Evolution of regulatory networks
Part 4. Bioinformatics
4.4. Comparative Analysis and Phylogeny
Published Online: 15 NOV 2005
Copyright © 2005 John Wiley & Sons, Ltd
Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics
How to Cite
Bornberg-Bauer, E. and Veron, A. 2005. Evolution of regulatory networks. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.4:43.
- Published Online: 15 NOV 2005
Genetic regulation is intimately related to organismal development. Therefore, the understanding of genetic regulatory network evolution is also important for the understanding of organismal evolution.
Recent advances in genomics, proteomics, and transcriptomics have provided means for comparative analysis of molecules and networks. The application of mathematical concepts such as graph analysis has helped us to analyze the data in more depth and quantify important properties of regulatory networks. The most basic element of regulatory networks is the transcription factor itself and its upstream and downstream regulatory regions. These elements arrange into motifs that have a recurrent topology across phyla. At the next higher level, motifs arrange into modules that comprise functionally and often evolutionary-related transcription factors. These are controlled by some key regulators, probably the most ancestral proteins in such a family. As of current knowledge, the major driving forces in establishing networks with a certain topology are, apart from mutations, series of single-gene duplication and domain rearrangements. A small set of anciently conserved DNA-binding domains is frequently reused and their functions fine-tuned by choice and alteration of secondary regulatory domains. Fewer general principles are known for both the structuring and the evolution of promoter regions since binding sites are sparse and fuzzy, and transcription activation is context dependent. Most recently, a controversial debate on neutral or selective evolution of expression levels has begun.
- evolution of complexity;
- genetic networks;
- protein interactions