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Sci-Hi-C: A single-cell Hi-C method for mapping 3D genome organization in large number of single cells.
Ramani, Vijay; Deng, Xinxian; Qiu, Ruolan; Lee, Choli; Disteche, Christine M; Noble, William S; Shendure, Jay; Duan, Zhijun.
Affiliation
  • Ramani V; Department of Genome Sciences, University of Washington, Seattle, WA, United States. Electronic address: vijay.ramani@ucsf.edu.
  • Deng X; Department of Pathology, University of Washington, Seattle, WA, United States.
  • Qiu R; Department of Genome Sciences, University of Washington, Seattle, WA, United States.
  • Lee C; Department of Genome Sciences, University of Washington, Seattle, WA, United States.
  • Disteche CM; Department of Pathology, University of Washington, Seattle, WA, United States; Department of Medicine, University of Washington, Seattle, WA, United States.
  • Noble WS; Department of Genome Sciences, University of Washington, Seattle, WA, United States.
  • Shendure J; Department of Genome Sciences, University of Washington, Seattle, WA, United States; Howard Hughes Medical Institute, Seattle, WA, United States. Electronic address: shendure@uw.edu.
  • Duan Z; Division of Hematology, University of Washington School of Medicine, Seattle, WA, United States; Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, United States. Electronic address: zjduan@uw.edu.
Methods ; 170: 61-68, 2020 01 01.
Article in En | MEDLINE | ID: mdl-31536770
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Chromosome Mapping / Single-Cell Analysis / High-Throughput Nucleotide Sequencing Limits: Animals / Humans Language: En Journal: Methods Journal subject: BIOQUIMICA Year: 2020 Document type: Article Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Chromosome Mapping / Single-Cell Analysis / High-Throughput Nucleotide Sequencing Limits: Animals / Humans Language: En Journal: Methods Journal subject: BIOQUIMICA Year: 2020 Document type: Article Country of publication: