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

Kuljeet Singh Sandhu(Genome Institute of Singapore), Guoliang Li(Genome Institute of Singapore), Huay Mei Poh(Genome Institute of Singapore), Yu Ling Kelly Quek(University of Queensland), Yee Yen Sia(Genome Institute of Singapore), Su Qin Peh(Genome Institute of Singapore), Fabianus Hendriyan Mulawadi(Genome Institute of Singapore), Joanne Lim(Genome Institute of Singapore), Mile Šikić(University of Zagreb), Francesca Menghi(Genome Institute of Singapore), Anbupalam Thalamuthu(Genome Institute of Singapore), Wing‐Kin Sung(Genome Institute of Singapore), Xiaoan Ruan(Genome Institute of Singapore), Melissa J. Fullwood(National University of Singapore), Edison Liu(Jackson Laboratory), Péter Csermely(Semmelweis University), Y Ruan(Jackson Laboratory)
Cell Reports
October 25, 2012
Cited by 122Open Access
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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.


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