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Methods. 2020 Jan 1;170:61-68. doi: 10.1016/j.ymeth.2019.09.012. Epub 2019 Sep 16.

Sci-Hi-C: A single-cell Hi-C method for mapping 3D genome organization in large number of single cells.

Author information

1
Department of Genome Sciences, University of Washington, Seattle, WA, United States. Electronic address: vijay.ramani@ucsf.edu.
2
Department of Pathology, University of Washington, Seattle, WA, United States.
3
Department of Genome Sciences, University of Washington, Seattle, WA, United States.
4
Department of Pathology, University of Washington, Seattle, WA, United States; Department of Medicine, University of Washington, Seattle, WA, United States.
5
Department of Genome Sciences, University of Washington, Seattle, WA, United States; Howard Hughes Medical Institute, Seattle, WA, United States. Electronic address: shendure@uw.edu.
6
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.

Abstract

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.

KEYWORDS:

Chromatin; Chromosome; Hi-C; Sci-Hi-C; Single cell; Single-cell Hi-C; Three-dimensional (3D) genome architecture

PMID:
31536770
PMCID:
PMC6949367
[Available on 2021-01-01]
DOI:
10.1016/j.ymeth.2019.09.012

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