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A publish-subscribe model of genetic networks

Calcott, Brett; Balcan, Duygu; Hohenlohe, Paul

Description

We present a simple model of genetic regulatory networks in which regulatory connections among genes are mediated by a limited number of signaling molecules. Each gene in our model produces (publishes) a single gene product, which regulates the expression of other genes by binding to regulatory regions that correspond (subscribe) to that product. We explore the consequences of this publish-subscribe model of regulation for the properties of single networks and for the evolution of populations...[Show more]

dc.contributor.authorCalcott, Brett
dc.contributor.authorBalcan, Duygu
dc.contributor.authorHohenlohe, Paul
dc.date.accessioned2009-06-11T04:20:24Z
dc.date.accessioned2010-12-20T06:04:04Z
dc.date.available2009-06-11T04:20:24Z
dc.date.available2010-12-20T06:04:04Z
dc.identifier.citationPLoS ONE 3.9 (2008): e3245
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/10440/469
dc.identifier.urihttp://digitalcollections.anu.edu.au/handle/10440/469
dc.description.abstractWe present a simple model of genetic regulatory networks in which regulatory connections among genes are mediated by a limited number of signaling molecules. Each gene in our model produces (publishes) a single gene product, which regulates the expression of other genes by binding to regulatory regions that correspond (subscribe) to that product. We explore the consequences of this publish-subscribe model of regulation for the properties of single networks and for the evolution of populations of networks. Degree distributions of randomly constructed networks, particularly multimodal in-degree distributions, which depend on the length of the regulatory sequences and the number of possible gene products, differed from simpler Boolean NK models. In simulated evolution of populations of networks, single mutations in regulatory or coding regions resulted in multiple changes in regulatory connections among genes, or alternatively in neutral change that had no effect on phenotype. This resulted in remarkable evolvability in both number and length of attractors, leading to evolved networks far beyond the expectation of these measures based on random distributions. Surprisingly, this rapid evolution was not accompanied by changes in degree distribution; degree distribution in the evolved networks was not substantially different from that of randomly generated networks. The publish-subscribe model also allows exogenous gene products to create an environment, which may be noisy or stable, in which dynamic behavior occurs. In simulations, networks were able to evolve moderate levels of both mutational and environmental robustness.
dc.format15 pages
dc.publisherPublic Library of Science
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.sourcePLOS ONE (Public Library of Science)
dc.source.urihttp://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0003245
dc.subjectKeywords: gene product; article; controlled study; gene expression regulation; gene mutation; gene regulatory network; genetic code; mathematical model; phenotype; regulatory sequence; simulation; algorithm; biological model; computer simulation; environment; gene;
dc.titleA publish-subscribe model of genetic networks
dc.typeJournal article
local.identifier.citationvolume3
dcterms.dateAccepted2008-08-27
dc.date.issued2008-09-19
local.identifier.absfor220399
local.identifier.ariespublicationu4193696xPUB77
local.type.statusPublished Version
local.contributor.affiliationCalcott, Brett, Research School of Social Sciences, Philosophy Program and School of Botany and Zoology
local.contributor.affiliationBalcan, Duygu, Indiana University
local.contributor.affiliationHohenlohe, Paul, Oregon State University
local.bibliographicCitation.issue9
local.bibliographicCitation.startpagee3245
local.identifier.doi10.1371/journal.pone.0003245
dc.date.updated2015-12-08T08:03:41Z
local.identifier.scopusID2-s2.0-52449083608
CollectionsANU Research Publications

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