Dissection of a complex transcriptional response using genome‐wide transcriptional modelling - Martino Barenco; Daniel Brewer; Efterpi Papouli; Daniela Tomescu; Robin Callard; Jaroslav Stark; Michael Hubank (Molecular Systems Biology)
Abstract Modern genomics technologies generate huge data sets creating a demand for systems level, experimentally verified, analysis techniques. We examined the transcriptional response to DNA damage in a human T cell line (MOLT4) using microarrays. By measuring both mRNA accumulation and degradation over a short time course, we were able to construct a mechanistic model of the transcriptional response. The model predicted three dominant transcriptional activity profiles—an early response controlled by NFκB and c‐Jun, a delayed response controlled by p53, and a late response related to cell cycle re‐entry. The method also identified, with defined confidence limits, the transcriptional targets associated with each activity. Experimental inhibition of NFκB, c‐Jun and p53 confirmed that target predictions were accurate. Model predictions directly explained 70% of the 200 most significantly upregulated genes in the DNA‐damage response. Genome‐wide transcriptional modelling (GWTM) requires no prior knowledge of either transcription factors or their targets. GWTM is an economical and effective method for identifying the main transcriptional activators in a complex response and confidently predicting their targets.