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

Molecular Systems Biology
Martino BarencoMichael Hubank

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.

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Citations

Apr 5, 2011·Nucleic Acids Research·Max KoeppelMarion Lohrum
Apr 13, 2012·Nucleic Acids Research·Chengyang WangX Shirley Liu
Feb 14, 2012·Current Opinion in Immunology·Martin Turner, Daniel Hodson
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Sep 10, 2020·International Journal of Molecular Sciences·Jung-Im WonDong-Hoon Jeong
May 11, 2018·Radiation Research·M A Suresh KumarSally A Amundson

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Datasets Mentioned

BETA
E-MEXP-2177
E-MEXP-2179

Methods Mentioned

BETA
transfection
ChIP-Chip
ChIP
ChIP-seq
electrophoretic-mobility shift assay
chips

Software Mentioned

Limma
Affymetrix
DAVID
R code
ArrayExpress
GeneTrail
R
TRED
Bioconductor
HVDM

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