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

Abolfazl Doostparast Torshizi, Chris Armoskus, Hanwen Zhang, Marc P. Forrest, Siwei Zhang, Tade Souaiaia, Oleg V. Evgrafov, James A. Knowles, Jubao Duan, Kai Wang

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

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 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.

Original languageEnglish (US)
Article numberaau4139
JournalScience Advances
Volume5
Issue number9
DOIs
StatePublished - Sep 11 2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General

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