Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data

Molecular interactions between protein complexes and DNA carry out essential gene regulatory functions. Uncovering such interactions by means of chromatin-immunoprecipitation coupled with massively parallel sequencing (ChIP-Seq) has recently become the focus of intense interest. We here introduce QuEST (Quantitative Enrichment of Sequence Tags), a powerful statistical framework based on the Kernel Density Estimation approach, which utilizes ChIP-Seq data to determine positions where protein complexes come into contact with DNA. Using QuEST, we discovered several thousand binding sites for the human transcription factors SRF, GABP and NRSF at an average resolution of about 20 base-pairs. MEME-based motif analyses on the QuEST-identified sequences revealed DNA binding by cofactors of SRF, providing evidence that cofactor binding specificity can be obtained from ChIP-Seq data. By combining QuEST analyses with gene ontology (GO) annotations and expression data, we illustrate how general functions of transcription factors can be inferred.