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Single-cell Hi-C reveals cell-to-cell variability in chromosome structure

Author

Listed:
  • Takashi Nagano

    (Nuclear Dynamics Programme, The Babraham Institute, Cambridge CB22 3AT, UK)

  • Yaniv Lubling

    (Weizmann Institute, Rehovot 76100, Israel)

  • Tim J. Stevens

    (University of Cambridge, Cambridge CB2 1GA, UK)

  • Stefan Schoenfelder

    (Nuclear Dynamics Programme, The Babraham Institute, Cambridge CB22 3AT, UK)

  • Eitan Yaffe

    (Weizmann Institute, Rehovot 76100, Israel)

  • Wendy Dean

    (Epigenetics Programme, The Babraham Institute, Cambridge CB22 3AT, UK)

  • Ernest D. Laue

    (University of Cambridge, Cambridge CB2 1GA, UK)

  • Amos Tanay

    (Weizmann Institute, Rehovot 76100, Israel)

  • Peter Fraser

    (Nuclear Dynamics Programme, The Babraham Institute, Cambridge CB22 3AT, UK)

Abstract

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture (3C) assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single-cell Hi-C, combined with genome-wide statistical analysis and structural modelling of single-copy X chromosomes, to show that individual chromosomes maintain domain organization at the megabase scale, but show variable cell-to-cell chromosome structures at larger scales. Despite this structural stochasticity, localization of active gene domains to boundaries of chromosome territories is a hallmark of chromosomal conformation. Single-cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organization underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns.

Suggested Citation

  • Takashi Nagano & Yaniv Lubling & Tim J. Stevens & Stefan Schoenfelder & Eitan Yaffe & Wendy Dean & Ernest D. Laue & Amos Tanay & Peter Fraser, 2013. "Single-cell Hi-C reveals cell-to-cell variability in chromosome structure," Nature, Nature, vol. 502(7469), pages 59-64, October.
    • Handle: RePEc:nat:nature:v:502:y:2013:i:7469:d:10.1038_nature12593
    DOI: 10.1038/nature12593
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    Citations

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    Cited by:

    1. Zhaohui Qin & Ben Li & Karen N. Conneely & Hao Wu & Ming Hu & Deepak Ayyala & Yongseok Park & Victor X. Jin & Fangyuan Zhang & Han Zhang & Li Li & Shili Lin, 2016. "Statistical Challenges in Analyzing Methylation and Long-Range Chromosomal Interaction Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 284-309, October.
    2. Guang Shi & D. Thirumalai, 2023. "A maximum-entropy model to predict 3D structural ensembles of chromatin from pairwise distances with applications to interphase chromosomes and structural variants," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. Laureano Tomás-Daza & Llorenç Rovirosa & Paula López-Martí & Andrea Nieto-Aliseda & François Serra & Ainoa Planas-Riverola & Oscar Molina & Rebecca McDonald & Cedric Ghevaert & Esther Cuatrecasas & Do, 2023. "Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    4. Ting Peng & Yingping Hou & Haowei Meng & Yong Cao & Xiaotian Wang & Lumeng Jia & Qing Chen & Yang Zheng & Yujie Sun & Hebing Chen & Tingting Li & Cheng Li, 2023. "Mapping nucleolus-associated chromatin interactions using nucleolus Hi-C reveals pattern of heterochromatin interactions," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    5. Surya K Ghosh & Daniel Jost, 2018. "How epigenome drives chromatin folding and dynamics, insights from efficient coarse-grained models of chromosomes," PLOS Computational Biology, Public Library of Science, vol. 14(5), pages 1-26, May.
    6. Hao Wang & Jiaxin Yang & Yu Zhang & Jianliang Qian & Jianrong Wang, 2022. "Reconstruct high-resolution 3D genome structures for diverse cell-types using FLAMINGO," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    7. Markus Götz & Olivier Messina & Sergio Espinola & Jean-Bernard Fiche & Marcelo Nollmann, 2022. "Multiple parameters shape the 3D chromatin structure of single nuclei at the doc locus in Drosophila," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    8. Sarah B. Reiff & Andrew J. Schroeder & Koray Kırlı & Andrea Cosolo & Clara Bakker & Luisa Mercado & Soohyun Lee & Alexander D. Veit & Alexander K. Balashov & Carl Vitzthum & William Ronchetti & Kent M, 2022. "The 4D Nucleome Data Portal as a resource for searching and visualizing curated nucleomics data," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    9. Dunming Hua & Ming Gu & Xiao Zhang & Yanyi Du & Hangcheng Xie & Li Qi & Xiangjun Du & Zhidong Bai & Xiaopeng Zhu & Dechao Tian, 2024. "DiffDomain enables identification of structurally reorganized topologically associating domains," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    10. Judith H. I. Haarhuis & Robin H. Weide & Vincent A. Blomen & Koen D. Flach & Hans Teunissen & Laureen Willems & Thijn R. Brummelkamp & Benjamin D. Rowland & Elzo Wit, 2022. "A Mediator-cohesin axis controls heterochromatin domain formation," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    11. Li-Hsin Chang & Sourav Ghosh & Andrea Papale & Jennifer M. Luppino & Mélanie Miranda & Vincent Piras & Jéril Degrouard & Joanne Edouard & Mallory Poncelet & Nathan Lecouvreur & Sébastien Bloyer & Amél, 2023. "Multi-feature clustering of CTCF binding creates robustness for loop extrusion blocking and Topologically Associating Domain boundaries," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    12. Abhijit Chakraborty & Jeffrey G. Wang & Ferhat Ay, 2022. "dcHiC detects differential compartments across multiple Hi-C datasets," Nature Communications, Nature, vol. 13(1), pages 1-21, December.

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