Studying the Evolution of Transcription Factor Binding Events Using Multispecies ChIP-Seq Data

• Activity Number: 495
• Type: Topic Contributed
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Wei Zheng*+ and Hongyu Zhao
• Companies: Yale University and Yale School of Public Health
• Keywords: transcription factor binding ; evolution ; phlogenetic tree ; EM algorithm ; multiple sequence alignment ; ChIP-Seq

Abstract

Recent technology advances make it possible to collect whole-genome transcription factor binding (TFB) profiles from multiple species through the ChIP-Seq data. This provides rich information to understand TFB evolution. However, few rigorous statistical models are available to infer TFB evolution from these data. We have developed a phylogenetic tree based method to model the on/off rates of TFB events. There are two unique features of our method compared to existing models. First, we mask nucleotide substitutions and focus on INDEL disruption of TFB events, which are rarer evolution events and more appropriate for divergent species and non-coding regulatory regions. Second, we correct for ascertainment bias in ChIP-Seq data by maximizing likelihood conditional on the observed (incomplete) data. When this method is applied to a real example of five vertebrates ChIP-Seq data, we find that the transition rates are higher in TFB regions than in homologous nonbinding regions. When we compare the inferred transition rates between the conserved and non-conserved regions, as expected, the conserved regions are estimated to have lower transition rates.