ChIP-on-chip significance analysis reveals ubiquitous transcription factor binding
© Margolin et al; licensee BioMed Central Ltd. 2007
Published: 20 November 2007
ChIP-on-chip technology provides a genome-scale view of transcription factor (TF)/target interactions and a systems-level window into transcriptional regulatory networks. However, while many studies have used ChIP-on-chip data to effectively discover new TF targets, statistical methods have fallen short of developing an accurate model to disassociate signals caused by experimental noise from those caused by true biological variation, thus leveraging the technology to provide high confidence predictions of the full range of interactions.
The method is tested on six different ChIP-on-chip arrays representing replicate experiments for three different TFs (NOTCH1, MYC and HES1). For each experiment, this analysis reveals an order of magnitude more genomic binding events than detected by traditional methods, predicting several thousand interactions for each TF and suggesting previously unappreciated complexity of transcriptional regulatory networks. Several independent experiments are used to provide evidence about the validity of these predictions. First, biochemical validation of more than 20 predicted targets by gene specific ChIP and qPCR confirm the accuracy of false discovery rate statistics computed by the method. Second, binding site enrichment analysis indicates that the strength of binding site signals are maintained over several thousand promoters. Finally, gene expression analysis reveals a coordinated downregulation of gene expression for the entire range of predicted NOTCH1 bound genes upon NOTCH1 inhibition experiments in cell lines, indicating that a large percentage of bound genes are also functionally regulated by NOTCH1.
This article is published under license to BioMed Central Ltd.