Inferring the transcriptional regulatory mechanism of signal-dependent gene expression via an integrative computational approach.
Sufeng ChiangHisaaki ShinoharaJia-Hsin HuangHuai-Kuang TsaiMariko OkadaPublished in: FEBS letters (2020)
Eukaryotic transcription factors (TFs) coordinate different upstream signals to regulate the expression of their target genes. To unveil this regulatory network in B-cell receptor signaling, we developed a computational pipeline to systematically analyze the extracellular signal-regulated kinase (ERK)- and IκB kinase (IKK)-dependent transcriptome responses. We combined a bilinear regression method and kinetic modeling to identify the signal-to-TF and TF-to-gene dynamics, respectively. We input a set of time-course experimental data for B cells and concentrated on transcriptional activators. The results show that the combination of TFs differentially controlled by ERK and IKK could contribute divergent expression dynamics in orchestrating the B-cell response. Our findings provide insights into the regulatory mechanisms underlying signal-dependent gene expression in eukaryotic cells.
Keyphrases
- gene expression
- transcription factor
- genome wide identification
- poor prognosis
- genome wide
- dna methylation
- signaling pathway
- induced apoptosis
- cell proliferation
- dna binding
- pi k akt
- cell cycle arrest
- protein kinase
- binding protein
- copy number
- tyrosine kinase
- cell death
- machine learning
- long non coding rna
- oxidative stress
- genome wide analysis