Department of Genome Sciences, University of Washington, Seattle, WA, United States.
Department of Pathology, University of Washington, Seattle, WA, United States.
Methods. 2020 Jan 1;170:61-68. doi: 10.1016/j.ymeth.2019.09.012. Epub 2019 Sep 16.
The highly dynamic nature of chromosome conformation and three-dimensional (3D) genome organization leads to cell-to-cell variability in chromatin interactions within a cell population, even if the cells of the population appear to be functionally homogeneous. Hence, although Hi-C is a powerful tool for mapping 3D genome organization, this heterogeneity of chromosome higher order structure among individual cells limits the interpretive power of population based bulk Hi-C assays. Moreover, single-cell studies have the potential to enable the identification and characterization of rare cell populations or cell subtypes in a heterogeneous population. However, it may require surveying relatively large numbers of single cells to achieve statistically meaningful observations in single-cell studies. By applying combinatorial cellular indexing to chromosome conformation capture, we developed single-cell combinatorial indexed Hi-C (sci-Hi-C), a high throughput method that enables mapping chromatin interactomes in large number of single cells. We demonstrated the use of sci-Hi-C data to separate cells by karytoypic and cell-cycle state differences and to identify cellular variability in mammalian chromosomal conformation. Here, we provide a detailed description of method design and step-by-step working protocols for sci-Hi-C.
染色体构象和三维(3D)基因组组织的高度动态特性导致即使细胞群体中的细胞表现出功能上的均一性,染色质相互作用在细胞群体内也存在细胞间的可变性。因此,尽管 Hi-C 是绘制 3D 基因组组织的有力工具,但个体细胞间染色体高级结构的这种异质性限制了基于群体的批量 Hi-C 测定的解释能力。此外,单细胞研究有可能识别和表征异质群体中的稀有细胞群体或细胞亚型。然而,在单细胞研究中实现具有统计学意义的观察结果,可能需要对相对大量的单细胞进行调查。通过将组合细胞索引应用于染色体构象捕获,我们开发了单细胞组合索引 Hi-C(sci-Hi-C),这是一种高通量方法,可用于在大量单细胞中绘制染色质相互作用组。我们证明了 sci-Hi-C 数据可用于通过核型和细胞周期状态差异来分离细胞,并鉴定哺乳动物染色体构象中的细胞变异性。在这里,我们提供了 sci-Hi-C 的详细方法设计和分步工作方案描述。