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Evolutionary rates and centrality in the yeast gene regulatory network

Richard Jovelin* and Patrick C Phillips

Author affiliations

Center for Ecology and Evolutionary Biology, 5289 University of Oregon, Eugene, OR 97403, USA

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Citation and License

Genome Biology 2009, 10:R35  doi:10.1186/gb-2009-10-4-r35

Published: 9 April 2009

Abstract

Background

Transcription factors play a fundamental role in regulating physiological responses and developmental processes. Here we examine the evolution of the yeast transcription factors in the context of the structure of the gene regulatory network.

Results

In contrast to previous results for the protein-protein interaction and metabolic networks, we find that the position of a gene within the transcription network affects the rate of protein evolution such that more central transcription factors tend to evolve faster. Centrality is also positively correlated with expression variability, suggesting that the higher rate of divergence among central transcription factors may be due to their role in controlling information flow and may be the result of adaptation to changing environmental conditions. Alternatively, more central transcription factors could be more buffered against environmental perturbations and, therefore, less subject to strong purifying selection. Importantly, the relationship between centrality and evolutionary rates is independent of expression level, expression variability and gene essentiality.

Conclusions

Our analysis of the transcription network highlights the role of network structure on protein evolutionary rate. Further, the effect of network centrality on nucleotide divergence is different among the metabolic, protein-protein and transcriptional networks, suggesting that the effect of gene position is dependant on the function of the specific network under study. A better understanding of how these three cellular networks interact with one another may be needed to fully examine the impact of network structure on the function and evolution of biological systems.