TY - JOUR T1 - Reverse Engineering of Trascriptional Networks Uncovers Candidate Master Regulators Governing Neuropathology of Schizophrenia JF - bioRxiv DO - 10.1101/133363 SP - 133363 AU - Abolfazl Doostparast Torshizi AU - Chris Armoskus AU - Siwei Zhang AU - Winton Moy AU - Oleg V Evgrafov AU - Jubao Duan AU - James A Knowles AU - Kai Wang Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/05/05/133363.abstract N2 - Tissue-specific reverse engineering of transcriptional networks has led to groundbreaking discoveries uncovering underlying regulators of cellular networks in various diseases. However, whether these approaches can be applied to complex psychiatric diseases is largely unexplored, partly due to the general lack of appropriate cellular models for mental disorders. In this study, using a recently published high quality RNA-seq data on dorsolateral prefrontal cortex from 307 Schizophrenia (SCZ) patients and 245 controls, we deconvoluted the transcriptional network aiming at the identification of master regulators mediating expression of a large body of genes. Together with an independent RNA-seq data on cultured primary neuronal cells derived from olfactory neuroepithelium from a cohort of 143 SCZ cases and 112 controls, we identified five candidate master regulators (MRs), including TCF4, NR1H2, HDAC9, ZNF10, and ZNF436. TCF4 was previously identified as a SCZ susceptibility gene, but its regulatory subnetworks had been elusive. Other genes have not been convincingly associated with SCZ in previous studies. Additional analysis of predicted transcription factor binding site, ChIP-Seq data and ATAC-Seq data confirmed many predicted regulatory targets by the identified MRs. Our study uncovered a few candidate master regulators for SCZ that affects a collection of genes, and these master regulators may serve as therapeutic targets for intervention. ER -