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

SCIENCE ADVANCES(2019)

Cited 54|Views39
No score
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.
More
Translated text
Key words
tcf4,schizophrenia,transcriptional networks,deconvolution
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined