IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v8y2017i1d10.1038_s41467-017-02386-3.html
   My bibliography  Save this article

Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains

Author

Listed:
  • Gil Ron

    (The Hebrew University of Jerusalem)

  • Yuval Globerson

    (The Hebrew University of Jerusalem)

  • Dror Moran

    (The Hebrew University of Jerusalem)

  • Tommy Kaplan

    (The Hebrew University of Jerusalem)

Abstract

Proximity-ligation methods such as Hi-C allow us to map physical DNA–DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter–enhancer interactions. We use a unified probabilistic model to segment the genome into domains, which we then merge hierarchically and fit using a local background model, allowing us to identify over-represented DNA–DNA interactions across the genome. By analyzing the published Hi-C data sets in human and mouse, we identify hundreds of thousands of putative enhancers and their target genes, and compile an extensive genome-wide catalog of gene regulation in human and mouse. As we show, our predictions are highly enriched for ChIP-seq and DNA accessibility data, evolutionary conservation, eQTLs and other DNA–DNA interaction data.

Suggested Citation

  • Gil Ron & Yuval Globerson & Dror Moran & Tommy Kaplan, 2017. "Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains," Nature Communications, Nature, vol. 8(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-02386-3
    DOI: 10.1038/s41467-017-02386-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-017-02386-3
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-017-02386-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Long Jin & Danyang Wang & Jiaman Zhang & Pengliang Liu & Yujie Wang & Yu Lin & Can Liu & Ziyin Han & Keren Long & Diyan Li & Yu Jiang & Guisen Li & Yu Zhang & Jingyi Bai & Xiaokai Li & Jing Li & Lu Lu, 2023. "Dynamic chromatin architecture of the porcine adipose tissues with weight gain and loss," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    2. 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.
    3. M S Vijayabaskar & Debbie K Goode & Nadine Obier & Monika Lichtinger & Amber M L Emmett & Fatin N Zainul Abidin & Nisar Shar & Rebecca Hannah & Salam A Assi & Michael Lie-A-Ling & Berthold Gottgens & , 2019. "Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-29, November.
    4. Michael Lattke & Robert Goldstone & James K. Ellis & Stefan Boeing & Jerónimo Jurado-Arjona & Nicolás Marichal & James I. MacRae & Benedikt Berninger & Francois Guillemot, 2021. "Extensive transcriptional and chromatin changes underlie astrocyte maturation in vivo and in culture," Nature Communications, Nature, vol. 12(1), pages 1-18, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-02386-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.