title: Dissection of a complex transcriptional response using genome-wide transcriptional modelling.
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 NFkappaB 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 NFkappaB, 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.
authors.affiliation: Department of Molecular Heamatology and Cancer Biology, UCL Institute of Child Health, London, UK.
authors.forename: Martino
authors.initials: M
authors.lastname: Barenco
authors.forename: Daniel
authors.initials: D
authors.lastname: Brewer
authors.forename: Efterpi
authors.initials: E
authors.lastname: Papouli
authors.forename: Daniela
authors.initials: D
authors.lastname: Tomescu
authors.forename: Robin
authors.initials: R
authors.lastname: Callard
authors.forename: Jaroslav
authors.initials: J
authors.lastname: Stark
authors.forename: Michael
authors.initials: M
authors.lastname: Hubank
mesh_terms: D002460:Cell Line; D016000:Cluster Analysis; D019295:Computational Biology; D004249:DNA Damage / Q000235:genetics; D020869:Gene Expression Profiling; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D020871:RNA Stability / Q000528:radiation effects; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D011839:Radiation, Ionizing; D015203:Reproducibility of Results; D013997:Time Factors; D014157:Transcription Factors / Q000378:metabolism; D014158:Transcription, Genetic / Q000235:genetics* / Q000528:radiation effects; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism; D015854:Up-Regulation / Q000235:genetics / Q000528:radiation effects
chemical_list: D012333:RNA, Messenger; D014157:Transcription Factors; D016159:Tumor Suppressor Protein p53