Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia.
Abolfazl Doostparast TorshiziChris ArmoskusHanwen ZhangMarc P ForrestSiwei ZhangTade SouaiaiaOleg V EvgrafovJames A KnowlesJubao DuanKai WangPublished in: Science advances (2019)
Applying tissue-specific deconvolution of transcriptional networks to identify their master regulators (MRs) in neuropsychiatric disorders has been largely unexplored. Here, using two schizophrenia (SCZ) case-control RNA-seq datasets, one on postmortem dorsolateral prefrontal cortex (DLPFC) and another on cultured olfactory neuroepithelium, we deconvolved the transcriptional networks and identified TCF4 as a top candidate MR that may be dysregulated in SCZ. We validated TCF4 as a MR through enrichment analysis of TCF4-binding sites in induced pluripotent stem cell (hiPSC)-derived neurons and in neuroblastoma cells. We further validated the predicted TCF4 targets by knocking down TCF4 in hiPSC-derived neural progenitor cells (NPCs) and glutamatergic neurons (Glut_Ns). The perturbed TCF4 gene network in NPCs was more enriched for pathways involved in neuronal activity and SCZ-associated risk genes, compared to Glut_Ns. Our results suggest that TCF4 may serve as a MR of a gene network dysregulated in SCZ at early stages of neurodevelopment.
Keyphrases
- rna seq
- prefrontal cortex
- transcription factor
- genome wide
- stem cells
- bipolar disorder
- gene expression
- single cell
- magnetic resonance
- spinal cord
- contrast enhanced
- copy number
- case control
- genome wide identification
- endothelial cells
- magnetic resonance imaging
- spinal cord injury
- oxidative stress
- brain injury
- drug induced
- heat shock
- zika virus
- cell proliferation
- signaling pathway
- diabetic rats
- cell therapy
- network analysis
- stress induced