Architecture of the human regulatory network derived from ENCODE data.
Architecture of the human regulatory network derived from ENCODE data.
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DOI：
10.1038/nature11245
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发表时间：
2012-09-06
期刊：
影响因子：
64.8
通讯作者：
Snyder, Michael
中科院分区：
文献类型：
--
作者：
Gerstein, Mark B.;Kundaje, Anshul;Hariharan, Manoj;Landt, Stephen G.;Yan, Koon-Kiu;Cheng, Chao;Mu, Xinmeng Jasmine;Khurana, Ekta;Rozowsky, Joel;Alexander, Roger;Min, Renqiang;Alves, Pedro;Abyzov, Alexej;Addleman, Nick;Bhardwaj, Nitin;Boyle, Alan P.;Cayting, Philip;Charos, Alexandra;Chen, David Z.;Cheng, Yong;Clarke, Declan;Eastman, Catharine;Euskirchen, Ghia;Frietze, Seth;Fu, Yao;Gertz, Jason;Grubert, Fabian;Harmanci, Arif;Jain, Preti;Kasowski, Maya;Lacroute, Phil;Leng, Jing;Lian, Jin;Monahan, Hannah;O'Geen, Henriette;Ouyang, Zhengqing;Partridge, E. Christopher;Patacsil, Dorrelyn;Pauli, Florencia;Raha, Debasish;Ramirez, Lucia;Reddy, Timothy E.;Reed, Brian;Shi, Minyi;Slifer, Teri;Wang, Jing;Wu, Linfeng;Yang, Xinqiong;Yip, Kevin Y.;Zilberman-Schapira, Gili;Batzoglou, Serafim;Sidow, Arend;Farnham, Peggy J.;Myers, Richard M.;Weissman, Sherman M.;Snyder, Michael
转录因子（TFs）以组合方式结合以指定基因的开启和关闭状态；这些结合事件的集合形成了一个调控网络，构成了细胞的接线图。为了研究人类转录调控网络的原理，我们在458个ChIP-Seq实验中确定了119个tf的基因组结合信息。我们发现tf的组合，共同关联具有高度的环境特异性：不同的因子组合结合在特定的基因组位置。特别是，在近端和远端基因的结合上存在显著差异。我们将所有的TF结合组织成一个层次结构，并将其与其他基因组信息（如miRNA调控）整合在一起，形成一个密集的元网络。不同层次的因子具有不同的性质，如顶层因子对表达的影响更大，中层因子对靶标的协同调节可以缓解信息流瓶颈。此外，这些共同调节产生了许多丰富的网络基序，例如噪声缓冲前馈回路。最后，更多连接的网络组件受到更强的选择，并表现出更大程度的等位基因特异性活性（即与两个亲本等位基因的差异结合）。在这项研究中获得的调控信息将对解释个人基因组序列和理解人类生物学和疾病的基本原理至关重要。
Transcription factors (TFs) bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 TFs in 458 ChIP-Seq experiments. We found the combinatorial, co-association of TFs to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the TF binding into a hierarchy and integrated it with other genomic information (e.g. miRNA regulation), forming a dense meta-network. Factors at different levels have different properties: for instance, top-level TFs more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs -- e.g. noise-buffering feed-forward loops. Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (i.e., differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.
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DOI：
10.1126/science.1215040
发表时间：
2012-02-17
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
MacArthur DG;Balasubramanian S;Frankish A;Huang N;Morris J;Walter K;Jostins L;Habegger L;Pickrell JK;Montgomery SB;Albers CA;Zhang ZD;Conrad DF;Lunter G;Zheng H;Ayub Q;DePristo MA;Banks E;Hu M;Handsaker RE;Rosenfeld JA;Fromer M;Jin M;Mu XJ;Khurana E;Ye K;Kay M;Saunders GI;Suner MM;Hunt T;Barnes IH;Amid C;Carvalho-Silva DR;Bignell AH;Snow C;Yngvadottir B;Bumpstead S;Cooper DN;Xue Y;Romero IG;1000 Genomes Project Consortium;Wang J;Li Y;Gibbs RA;McCarroll SA;Dermitzakis ET;Pritchard JK;Barrett JC;Harrow J;Hurles ME;Gerstein MB;Tyler-Smith C
通讯作者：
Tyler-Smith C
影响因子：
7
作者：
Barski, Artem;Jothi, Raja;Zhao, Keji
通讯作者：
Zhao, Keji
DOI：
10.1084/jem.20102260
发表时间：
2010-11-22
期刊：
The Journal of experimental medicine
影响因子：
--
作者：
Kerenyi MA;Orkin SH
通讯作者：
Orkin SH
影响因子：
7.3
作者：
Bhardwaj, Nitin;Kim, Philip M.;Gerstein, Mark B.
通讯作者：
Gerstein, Mark B.
影响因子：
56.9
作者：
Lee, TI;Rinaldi, NJ;Young, RA
通讯作者：
Young, RA