Publications - Published papers

Please find below publications of our group. Currently, we list 508 papers. Some of the publications are in collaboration with the group of Sonja Prohaska and are also listed in the publication list for her individual group. Access to published papers (access) is restricted to our local network and chosen collaborators. If you have problems accessing electronic information, please let us know:

©NOTICE: All papers are copyrighted by the authors; If you would like to use all or a portion of any paper, please contact the author.

Measuring Transcription Factor Binding Site Turnover: A Maximum Likelihood Approach using Phylogenies

Wolfgang Otto, Peter F. Stadler, Francesc López-Gialdéz, Jeffrey Townsend, Vincent Lynch, Günter P. Wagner


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Genome Biol. Evol. 1:85-98 (2009)


A major mode of gene expression evolution is based on changes in cis-regulatory elements (CREs) whose function critically depends on the presence of transcription factor binding sites (TFBS). Since CREs experience extensive TFBS turnover even with conserved function, alignment-based studies of CRE sequence evolution are limited to very closely related species. Here, we propose an alternative approach based on a stochastic model of TFBS turnover. We implemented a maximum likelihood model that permits variable turnover rates in different parts of the species tree. This model can be used to detect changes in turnover rate as a proxy for differences in the selective pressures acting on TFBS in different clades. We applied this method to five TFBS in fungi and three TFBS in the HoxA clusters of vertebrates. We find that the estimated turnover rate is generally high, with half-life ranging between ~5 million and 150 million years, with a mode around 10s of millions of years. This rate is consistent with the finding that even functionally conserved enhancers can show very low sequence similarity. We also detect statistically significant differences in the equilibrium densities of estrogen- and vertebrates. Even more extreme clade-specific differences were found in the fungal data. We conclude that stochastic models of transcription factor binding site turnover enable the detection of shifts in the selective pressures acting on CREs in different organisms. The analysis tool, called CRETO (Cis-Regulatory Element Turn-Over) can be downloaded from


cis-regulatory evolution, non-coding sequences, evolution of gene regulation, enhancer evolution, promoter evolution, evolution of development