Carty Mark A, Elemento Olivier
Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY, 10021, USA.
Memorial Sloan Kettering Cancer Center, New York, NY, 10021, USA.
Methods Mol Biol. 2016;1418:177-89. doi: 10.1007/978-1-4939-3578-9_9.
The three dimensional (3D) architecture of chromosomes is not random but instead tightly organized due to chromatin folding and chromatin interactions between genomically distant loci. By bringing genomically distant functional elements such as enhancers and promoters into close proximity, these interactions play a key role in regulating gene expression. Some of these interactions are dynamic, that is, they differ between cell types, conditions and can be induced by specific stimuli or differentiation events. Other interactions are more structural and stable, that is they are constitutionally present across several cell types. Genome contact interactions can occur via recruitment and physical interaction between chromatin-binding proteins and correlate with epigenetic marks such as histone modifications. Absence of a contact can occur due to presence of insulators, that is, chromatin-bound complexes that physically separate genomic loci. Understanding which contacts occur or do not occur in a given cell type is important since it can help explain how genes are regulated and which functional elements are involved in such regulation. The analysis of genome contact interactions has been greatly facilitated by the relatively recent development of chromosome conformation capture (3C). In an even more recent development, 3C was combined with next generation sequencing and led to Hi-C, a technique that in theory queries all possible pairwise interactions both within the same chromosome (intra) and between chromosomes (inter). Hi-C has now been used to study genome contact interactions in several human and mouse cell types as well as in animal models such as Drosophila and yeast. While it is fair to say that Hi-C has revolutionized the study of chromatin interactions, the computational analysis of Hi-C data is extremely challenging due to the presence of biases, artifacts, random polymer ligation and the huge number of potential pairwise interactions. In this chapter, we outline a strategy for analysis of genome contact experiments based on Hi-C using R and Bioconductor.
染色体的三维（3D）结构并非随机形成，而是由于染色质折叠以及基因组上远距离位点之间的染色质相互作用而紧密组织。通过将基因组上远距离的功能元件（如增强子和启动子）拉近，这些相互作用在调节基因表达中发挥关键作用。其中一些相互作用是动态的，也就是说，它们在不同细胞类型、条件下有所不同，并且可由特定刺激或分化事件诱导产生。其他相互作用则更具结构性且稳定，即它们在多种细胞类型中都固有存在。基因组接触相互作用可通过染色质结合蛋白之间的募集和物理相互作用发生，并与表观遗传标记（如组蛋白修饰）相关。由于绝缘子的存在，即物理上分隔基因组位点的染色质结合复合物，可能会导致接触缺失。了解在给定细胞类型中哪些接触发生或未发生很重要，因为这有助于解释基因是如何被调控的以及哪些功能元件参与了这种调控。染色体构象捕获技术（3C）的相对较新发展极大地促进了基因组接触相互作用的分析。在更近的发展中，3C与下一代测序相结合并产生了Hi-C技术，该技术理论上可查询同一染色体内部（ intra）以及不同染色体之间（inter）的所有可能的成对相互作用。Hi-C现已用于研究多种人类和小鼠细胞类型以及果蝇和酵母等动物模型中的基因组接触相互作用。虽然可以说Hi-C彻底改变了染色质相互作用的研究，但由于存在偏差、假象、随机聚合物连接以及大量潜在的成对相互作用，Hi-C数据 的计算分析极具挑战性。在本章中，我们概述了一种基于Hi-C使用R和Bioconductor分析基因组接触实验的策略。
