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Understanding tissue-specificity with human tissue-specific regulatory networks

Understanding tissue-specificity with human tissue-specific regulatory networks

作     者:Weili GUO Lin ZHU Suping DENG Xingming ZHAO Deshuang HUANG 

作者机构:College of Electromics and Information Engineering Tongji University 

出 版 物:《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期:2016年第59卷第7期

页      面:51-60页

核心收录:

学科分类:1001[医学-基础医学(可授医学、理学学位)] 10[医学] 

基  金:supported by National Natural Science Foundation of China (Grant Nos. 61520106006, 31571364, 61532008, 61411140249, 61133010, 91529303, 61572363) Innovation Program of Shanghai Municipal Education Commission (Grant No. 13ZZ072) Shanghai Pujiang Program (Grant No. 13PJD032) Ph.D. Programs Foundation of Ministry of Education of China (Grant No. 20120072110040) Fundamental Research Funds for the Central Universities Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase) 

主  题:tissue-specificity gene regulatory network transcription factor tissue-specific regulation disease gene 

摘      要:Tissue-specificity is important for the function of human body. However, it is still not clear how the functional diversity of different tissues is achieved. Here we construct gene regulatory networks in 13 human tissues by integrating large-scale transcription factor(TF)-gene regulations with gene and protein expression data. By comparing these regulatory networks, we find many tissue-specific regulations that are important for tissue identity. In particular, the tissue-specific TFs are found to regulate more genes than those expressed in multiple tissues, and the processes regulated by these tissue-specific TFs are closely related to tissue ***, the regulations that are present in certain tissue are found to be enriched in the tissue associated disease genes, and these networks provide the molecular context of disease genes. Therefore, recognizing tissuespecific regulatory networks can help better understand the molecular mechanisms underlying diseases and identify new disease genes.

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