Literature DB >> 20351254

Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels.

Nitin Bhardwaj1, Koon-Kiu Yan, Mark B Gerstein.   

Abstract

Gene regulatory networks have been shown to share some common aspects with commonplace social governance structures. Thus, we can get some intuition into their organization by arranging them into well-known hierarchical layouts. These hierarchies, in turn, can be placed between the extremes of autocracies, with well-defined levels and clear chains of command, and democracies, without such defined levels and with more co-regulatory partnerships between regulators. In general, the presence of partnerships decreases the variation in information flow amongst nodes within a level, more evenly distributing stress. Here we study various regulatory networks (transcriptional, modification, and phosphorylation) for five diverse species, Escherichia coli to human. We specify three levels of regulators--top, middle, and bottom--which collectively govern the non-regulator targets lying in the lowest fourth level. We define quantities for nodes, levels, and entire networks that measure their degree of collaboration and autocratic vs. democratic character. We show individual regulators have a range of partnership tendencies: Some regulate their targets in combination with other regulators in local instantiations of democratic structure, whereas others regulate mostly in isolation, in more autocratic fashion. Overall, we show that in all networks studied the middle level has the highest collaborative propensity and coregulatory partnerships occur most frequently amongst midlevel regulators, an observation that has parallels in corporate settings where middle managers must interact most to ensure organizational effectiveness. There is, however, one notable difference between networks in different species: The amount of collaborative regulation and democratic character increases markedly with overall genomic complexity.

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Year:  2010        PMID: 20351254      PMCID: PMC2872381          DOI: 10.1073/pnas.0910867107

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  26 in total

1.  Topological and causal structure of the yeast transcriptional regulatory network.

Authors:  Nabil Guelzim; Samuele Bottani; Paul Bourgine; François Képès
Journal:  Nat Genet       Date:  2002-04-22       Impact factor: 38.330

2.  Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae.

Authors:  Christine E Horak; Nicholas M Luscombe; Jiang Qian; Paul Bertone; Stacy Piccirrillo; Mark Gerstein; Michael Snyder
Journal:  Genes Dev       Date:  2002-12-01       Impact factor: 11.361

Review 3.  Structure and evolution of transcriptional regulatory networks.

Authors:  M Madan Babu; Nicholas M Luscombe; L Aravind; Mark Gerstein; Sarah A Teichmann
Journal:  Curr Opin Struct Biol       Date:  2004-06       Impact factor: 6.809

4.  Genomic analysis of regulatory network dynamics reveals large topological changes.

Authors:  Nicholas M Luscombe; M Madan Babu; Haiyuan Yu; Michael Snyder; Sarah A Teichmann; Mark Gerstein
Journal:  Nature       Date:  2004-09-16       Impact factor: 49.962

5.  Gene regulatory network growth by duplication.

Authors:  Sarah A Teichmann; M Madan Babu
Journal:  Nat Genet       Date:  2004-04-11       Impact factor: 38.330

Review 6.  Review: compilation and characteristics of dedicated transcription factors in Saccharomyces cerevisiae.

Authors:  V V Svetlov; T G Cooper
Journal:  Yeast       Date:  1995-12       Impact factor: 3.239

7.  Transcriptional regulatory code of a eukaryotic genome.

Authors:  Christopher T Harbison; D Benjamin Gordon; Tong Ihn Lee; Nicola J Rinaldi; Kenzie D Macisaac; Timothy W Danford; Nancy M Hannett; Jean-Bosco Tagne; David B Reynolds; Jane Yoo; Ezra G Jennings; Julia Zeitlinger; Dmitry K Pokholok; Manolis Kellis; P Alex Rolfe; Ken T Takusagawa; Eric S Lander; David K Gifford; Ernest Fraenkel; Richard A Young
Journal:  Nature       Date:  2004-09-02       Impact factor: 49.962

8.  Transcriptional regulatory networks in Saccharomyces cerevisiae.

Authors:  Tong Ihn Lee; Nicola J Rinaldi; François Robert; Duncan T Odom; Ziv Bar-Joseph; Georg K Gerber; Nancy M Hannett; Christopher T Harbison; Craig M Thompson; Itamar Simon; Julia Zeitlinger; Ezra G Jennings; Heather L Murray; D Benjamin Gordon; Bing Ren; John J Wyrick; Jean-Bosco Tagne; Thomas L Volkert; Ernest Fraenkel; David K Gifford; Richard A Young
Journal:  Science       Date:  2002-10-25       Impact factor: 47.728

9.  Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach.

