Dissection of a complex transcriptional response using genome-wide transcriptional modelling

Barenco, Martino, Brewer, Daniel ORCID: https://orcid.org/0000-0003-4753-9794, Papouli, Efterpi, Tomescu, Daniela, Callard, Robin, Stark, Jaroslav and Hubank, Michael (2009) Dissection of a complex transcriptional response using genome-wide transcriptional modelling. Molecular Systems Biology, 5. p. 327. ISSN 1744-4292

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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.

Item Type: Article
Uncontrolled Keywords: cell line,cluster analysis,computational biology,dna damage,gene expression profiling,genome, human,humans,models, genetic,oligonucleotide array sequence analysis,rna stability,rna, messenger,radiation, ionizing,reproducibility of results,time factors,transcription factors,transcription, genetic,tumor suppressor protein p53,up-regulation
Faculty \ School: Faculty of Science > School of Biological Sciences
UEA Research Groups: Faculty of Medicine and Health Sciences > Research Groups > Cancer Studies
Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health
Depositing User: Pure Connector
Date Deposited: 06 Jan 2014 14:12
Last Modified: 19 Oct 2023 01:15
URI: https://ueaeprints.uea.ac.uk/id/eprint/47032
DOI: 10.1038/msb.2009.84

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