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A three-dimensional model of the yeast genome

Author

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  • Zhijun Duan

    (Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington 98195-8056, USA
    University of Washington Seattle)

  • Mirela Andronescu

    (University of Washington, Seattle, Washington 98195-5065, USA)

  • Kevin Schutz

    (Graduate Program in Molecular and Cellular Biology, University of Washington, Seattle, Washington 98195-5065, USA)

  • Sean McIlwain

    (University of Washington, Seattle, Washington 98195-5065, USA)

  • Yoo Jung Kim

    (Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington 98195-8056, USA
    University of Washington Seattle)

  • Choli Lee

    (University of Washington, Seattle, Washington 98195-5065, USA)

  • Jay Shendure

    (University of Washington, Seattle, Washington 98195-5065, USA)

  • Stanley Fields

    (University of Washington Seattle
    University of Washington, Seattle, Washington 98195-5065, USA
    Howard Hughes Medical Institute)

  • C. Anthony Blau

    (Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington 98195-8056, USA
    University of Washington Seattle
    University of Washington, Seattle, Washington 98195-5065, USA)

  • William S. Noble

    (University of Washington, Seattle, Washington 98195-5065, USA)

Abstract

A genome in 3D The three-dimensional configuration of chromosomes in the nucleus of budding yeast has been determined from a kilobase-resolution map of intra- and inter-chromosomal interactions identified by high-throughput chromosome conformation capture. The genome resembles a water lily in overall shape, with 32 chromosome arms jutting out from a base of clustered centromeres at one pole of the nucleus. The 3D map, a snapshot that ignores the dynamic nature of chromosomes, provides a first glimpse into the architecture of a eukaryotic genome at high resolution, highlighting the three-dimensional complexity of the genome of even this simple organism. Further work should unveil the general organizing principles by which the DNA sequence specifies this structure.

Suggested Citation

  • Zhijun Duan & Mirela Andronescu & Kevin Schutz & Sean McIlwain & Yoo Jung Kim & Choli Lee & Jay Shendure & Stanley Fields & C. Anthony Blau & William S. Noble, 2010. "A three-dimensional model of the yeast genome," Nature, Nature, vol. 465(7296), pages 363-367, May.
    • Handle: RePEc:nat:nature:v:465:y:2010:i:7296:d:10.1038_nature08973
    DOI: 10.1038/nature08973
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    Citations

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    Cited by:

    1. Zhen Wah Tan & Enrico Guarnera & Igor N Berezovsky, 2018. "Exploring chromatin hierarchical organization via Markov State Modelling," PLOS Computational Biology, Public Library of Science, vol. 14(12), pages 1-35, December.
    2. 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.
    3. 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.
    4. Manyu Du & Fan Zou & Yi Li & Yujie Yan & Lu Bai, 2022. "Chemically Induced Chromosomal Interaction (CICI) method to study chromosome dynamics and its biological roles," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    5. Jessen V. Bredeson & Austin B. Mudd & Sofia Medina-Ruiz & Therese Mitros & Owen Kabnick Smith & Kelly E. Miller & Jessica B. Lyons & Sanjit S. Batra & Joseph Park & Kodiak C. Berkoff & Christopher Plo, 2024. "Conserved chromatin and repetitive patterns reveal slow genome evolution in frogs," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    6. Yi Li & James Lee & Lu Bai, 2024. "DNA methylation-based high-resolution mapping of long-distance chromosomal interactions in nucleosome-depleted regions," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    7. 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.
    8. Seungsoo Hahn & Dongsup Kim, 2015. "Identifying and Reducing Systematic Errors in Chromosome Conformation Capture Data," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-17, December.
    9. Benjamin Walker & Dane Taylor & Josh Lawrimore & Caitlin Hult & David Adalsteinsson & Kerry Bloom & M Gregory Forest, 2019. "Transient crosslinking kinetics optimize gene cluster interactions," PLOS Computational Biology, Public Library of Science, vol. 15(8), pages 1-28, August.
    10. 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.
    11. Alon Diament & Tamir Tuller, 2015. "Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-22, May.
    12. Jonas Paulsen & Odin Gramstad & Philippe Collas, 2015. "Manifold Based Optimization for Single-Cell 3D Genome Reconstruction," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-19, August.
    13. Zhang Qi & Xu Zheng & Lai Yutong, 2021. "An Empirical Bayes approach for the identification of long-range chromosomal interaction from Hi-C data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 20(1), pages 1-15, February.
    14. Hyelim Jo & Taemook Kim & Yujin Chun & Inkyung Jung & Daeyoup Lee, 2021. "A compendium of chromatin contact maps reflecting regulation by chromatin remodelers in budding yeast," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    15. Ofir Shukron & David Holcman, 2017. "Transient chromatin properties revealed by polymer models and stochastic simulations constructed from Chromosomal Capture data," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-20, April.
    16. Simeon Carstens & Michael Nilges & Michael Habeck, 2016. "Inferential Structure Determination of Chromosomes from Single-Cell Hi-C Data," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-33, December.

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