Architecture of the human regulatory network derived from ENCODE data

Mark B. Gerstein (), Anshul Kundaje, Manoj Hariharan, Stephen G. Landt, Koon-Kiu Yan, Chao Cheng, Xinmeng Jasmine Mu, Ekta Khurana, Joel Rozowsky, Roger Alexander, Renqiang Min, Pedro Alves, Alexej Abyzov, Nick Addleman, Nitin Bhardwaj, Alan P. Boyle, Philip Cayting, Alexandra Charos, David Z. Chen, Yong Cheng, Declan Clarke, Catharine Eastman, Ghia Euskirchen, Seth Frietze, Yao Fu, Jason Gertz, Fabian Grubert, Arif Harmanci, Preti Jain, Maya Kasowski, Phil Lacroute, Jing Leng, Jin Lian, Hannah Monahan, Henriette O’Geen, Zhengqing Ouyang, E. Christopher Partridge, Dorrelyn Patacsil, Florencia Pauli, Debasish Raha, Lucia Ramirez, Timothy E. Reddy, Brian Reed, Minyi Shi, Teri Slifer, Jing Wang, Linfeng Wu, Xinqiong Yang, Kevin Y. Yip, Gili Zilberman-Schapira, Serafim Batzoglou, Arend Sidow, Peggy J. Farnham, Richard M. Myers, Sherman M. Weissman and Michael Snyder ()
Additional contact information
Mark B. Gerstein: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Anshul Kundaje: Stanford University, 318 Campus Drive
Manoj Hariharan: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Stephen G. Landt: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Koon-Kiu Yan: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Chao Cheng: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Xinmeng Jasmine Mu: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Ekta Khurana: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Joel Rozowsky: Yale University, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Roger Alexander: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Renqiang Min: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Pedro Alves: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Alexej Abyzov: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Nick Addleman: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Nitin Bhardwaj: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Alan P. Boyle: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Philip Cayting: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Alexandra Charos: Cellular, and Developmental Biology, Yale University
David Z. Chen: Yale University, 51 Prospect Street, New Haven, Connecticut 06511, USA
Yong Cheng: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Declan Clarke: Yale University, 225 Prospect Street, New Haven, Connecticut 06520, USA
Catharine Eastman: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Ghia Euskirchen: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Seth Frietze: University of Southern California, Norris Comprehensive Cancer Center, 1450 Biggy Street, NRT 6503, Los Angeles, California 90089, USA
Yao Fu: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Jason Gertz: HudsonAlpha Institute for Biotechnology, 601 Genome Way
Fabian Grubert: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Arif Harmanci: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Preti Jain: HudsonAlpha Institute for Biotechnology, 601 Genome Way
Maya Kasowski: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Phil Lacroute: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Jing Leng: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Jin Lian: Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06510, USA
Hannah Monahan: Cellular, and Developmental Biology, Yale University
Henriette O’Geen: Genome Center, University of California-Davis, 451 Health Sciences Drive, Davis, California 95616, USA
Zhengqing Ouyang: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
E. Christopher Partridge: HudsonAlpha Institute for Biotechnology, 601 Genome Way
Dorrelyn Patacsil: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Florencia Pauli: HudsonAlpha Institute for Biotechnology, 601 Genome Way
Debasish Raha: Cellular, and Developmental Biology, Yale University
Lucia Ramirez: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Timothy E. Reddy: HudsonAlpha Institute for Biotechnology, 601 Genome Way
Brian Reed: Cellular, and Developmental Biology, Yale University
Minyi Shi: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Teri Slifer: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Jing Wang: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Linfeng Wu: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Xinqiong Yang: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA
Kevin Y. Yip: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Gili Zilberman-Schapira: Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA
Serafim Batzoglou: Stanford University, 318 Campus Drive
Arend Sidow: Stanford University, SUMC L235 (Edwards Bldg), 300 Pasteur Drive, Stanford, California 94305, USA
Peggy J. Farnham: University of Southern California, Norris Comprehensive Cancer Center, 1450 Biggy Street, NRT 6503, Los Angeles, California 90089, USA
Richard M. Myers: HudsonAlpha Institute for Biotechnology, 601 Genome Way
Sherman M. Weissman: Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06510, USA
Michael Snyder: Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA

Nature, 2012, vol. 489, issue 7414, 91-100

Abstract: Abstract Transcription factors 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 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors 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 transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors 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 (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, 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.

Date: 2012
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DOI: 10.1038/nature11245

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