Lawrence Berkeley National Laboratory

Identifying transcriptional regulatory elements represents a significant challenge in annotating the genomes of higher vertebrates. We have developed a computational tool, rVISTA, for high-throughput discovery of cis-regulatory elements that combines transcription factor binding site prediction and the analysis of inter-species sequence conservation. Here, we illustrate the ability of rVISTA to identify true transcription factor binding sites through the analysis of AP-1 and NFAT binding sites in the 1 Mb well-annotated cytokine gene cluster1 (Hs5q31; Mm11). The exploitation of orthologous human-mouse data set resulted in the elimination of 95% of the 38,000 binding sites predicted upon analysis of the human sequence alone, while it identified 87% of the experimentally verified binding sites in this region.