Doostparast Torshizi, A. | bioRxiv Science

bioRxiv2018

Transcriptional Network Analysis on Brains Reveals a Potential Regulatory Role of PPP1R3F in Autism Spectrum Disorders

ObjectiveThis study aims at identifying master regulators of transcriptional networks in autism spectrum disorders (ASDs).\n\nResultsWith two sets of independent RNA-Seq data generated on cerebellum from patients with ASDs and control subjects (N=39 and 45 for set 1, N=24 and 38 for set 2, respectively), we carried out a network deconvolution of transcriptomic data, followed by virtual protein activity analysis. We identified PPP1R3F (Protein Phosphatase 1 Regulatory Subunit 3F) as a master regulator affecting a large body of downstream genes that are associated with the disease phenotype. Pathway enrichment analysis on the identified targets of PPP1R3F in both datasets indicated alteration of endocytosis pathway. This exploratory analysis is limited by sample size, but it illustrates a successful application of network deconvolution approaches in the analysis of brain gene expression data and generates a hypotheses that may be further validated by large-scale studies in the future.

bioinformatics↗

bioRxiv2017

Reverse Engineering of Trascriptional Networks Uncovers Candidate Master Regulators Governing Neuropathology of Schizophrenia

Tissue-specific reverse engineering of transcriptional networks has uncovered master regulators (MRs) of cellular networks in various cancers, yet the application of this method to neuropsychiatric disorders is largely unexplored. Here, using RNA-Seq data on postmortem dorsolateral prefrontal cortex (DLPFC) from schizophrenia (SCZ) patients and control subjects, we deconvolved the transcriptional network to identify MRs that mediate expression of a large body of target genes. Together with an independent RNA-Seq data on cultured cells derived from olfactory neuroepithelium, we identified TCF4, a leading SCZ risk locus implicated by genome-wide association studies, as one of the top candidate MRs that may be potentially dysregulated in SCZ. We validated the dysregulated TCF4-related transcriptional network through examining the transcription factor binding footprints inferred from human induced pluripotent stem cell (hiPSC)-derived neuronal ATAC-Seq data, as well as direct binding sites obtained from ChIP-seq data in SH-SY5Y cells. The predicted TCF4 transcriptional targets were enriched for genes showing transcriptomic changes upon knockdown of TCF4 in hiPSC-derived neural progenitor cells (NPC) and glutamatergic neurons (Glut_N), based on observations from three separate cell lines. The altered TCF4 gene network perturbations in NPC, as compared to that in Glut_N, was more similar to the expression differences in the TCF4 gene network observed in the DLPFC of individuals with SCZ. Moreover, TCF4-associated gene expression changes in NPC were more enriched than Glut_N for pathways involved in neuronal activity, genome-wide significant SCZ risk genes, and SCZ-associated de novo mutations. Our results suggest that TCF4 may potentially serve as a MR of a gene network that confers susceptibility to SCZ at early stage of neurodevelopment, highlighting the importance of network dysregulation involving core genes and many hundreds of peripheral genes in conferring susceptibility to neuropsychiatric diseases.

neuroscience↗