Large-Scale Functional Organization of Long-Range Chromatin Interaction Networks

Sandhu, Kuljeet Singh, Li, Guoliang, Poh, Huay Mei, Quek, Yu Ling Kelly, Sia, Yee Yen, Peh, Su Qin, Mulawadi, Fabianus Hendriyan, Lim, Joanne, Sikic, Mile, Menghi, Francesca, Thalamuthu, Anbupalam, Sung, Wing Kin, Ruan, Xiaoan, Fullwood, Melissa Jane, Liu, Edison, Csermely, Peter and Ruan, Yijun (2012) Large-Scale Functional Organization of Long-Range Chromatin Interaction Networks. Cell Reports, 2 5: 1207-1219. doi:10.1016/j.celrep.2012.09.022

Author Sandhu, Kuljeet Singh
Li, Guoliang
Poh, Huay Mei
Quek, Yu Ling Kelly
Sia, Yee Yen
Peh, Su Qin
Mulawadi, Fabianus Hendriyan
Lim, Joanne
Sikic, Mile
Menghi, Francesca
Thalamuthu, Anbupalam
Sung, Wing Kin
Ruan, Xiaoan
Fullwood, Melissa Jane
Liu, Edison
Csermely, Peter
Ruan, Yijun
Title Large-Scale Functional Organization of Long-Range Chromatin Interaction Networks
Journal name Cell Reports   Check publisher's open access policy
ISSN 2211-1247
Publication date 2012-11-01
Year available 2012
Sub-type Article (original research)
DOI 10.1016/j.celrep.2012.09.022
Open Access Status DOI
Volume 2
Issue 5
Start page 1207
End page 1219
Total pages 13
Place of publication Cambridge, MA United States
Publisher Cell Press
Language eng
Abstract Interactions among different brain regions are usually examined through functional connectivity (FC) analysis, which is exclusively based on measuring pairwise correlations in activities. However, interactions beyond the pairwise level, i.e., higher-order interactions (HOIs), are vital in understanding the behavior of many complex systems. So far whether HOIs exist among brain regions and how they can affect brain's activities remain largely elusive. To address these issues, here we analyzed blood oxygenation level-dependent (BOLD) signals recorded from six typical macroscopic functional networks of the brain in 100 human subjects (46 males and 54 females) during the resting state. Through examining the binarized BOLD signals, we found that HOIs within and across individual networks were both very weak, regardless of the network size, topology, degree of spatial proximity, spatial scales and whether the global signal was regressed or not. To investigate the potential mechanisms underlying the weak HOIs, we analyzed the dynamics of a network model, and also found that HOIs were generally weak within a wide range of key parameters, provided that the overall dynamic feature of the model was similar to the empirical data and it was operating close to a linear fluctuation regime. Taken together, our results suggest that weak HOI may be a general property of brain's macroscopic functional networks, which implies the dominance of pairwise interactions in shaping brain activities at such a scale and warrants the validity of widely used pairwise-based FC approaches.SIGNIFICANCE STATEMENTTo explain how activities of different brain areas are coordinated through interactions is essential to reveal the mechanisms underlying various brain functions. Traditionally, such an interaction structure is commonly studied by using pairwise-based functional network analyses. It is unclear whether the interactions beyond the pairwise level (higher-order interactions or HOIs) play any role in this process. Here we show that HOIs are generally weak in macroscopic brain networks. We also suggested a possible dynamical mechanism that may underlay this phenomenon. These results provide plausible explanation for the effectiveness of widely used pairwise-based approaches in analyzing brain networks. More importantly, it reveals a simple organization of brain's macroscopic functional systems that is previously unknown.
Formatted abstract
Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these
interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities.  The communities were enriched in specific functions and were syntenic through evolution.
Disease-associated SNPs from genome-wide association studies were enriched among the nodes with fewer interactions, implying their selection against deleterious interactions by limiting the total number of interactions, a model that we further
reconciled using somatic and germline cancer mutation data. The hubs lacked disease-associated SNPs, constituted a nonrandomly interconnected core of
key cellular functions, and exhibited lethality in mouse mutants, supporting an evolutionary selection that favored the nonrandom spatial clustering of the
least-evolving key genomic domains against random genetic or transcriptional errors in the genome.  Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions.
Keyword Cancer Risk Loci
Gene Expression
Biological Networks
Complex Networks
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
Institute for Molecular Bioscience - Publications
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Citation counts: TR Web of Science Citation Count  Cited 35 times in Thomson Reuters Web of Science Article | Citations
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