Detecting Over-represented Motifs in Alternatively Spliced Exons using Gibbs Sampling

Alternative pre-mRNA splicing is a biological mechanism with significant prevalence in complex organisms and experimentally verified association with numerous disease-causing factors. Splicing-related proteins play a significant regulatory role during this process. In this study, we applied a stochastic analysis of alternatively spliced human genes based on Gibbs sampling, in order to identify short consensus sequences that are over-represented compared to a reference Markov model describing constitutive exons of the same genes. The analysis resulted in a set of statistically significant over- represented motifs. The biological importance of these motifs was assessed by estimating the likelihood of being identified by cis-acting elements that correspond to the binding domains of splicing enhancers/silencers. The results indicate that the identified over-represented sequences are often similar to those recognized by known regulatory splicing elements.