%0 Journal Article
%T Transcriptional Dynamics Reveal Critical Roles for Non-coding RNAs in the Immediate-Early Response
%A Ahmad M. N. Alhendi
%A Alistair R. R. Forrest
%A Carsten O. Daub
%A Colin A. Semple
%A Erik Arner
%A Hideya Kawaji
%A Levon M. Khachigian
%A Mariko Okada-Hatakeyama
%A Masayoshi Itoh
%A Piero Carninci
%A Shigeyuki Magi
%A Stuart Aitken
%A Timo Lassmann
%A Yoshihide Hayashizaki
%A the FANTOM Consortium
%J -
%D 2015
%R 10.1371/journal.pcbi.1004217
%X The immediate-early response mediates cell fate in response to a variety of extracellular stimuli and is dysregulated in many cancers. However, the specificity of the response across stimuli and cell types, and the roles of non-coding RNAs are not well understood. Using a large collection of densely-sampled time series expression data we have examined the induction of the immediate-early response in unparalleled detail, across cell types and stimuli. We exploit cap analysis of gene expression (CAGE) time series datasets to directly measure promoter activities over time. Using a novel analysis method for time series data we identify transcripts with expression patterns that closely resemble the dynamics of known immediate-early genes (IEGs) and this enables a comprehensive comparative study of these genes and their chromatin state. Surprisingly, these data suggest that the earliest transcriptional responses often involve promoters generating non-coding RNAs, many of which are produced in advance of canonical protein-coding IEGs. IEGs are known to be capable of induction without de novo protein synthesis. Consistent with this, we find that the response of both protein-coding and non-coding RNA IEGs can be explained by their transcriptionally poised, permissive chromatin state prior to stimulation. We also explore the function of non-coding RNAs in the attenuation of the immediate early response in a small RNA sequencing dataset matched to the CAGE data: We identify a novel set of microRNAs responsible for the attenuation of the IEG response in an estrogen receptor positive cancer cell line. Our computational statistical method is well suited to meta-analyses as there is no requirement for transcripts to pass thresholds for significant differential expression between time points, and it is agnostic to the number of time points per dataset
%K Immediate early genes
%K MicroRNAs
%K Long non-coding RNAs
%K DNA transcription
%K Transcription factors
%K Non-coding RNA
%K MAPK signaling cascades
%K Chromatin
%U https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004217