶，从而发挥将表观遗传学和遗传调控结合在一起的关键调节因子的功能。尽管认识到非编码RNA在表观遗传学调控中的重要性，以及这一领域积累的丰富数据，但仍然缺乏定量工具来表征非编码RNA控制表观遗传的不同模式。缺乏非编码RNA介导的表观遗传调控的定量模型在很大程度上是由于不同层次的表观遗传学的多尺度耦合，包括组蛋白修饰、DNA甲基化和3D染色体折叠。重要的是要确定这些多尺度的相互作用如何决定染色质和基因活动的3D组织。为了实现这一目标，将建立一个通用的数学框架来研究非编码RNA对表观遗传控制的各种模式的非线性，并将研究通过非编码RNA将表观遗传和遗传调控结合在一起的各种重复调控基序的出现特性。这项研究不仅将提供目前缺乏的有价值的工具来剖析非编码RNA对表观遗传学的调控，以及对理解相关丰富的非线性动力学和紧急特性的关键影响，而且还将为建立受多尺度表观遗传学-遗传调控网络调控的一系列生物系统的模型奠定基础。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。

An organism's genetic information is coded by its DNA sequence, however the activity of genes such as whether they are expressed or silenced, is controlled by "epigenetic marks" on chromatin or modifications of DNA and histones. Epigenetic marks are stable and can be inherited from generation to generation. They also can be disrupted, leading to activation of normally silenced genes and the silencing of normally active genes, the result of which can be developmental abnormalities and other complex diseases. It is well understood that the interactions among DNA, histone proteins and other regulatory factors such as histone modification enzymes, transcription factors, and regulatory noncoding RNAs determine the epigenetic marks including DNA and histone modifications and thus change the 3D packing of nucleosome and gene activities. This project provides new integrated mathematical modeling frameworks for epigenetics to advance our fundamental knowledge on the coupling of the different layers of epigenetics. Researchers involved in the project, including graduate, undergraduate and high school students, will receive solid interdisciplinary training in mathematical modeling of epigenetics-regulated biological systems, including model construction/validation, sensitivity analysis, and deterministic/stochastic simulation.Noncoding RNAs serve as binding scaffolds for RNA-binding proteins to recruit epigenetic enzymes and thus functions as key regulators that couple epigenetic and genetic regulations. Despite the recognized importance of noncoding RNAs in the regulation of epigenetics, and the abundance of accumulated data in this area, quantitative tools are still lacking to characterize different modes of epigenetic control by noncoding RNAs. The lack of quantitative models of noncoding RNA mediated epigenetic control is largely due to the multiscale coupling of different layers of epigenetics, including histone modification, DNA methylation, and 3D chromosome folding. It is important to determine how these multiscale interactions determine the 3D organization of the chromatin and gene activities. To achieve this goal, a general mathematical framework will be developed to study the nonlinearity of various modes of epigenetic control by noncoding RNAs, and the emergent properties of various recurring regulatory motifs that couples epigenetic and genetic regulation through noncoding RNAs will be investigated. This research will not only provide valuable tools that are currently lacking to dissect the regulation of epigenetics by noncoding RNAs and critical implications for understanding the associated rich nonlinear dynamics and emergent properties, but also lay the foundation for the modeling of a host of biological systems that are regulated by a multiscale epigenetics-genetic regulatory network.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.