Unknown

Dataset Information

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

SUBMITTER: Barenco M 

PROVIDER: S-EPMC2795478 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature