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Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia
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 anot...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Association for the Advancement of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6739105/ https://www.ncbi.nlm.nih.gov/pubmed/31535015 http://dx.doi.org/10.1126/sciadv.aau4139 |
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author | Doostparast Torshizi, Abolfazl Armoskus, Chris Zhang, Hanwen Forrest, Marc P. Zhang, Siwei Souaiaia, Tade Evgrafov, Oleg V. Knowles, James A. Duan, Jubao Wang, Kai |
author_facet | Doostparast Torshizi, Abolfazl Armoskus, Chris Zhang, Hanwen Forrest, Marc P. Zhang, Siwei Souaiaia, Tade Evgrafov, Oleg V. Knowles, James A. Duan, Jubao Wang, Kai |
author_sort | Doostparast Torshizi, Abolfazl |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6739105 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-67391052019-09-18 Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia Doostparast Torshizi, Abolfazl Armoskus, Chris Zhang, Hanwen Forrest, Marc P. Zhang, Siwei Souaiaia, Tade Evgrafov, Oleg V. Knowles, James A. Duan, Jubao Wang, Kai Sci Adv Research Articles 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. American Association for the Advancement of Science 2019-09-11 /pmc/articles/PMC6739105/ /pubmed/31535015 http://dx.doi.org/10.1126/sciadv.aau4139 Text en Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Doostparast Torshizi, Abolfazl Armoskus, Chris Zhang, Hanwen Forrest, Marc P. Zhang, Siwei Souaiaia, Tade Evgrafov, Oleg V. Knowles, James A. Duan, Jubao Wang, Kai Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia |
title | Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia |
title_full | Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia |
title_fullStr | Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia |
title_full_unstemmed | Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia |
title_short | Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia |
title_sort | deconvolution of transcriptional networks identifies tcf4 as a master regulator in schizophrenia |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6739105/ https://www.ncbi.nlm.nih.gov/pubmed/31535015 http://dx.doi.org/10.1126/sciadv.aau4139 |
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