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iRegNet3D:用于编码和非编码疾病突变基因组分析的三维整合调控网络。

iRegNet3D: three-dimensional integrated regulatory network for the genomic analysis of coding and non-coding disease mutations.

作者信息

Liang Siqi, Tippens Nathaniel D, Zhou Yaoda, Mort Matthew, Stenson Peter D, Cooper David N, Yu Haiyuan

机构信息

Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, 14853, USA.

Weill Institute for Cell and Molecular Biology, Ithaca, NY, 14853, USA.

出版信息

Genome Biol. 2017 Jan 18;18(1):10. doi: 10.1186/s13059-016-1138-2.

Abstract

The mechanistic details of most disease-causing mutations remain poorly explored within the context of regulatory networks. We present a high-resolution three-dimensional integrated regulatory network (iRegNet3D) in the form of a web tool, where we resolve the interfaces of all known transcription factor (TF)-TF, TF-DNA and chromatin-chromatin interactions for the analysis of both coding and non-coding disease-associated mutations to obtain mechanistic insights into their functional impact. Using iRegNet3D, we find that disease-associated mutations may perturb the regulatory network through diverse mechanisms including chromatin looping. iRegNet3D promises to be an indispensable tool in large-scale sequencing and disease association studies.

摘要

在调控网络的背景下,大多数致病突变的机制细节仍未得到充分探索。我们以网络工具的形式展示了一个高分辨率的三维综合调控网络(iRegNet3D),在该网络中,我们解析了所有已知转录因子(TF)-TF、TF-DNA和染色质-染色质相互作用的界面,用于分析编码和非编码疾病相关突变,以获得关于其功能影响的机制性见解。使用iRegNet3D,我们发现疾病相关突变可能通过包括染色质环化在内的多种机制扰乱调控网络。iRegNet3D有望成为大规模测序和疾病关联研究中不可或缺的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32d5/5241969/bfd82d559346/13059_2016_1138_Fig1_HTML.jpg

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