Analysis of combinatorial regulation: scaling of partnerships between regulators with the number of governed targets.

Nitin Bhardwaj, Matthew B. Carson, Alexej Abyzov, Koon Kiu Yan, Hui Lu, Mark B. Gerstein

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Through combinatorial regulation, regulators partner with each other to control common targets and this allows a small number of regulators to govern many targets. One interesting question is that given this combinatorial regulation, how does the number of regulators scale with the number of targets? Here, we address this question by building and analyzing co-regulation (co-transcription and co-phosphorylation) networks that describe partnerships between regulators controlling common genes. We carry out analyses across five diverse species: Escherichia coli to human. These reveal many properties of partnership networks, such as the absence of a classical power-law degree distribution despite the existence of nodes with many partners. We also find that the number of co-regulatory partnerships follows an exponential saturation curve in relation to the number of targets. (For E. coli and Bacillus subtilis, only the beginning linear part of this curve is evident due to arrangement of genes into operons.) To gain intuition into the saturation process, we relate the biological regulation to more commonplace social contexts where a small number of individuals can form an intricate web of connections on the internet. Indeed, we find that the size of partnership networks saturates even as the complexity of their output increases. We also present a variety of models to account for the saturation phenomenon. In particular, we develop a simple analytical model to show how new partnerships are acquired with an increasing number of target genes; with certain assumptions, it reproduces the observed saturation. Then, we build a more general simulation of network growth and find agreement with a wide range of real networks. Finally, we perform various down-sampling calculations on the observed data to illustrate the robustness of our conclusions.

Original languageEnglish (US)
JournalPLoS Computational Biology
Volume6
Issue number5
DOIs
StatePublished - 2010
Externally publishedYes

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Regulator
Genes
Scaling
saturation
Escherichia coli
Biological Phenomena
Intuition
Target
Gene Order
Operon
Bacillus subtilis
Saturation
Internet
gene
Phosphorylation
genes
Bacilli
operon
Transcription
Gene

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience
  • Ecology
  • Molecular Biology
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Computational Theory and Mathematics

Cite this

Analysis of combinatorial regulation : scaling of partnerships between regulators with the number of governed targets. / Bhardwaj, Nitin; Carson, Matthew B.; Abyzov, Alexej; Yan, Koon Kiu; Lu, Hui; Gerstein, Mark B.

In: PLoS Computational Biology, Vol. 6, No. 5, 2010.

Research output: Contribution to journalArticle

Bhardwaj, Nitin ; Carson, Matthew B. ; Abyzov, Alexej ; Yan, Koon Kiu ; Lu, Hui ; Gerstein, Mark B. / Analysis of combinatorial regulation : scaling of partnerships between regulators with the number of governed targets. In: PLoS Computational Biology. 2010 ; Vol. 6, No. 5.
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