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Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia

80

Citations

47

References

2019

Year

Abstract

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 <i>TCF4</i> as a top candidate MR that may be dysregulated in SCZ. We validated <i>TCF4</i> as a MR through enrichment analysis of <i>TCF4</i>-binding sites in induced pluripotent stem cell (hiPSC)-derived neurons and in neuroblastoma cells. We further validated the predicted <i>TCF4</i> targets by knocking down <i>TCF4</i> in hiPSC-derived neural progenitor cells (NPCs) and glutamatergic neurons (Glut_Ns). The perturbed <i>TCF4</i> 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 <i>TCF4</i> may serve as a MR of a gene network dysregulated in SCZ at early stages of neurodevelopment.

References

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