Authors:  Hong-Wu Ma; Jan Buer; An-Ping Zeng
Journal:  BMC Bioinformatics       Date:  2004-12-16       Impact factor: 3.169

10.  Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Authors:  Raja Jothi; S Balaji; Arthur Wuster; Joshua A Grochow; Jörg Gsponer; Teresa M Przytycka; L Aravind; M Madan Babu
Journal:  Mol Syst Biol       Date:  2009-08-18       Impact factor: 11.429

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  26 in total

1.  Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

Authors:  Koon-Kiu Yan; Gang Fang; Nitin Bhardwaj; Roger P Alexander; Mark Gerstein
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-03       Impact factor: 11.205

2.  On the origins of hierarchy in complex networks.

Authors:  Bernat Corominas-Murtra; Joaquín Goñi; Ricard V Solé; Carlos Rodríguez-Caso
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-29       Impact factor: 11.205

Review 3.  Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.

Authors:  Peter Csermely; Tamás Korcsmáros; Huba J M Kiss; Gábor London; Ruth Nussinov
Journal:  Pharmacol Ther       Date:  2013-02-04       Impact factor: 12.310

4.  Fisher's geometrical model emerges as a property of complex integrated phenotypic networks.

Authors:  Guillaume Martin
Journal:  Genetics       Date:  2014-02-28       Impact factor: 4.562

5.  A genome-wide regulatory framework identifies maize pericarp color1 controlled genes.

Authors:  Kengo Morohashi; María Isabel Casas; Maria Lorena Falcone Ferreyra; Lorena Falcone Ferreyra; María Katherine Mejía-Guerra; Lucille Pourcel; Alper Yilmaz; Antje Feller; Bruna Carvalho; Julia Emiliani; Eduardo Rodriguez; Silvina Pellegrinet; Michael McMullen; Paula Casati; Erich Grotewold
Journal:  Plant Cell       Date:  2012-07-20       Impact factor: 11.277

6.  Ensembles of signal transduction models using Pareto Optimal Ensemble Techniques (POETs).

Authors:  Sang Ok Song; Anirikh Chakrabarti; Jeffrey D Varner
Journal:  Biotechnol J       Date:  2010-07       Impact factor: 4.677

7.  SND1 transcription factor-directed quantitative functional hierarchical genetic regulatory network in wood formation in Populus trichocarpa.

Authors:  Ying-Chung Lin; Wei Li; Ying-Hsuan Sun; Sapna Kumari; Hairong Wei; Quanzi Li; Sermsawat Tunlaya-Anukit; Ronald R Sederoff; Vincent L Chiang
Journal:  Plant Cell       Date:  2013-11-26       Impact factor: 11.277

8.  SEPARATING THE CAUSES AND CONSEQUENCES IN DISEASE TRANSCRIPTOME.

Authors:  Yong Fuga Li; Fuxiao Xin; Russ B Altman
Journal:  Pac Symp Biocomput       Date:  2016

9.  Cross-Disciplinary Network Comparison: Matchmaking Between Hairballs.

Authors:  Koon-Kiu Yan; Daifeng Wang; Anurag Sethi; Paul Muir; Robert Kitchen; Chao Cheng; Mark Gerstein
Journal:  Cell Syst       Date:  2016-03-23       Impact factor: 10.304

10.  Architecture of the human regulatory network derived from ENCODE data.

Authors:  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 Jane 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; Michael Snyder
Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

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