Exploring how the genome folds through proximity ligation and sequencing

描述（由申请人提供） 翻译后摘要：生物系统包含大量的组件，其物理相互作用带来的细胞过程。分子生物学的一个基本问题是对这些相互作用进行分类，并破译它们的功能后果。高通量测序使得能够快速、高分辨率和在体内表征这些相互作用中的一些（例如，通过ChIP-Seq的蛋白质-DNA结合和通过RIP-Seq的蛋白质-RNA结合）。但是许多交互对这些方法不敏感（例如，RNA- RNA复合物、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。这个缺口可以通过将高通量测序与基于邻近连接的方法相结合来桥接。在邻近连接中，空间上邻近的核酸彼此连接，形成嵌合寡核苷酸。对由X和Y组成的嵌合体的观察表明，X和Y在原始样本中一定是彼此靠近的。因此，关于空间排列的问题变成了关于序列组成的问题，使得利用高通量测序成为可能。然而，这些方法的发展是具有挑战性的：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，这是第一种以无偏见的全基因组方式将邻近连接和高通量测序偶联的技术（Lieberman-Aiden et al.，Science，2009）。Hi-C使用DNA-DNA邻近连接步骤来鉴定体内基因组DNA位点之间的长距离物理接触。我们使用Hi-C创建了人类基因组的低分辨率三维图谱，并取得了两个重大发现：（1）遗传调控伴随着基因从“开”区室到“关”区室的三维运动，反之亦然;（2）一种从未见过的大分子状态，分形球，它结合了非凡的空间密度和完全没有结。在这里，我们建议大大扩展上述工作，通过建立新一代的工具，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和蛋白质如何建立和调节基因组的三维结构。我们将通过三个具体的研究目标来实现这一目标：（1）我们将创建一套结合邻近连接和测序的新技术，以实现（a）DNA-RNA接触[通过DNA-RNA邻近连接];（B）RNA-RNA复合物[通过RNA-RNA邻近连接];（c）选定的蛋白质-蛋白质复合物[通过探针偶联邻近连接]的全面映射。我们将使用这些方法来生成体内生物分子接触的地图。(2)我们将创建哺乳动物基因组的高分辨率Hi-C图谱，全面绘制启动子-增强子接触并探索大规模组织特征，如转录工厂。(3)我们将开发新的分析方法，将（1）和（2）产生的数据与新的（a）信息工具，（B）计算分析，（c）物理模拟和（d）严格的理论方法相结合。我们将描述在分化和肿瘤发生过程中物理相互作用如何变化;确定在调节基因组折叠中最关键的RNA，蛋白质和途径，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。我们计划首先将这些技术应用于表征分化为神经谱系的小鼠ES细胞，然后分化为人类ES细胞和原发性肿瘤。这一努力将产生强大的新分子方法，这将大大提高我们评估细胞成分空间排列的能力。它将改变我们对哺乳动物基因组如何在细胞核内折叠的理解。它将揭示DNA，RNA和蛋白质之间的特定物理相互作用如何在分化，肿瘤发生和基因组折叠中发挥作用，并在此过程中提出新的药物靶标。最后，这项工作将产生一系列数据集，作为整个科学界的宝贵资源。 公共卫生相关性：生物系统包含大量的组分，它们的物理相互作用引起细胞过程，但是我们用于识别许多这些生物分子相互作用的工具是费力和缓慢的。我们最近开发了Hi-C方法来重建人类基因组的结构，并将扩展这种技术方法来绘制体内和高通量的DNA，RNA和蛋白质之间的相互作用。我们将使用这些图谱来研究基因组折叠如何调节细胞功能，并表征细胞分化和肿瘤发生的过程，确定关键的生物分子途径和潜在的药物靶点。

DESCRIPTION (Provided by the applicant) Abstract: 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., RNA- RNA 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. Public Health Relevance: Biological systems contain a large number of components whose physical interactions bring about cellular processes, but our tools for identifying many of these biomolecular interactions are laborious and slow. We recently developed the Hi-C method for reconstructing the architecture of the human genome, and will extend this technological approach to map interactions between DNA, RNA, and protein in vivo and at high-throughput. We will use these maps to study how genome folding regulates cell function, and to characterize the process of cellular differentiation and tumorigenesis, identifying crucial biomolecular pathways and potential drug targets.