gamma interferon; Janus kinase; messenger RNA; microRNA; STAT protein; transcription factor; article; controlled study; gene; gene expression profiling; gene expression regulation; melanoma cell; microarray analysis; priority journal; time series analysis; transcription regulation; Cell Line; Tumor; Cluster Analysis; Cytokines; Gene Expression Profiling; Gene Regulatory Networks; Humans; Interferon Regulatory Factor-1; Interferon-gamma; Melanoma; MicroRNAs; Molecular Sequence Annotation; Oligonucleotide Array Sequence Analysis; Principal Component Analysis; RNA Interference; RNA; Messenger; Signal Transduction; STAT1 Transcription Factor
[en] MicroRNAs (miRNAs) are ubiquitously expressed small non-coding RNAs that, in most cases, negatively regulate gene expression at the posttranscriptional level. miRNAs are involved in fine-tuning fundamental cellular processes such as proliferation, cell death and cell cycle control and are believed to confer robustness to biological responses. Here, we investigated simultaneously the transcriptional changes of miRNA and mRNA expression levels over time after activation of the Janus kinase/Signal transducer and activator of transcription (Jak/STAT) pathway by interferon-c stimulation of melanoma cells. To examine global miRNA and mRNA expression patterns, time-series microarray data were analysed. We observed delayed responses of miRNAs (after 24-48 h) with respect to mRNAs (12-24 h) and identified biological functions involved at each step of the cellular response. Inference of the upstream regulators allowed for identification of transcriptional regulators involved in cellular reactions to interferon-c stimulation. Linking expression profiles of transcriptional regulators and miRNAs with their annotated functions, we demonstrate the dynamic interplay of miRNAs and upstream regulators with biological functions. Finally, our data revealed network motifs in the form of feed-forward loops involving transcriptional regulators, mRNAs and miRNAs. Additional information obtained from integrating time-series mRNA and miRNA data may represent an important step towards understanding the regulatory principles of gene expression. © The Author(s) 2013.