Exploring how the genome folds through proximity ligation and sequencing

生物系统包含大量的成分，它们的物理相互作用会带来 关于细胞过程的。分子生物学中的一个基本问题是对这些 并破译它们的功能后果。高通量测序具有 使我们能够快速、高分辨率和 Vivo(例如，通过ChIP-Seq结合蛋白质-DNA和通过RIP-Seq结合蛋白质-RNA)。但很多人 相互作用不受这些方法的影响(例如，RNARNA复合体、ncRNA-DNA 结合，以及-除了下面描述的最近的工作-DNA-DNA接触和基因组 折叠。) 这一差距可以通过结合高通量测序和基于邻近连接的方法来弥合 方法：研究方法。在邻近连接中，空间上邻近的核酸彼此连接，形成 嵌合型寡头。对X和Y组成的嵌合体的观察表明，X和Y必须 在原始样本中已经很接近了。因此，关于空间的问题 排列变成了关于序列组成的问题，使得采取 高通量测序的优势。然而，这些方法的发展 具有挑战性：它们涉及微妙的分子生物学，并产生大量的高维 数据集需要全新的分析范式，包括广泛的物理建模。 我们最近开发了Hi-C，这是第一项将近距离结扎和高位结扎相结合的技术。 以无偏的、全基因组的方式进行吞吐量测序(Lieberman-Aiden等人，《科学》， 2009年)。HI-C使用DNA-DNA邻近连接步骤来识别远程物理接触 在活体内的基因组DNA座位之间。我们使用Hi-C创建了一个低分辨率的三维 人类基因组图谱，并取得了两个重大发现：(1)基因调控是 伴随着基因从“开”到“关”的三维运动 隔室，反之亦然；(2)一种前所未见的大分子状态，即分形球， 它结合了超乎寻常的空间密度和完全没有结点。 在这里，我们建议通过构建新一代工具来极大地扩展上述工作 用于系统地探索基因组、RNA和蛋白质的空间组织，并通过 应用这些工具来探索RNA和蛋白质是如何建立和调节三个- 基因组的维度结构。我们将通过三个具体的研究来实现这一点 目标： (1)我们将创造一套新技术组合，将近距离结扎和 测序，以实现(A)DNA-RNA接触[通过DNA-RNA]的全面测绘 邻近连接]；(B)RNA-RNA复合体[通过RNA-RNA邻近连接]；(C)选定 蛋白质-蛋白质复合体[通过探针耦合的邻近连接]。我们将使用这些方法来 生成活体内生物分子接触的地图。 (2)我们将全面创建哺乳动物基因组的高分辨率Hi-C图谱 绘制启动者-增强者联系人图，探索大规模组织功能，如 转录工厂。 (3)我们将开发新的分析方法，将(1)和(2)产生的数据结合起来 使用新的(A)信息学工具、(B)计算分析、(C)物理模拟和(D) 严谨的理论方法。我们将描述物理相互作用如何在 分化和肿瘤发生；确定最重要的RNA、蛋白质和途径 在调节基因组折叠方面至关重要，并产生这些途径的详细物理模型 以及它们如何调节基因组的物理结构。我们计划初步应用这些 表征小鼠胚胎干细胞向下分化神经谱系的技术，以及后来 分化人类胚胎干细胞和原发肿瘤。 这一努力将产生强大的新分子方法，这将极大地改善我们的 评估细胞组件的空间排列的能力。它将改变我们的 了解哺乳动物基因组如何在细胞核内折叠。它将揭示出它有多具体 DNA、RNA和蛋白质之间的物理相互作用在分化中起着作用， 肿瘤发生和基因组折叠，并在此过程中提出新的药物靶点。最后，这一点 这项工作将生成一系列数据集，作为科学研究的宝贵资源 社区作为一个整体。

Biological systems contain a large number of components whose physical interactions bring about cellular processes. A fundamental problem in molecular biology is to catalog these interactions and to decipher their functional consequences. High throughput sequencing has made it possible to characterize some of these interactions rapidly, at high-resolution, and in vivo (e.g., protein-DNA binding via ChIP-Seq and protein-RNA binding via RIP-Seq). But many interactions are not susceptible to these methods (e.g., RNARNA complexes, ncRNA-DNA binding, and - aside from recent work described below - DNA-DNA contacts and genome folding.) This gap may be bridged by coupling high-throughput sequencing with proximity-ligation-based methods. In proximity ligation, spatially proximate nucleic acids ligate to one another, forming a chimeric oligo. Observation of a chimera composed of X and Y suggests that X and Y must have been near one another in the original sample. As a result, questions about spatial arrangement become questions about sequence composition, making it possible to take advantage of high-throughput sequencing. Nevertheless, the development of these approaches is challenging: they involve subtle molecular biology and produce massive high-dimensional datasets requiring wholly new analytical paradigms including extensive physical modeling. We recently developed Hi-C, the first technology that couples proximity ligation and high- throughput sequencing in an unbiased, genome-wide fashion (Lieberman-Aiden et al., Science, 2009). Hi-C uses a DNA-DNA proximity ligation step to identify long-range physical contacts between genomic DNA loci in vivo. We used Hi-C to create a low-resolution three-dimensional map of the human genome, and made two significant discoveries: (1) genetic regulation is accompanied by the three-dimensional movement of genes from an 'on' compartment to an 'off' compartment, and vice-versa; (2) a never-before-seen macromolecular state, the fractal globule, which couples extraordinary spatial density and a total absence of knots. Here, we propose to dramatically extend the above work, by building a new generation of tools for systematically exploring the spatial organization of genomes, RNAs, and proteins, and by applying these tools to explore how RNAs and proteins establish and regulate the three- dimensional architecture of the genome. We will accomplish this through three specific research aims: (1) We will create an ensemble of new technologies combining proximity ligation and sequencing to enable comprehensive mapping of (a) DNA-RNA contacts [via DNA-RNA proximity ligation]; (b) RNA-RNA complexes [via RNA-RNA proximity ligation]; (c) selected protein-protein complexes [via probe-coupled proximity ligation]. We will use these methods to generate maps of biomolecular contacts in vivo. (2) We will create high-resolution Hi-C maps of mammalian genomes, comprehensively mapping promoter-enhancer contacts and exploring large-scale organizational features such as transcription factories. (3) We will develop new analytical approaches that combine the data produced by (1) and (2) with new (a) informatic tools, (b) computational analyses, (c) physical simulations, and (d) rigorous theoretical methods. We will characterize how physical interactions change during differentiation and tumorigenesis; identify the RNAs, proteins and pathways that that are most crucial in regulating genome folding, and produce detailed physical models of these pathways and how they modulate the physical structure of the genome. We plan to initially apply these techniques to characterize murine ES cells differentiating down a neural lineage, and later to differentiating human ES cells and to primary tumors. This effort will produce powerful new molecular methods which will dramatically improve our ability to assess the spatial arrangement of cellular components. It will transform our understanding of how mammalian genomes fold inside the nucleus. It will reveal how specific physical interactions between DNA, RNA, and protein play a role in differentiation, tumorigenesis, and genome folding, and suggest new drug targets in the process. Finally, this work will generate a series of datasets that will serve as valuable resources for the scientific community as a whole.