Model transcriptional networks with continuously varying expression levels

BMC Evolutionary Biology

Research Article

Clifford H Taubes¹  Mauricio O Carneiro²  Daniel L Hartl² 

[1] Department of Mathematics, Harvard University, 02138, Cambridge, MA, USA;Department of Organismic and Evolutionary Biology, Harvard University, 02138, Cambridge, MA, USA;

关键词: Continuous Model;    Interact Gene;    Output Vector;    Continuous Output;    Random Insertion;   

DOI  :  10.1186/1471-2148-11-363

 received in 2011-10-27, accepted in 2011-12-19,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundAt a time when genomes are being sequenced by the hundreds, much attention has shifted from identifying genes and phenotypes to understanding the networks of interactions among genes. We developed a gene network developmental model expanding on previous models of transcription regulatory networks. In our model, each network is described by a matrix representing the interactions between transcription factors, and a vector of continuous values representing the transcription factor expression in an individual.ResultsIn this work we used the gene network model to look at the impact of mating as well as insertions and deletions of genes in the evolution of complexity of these networks. We found that the natural process of diploid mating increases the likelihood of maintaining complexity, especially in higher order networks (more than 10 genes). We also show that gene insertion is a very efficient way to add more genes to a network as it provides a much higher chance of developmental stability.ConclusionsThe continuous model affords a more complete view of the evolution of interacting genes. The notion of a continuous output vector also incorporates the reality of gene networks and graded concentrations of gene products.

【 授权许可】

CC BY   
© Carneiro et al; licensee BioMed Central Ltd. 2011