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This content will become publicly available on September 22, 2016

Title: Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Here, our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm the presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.
Authors:
ORCiD logo [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [2] ;  [3] ;  [1]
  1. Univ. of Southern California, Los Angeles, CA (United States). Dept. of Molecular and Computational Biology, Dept. of Biological Sciences
  2. Univ. of California, San Francisco, CA (United States). Dept. of Anatomy; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physical Biosciences Division; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Center for X-Ray Tomography, Advanced Light Source
  3. Univ. of Southern California, Los Angeles, CA (United States). Dept. of Molecular and Computational Biology, Dept. of Biological Sciences; Univ. of Southern California, Los Angeles, CA (United States). Dept. of Chemistry and Norris Comprehensive Cancer Center
Publication Date:
OSTI Identifier:
1240760
Grant/Contract Number:
AC02-05CH11231; P41GM103445; U01HL108634; R01GM096089; 5R01 AI113009; U54DK107981-01
Type:
Published Article
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Volume: 113; Journal Issue: 12; Journal ID: ISSN 0027-8424
Publisher:
National Academy of Sciences, Washington, DC (United States)
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Institutes of Health (NIH); Arnold and Mabel Beckman Foundation
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 3D genome organization; Hi-C data analysis; genome structure modeling; centromere clustering; human genome