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

Vijay Ramani, Xinxian Deng, Ruolan Qiu, Choli Lee, Christine M Disteche, William S Noble, Zhijun Duan, Jay Shendure
doi: https://doi.org/10.1101/579573
Vijay Ramani
1Department of Genome Sciences, University of Washington, Seattle, WA
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Xinxian Deng
2Department of Pathology, University of Washington, Seattle, WA
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Ruolan Qiu
1Department of Genome Sciences, University of Washington, Seattle, WA
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Choli Lee
1Department of Genome Sciences, University of Washington, Seattle, WA
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Christine M Disteche
2Department of Pathology, University of Washington, Seattle, WA
3Department of Medicine, University of Washington, Seattle, WA
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William S Noble
1Department of Genome Sciences, University of Washington, Seattle, WA
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Zhijun Duan
4Division of Hematology, University of Washington School of Medicine, Seattle, WA
5Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA
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  • For correspondence: zjduan@uw.edu shendure@uw.edu
Jay Shendure
1Department of Genome Sciences, University of Washington, Seattle, WA
6Howard Hughes Medical Institute, Seattle, WA
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  • For correspondence: zjduan@uw.edu shendure@uw.edu
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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.

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Posted March 15, 2019.
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Sci-Hi-C: a single-cell Hi-C method for mapping 3D genome organization in large number of single cells
Vijay Ramani, Xinxian Deng, Ruolan Qiu, Choli Lee, Christine M Disteche, William S Noble, Zhijun Duan, Jay Shendure
bioRxiv 579573; doi: https://doi.org/10.1101/579573
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Sci-Hi-C: a single-cell Hi-C method for mapping 3D genome organization in large number of single cells
Vijay Ramani, Xinxian Deng, Ruolan Qiu, Choli Lee, Christine M Disteche, William S Noble, Zhijun Duan, Jay Shendure
bioRxiv 579573; doi: https://doi.org/10.1101/579573

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