Prommute – A Promoter Mutation Simulation for Modeling the Evolution of Genetic Regulatory Elements
Institute of Chemistry, Eötvös University (ELTE), 1117 Budapest, Pázmány Péter sétány 1/A, Hungary
- *Corresponding Author:
- Mátyás Cserháti
Institute of Chemistry
Eötvös University (ELTE)
1117 Budapest, Pázmány Péter sétány 1/A Hungary
E-mail: [email protected]
Received Date: May 24, 2012; Accepted Date: July 17, 2012; Published Date: July 20, 2012
Citation: Cserháti M (2012) Prommute – A Promoter Mutation Simulation for Modeling the Evolution of Genetic Regulatory Elements. J Comput Sci Syst Biol 5:074-080. doi:10.4172/jcsb.1000093
Copyright: © 2012 Cserháti M. This 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.
Studying mutations in promoter sequences has revolutionized molecular genetics by taking into account changes in the sequence which facilitate functional changes. Our knowledge of such changes can be furthered by tracking these changes as they occur after each base pair mutation. Although these mutations cannot be repeated or directly observed throughout molecular evolution, they can be modeled to give a feel of the dynamics of how regulatory elements are formed through time. This article presents PromMute, the graphical promoter mutation simulation, designed to model the appearance of transcription factor binding sites in promoters through single base pair mutations. It is capable of tracking the formation of a number of transcription factor binding sites, either from yeast, or supplied by the user through a number of generations applying natural selection. The program is compared to existing programs such as ev and PPE (Probability of Promoter Evolution). Different kinds of sample test simulations were done with the program, including studying the number of generations needed for the appearance of a given motif due to random mutations as well as the dynamics of motif turnover. PromMute is capable of modelling the transcription factor binding sites and scoring them more realistically. The sample test cases presented in the article show that longer transcription factor binding sites take a longer time to form, and that such motifs are also more prone to deformation by back mutations. The program is also useful for researchers who wish to study motif turnover of their own specified motifs.