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Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data
The brain is a highly complex organ consisting of numerous types of cells with ample diversity at the epigenetic level to achieve distinct gene expression profiles. During neuronal cell specification, transcription factors (TFs) form regulatory modules with chromatin remodeling proteins to initiate...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184133/ https://www.ncbi.nlm.nih.gov/pubmed/32368329 http://dx.doi.org/10.1016/j.csbj.2020.04.007 |
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author | Yin, Liduo Banerjee, Sharmi Fan, Jiayi He, Jianlin Lu, Xuemei Xie, Hehuang |
author_facet | Yin, Liduo Banerjee, Sharmi Fan, Jiayi He, Jianlin Lu, Xuemei Xie, Hehuang |
author_sort | Yin, Liduo |
collection | PubMed |
description | The brain is a highly complex organ consisting of numerous types of cells with ample diversity at the epigenetic level to achieve distinct gene expression profiles. During neuronal cell specification, transcription factors (TFs) form regulatory modules with chromatin remodeling proteins to initiate the cascade of epigenetic changes. Currently, little is known about brain epigenetic regulatory modules and how they regulate gene expression in a cell-type specific manner. To infer TFs involved in neuronal specification, we applied a recursive motif search approach on the differentially methylated regions identified from single-cell methylomes. The epigenetic transcription regulatory modules (ETRM), including EGR1 and MEF2C, were predicted and the co-expression of TFs in ETRMs were examined with RNA-seq data from single or sorted brain cells using a conditional probability matrix. Lastly, computational predications were validated with EGR1 ChIP-seq data. In addition, methylome and RNA-seq data generated from Egr1 knockout mice supported the essential role of EGR1 in brain epigenome programming, in particular for excitatory neurons. In summary, we demonstrated that brain single cell methylome and RNA-seq data can be integrated to gain a better understanding of how ETRMs control cell specification. The analytical pipeline implemented in this study is freely accessible in the Github repository (https://github.com/Gavin-Yinld/brain_TF). |
format | Online Article Text |
id | pubmed-7184133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-71841332020-05-04 Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data Yin, Liduo Banerjee, Sharmi Fan, Jiayi He, Jianlin Lu, Xuemei Xie, Hehuang Comput Struct Biotechnol J Research Article The brain is a highly complex organ consisting of numerous types of cells with ample diversity at the epigenetic level to achieve distinct gene expression profiles. During neuronal cell specification, transcription factors (TFs) form regulatory modules with chromatin remodeling proteins to initiate the cascade of epigenetic changes. Currently, little is known about brain epigenetic regulatory modules and how they regulate gene expression in a cell-type specific manner. To infer TFs involved in neuronal specification, we applied a recursive motif search approach on the differentially methylated regions identified from single-cell methylomes. The epigenetic transcription regulatory modules (ETRM), including EGR1 and MEF2C, were predicted and the co-expression of TFs in ETRMs were examined with RNA-seq data from single or sorted brain cells using a conditional probability matrix. Lastly, computational predications were validated with EGR1 ChIP-seq data. In addition, methylome and RNA-seq data generated from Egr1 knockout mice supported the essential role of EGR1 in brain epigenome programming, in particular for excitatory neurons. In summary, we demonstrated that brain single cell methylome and RNA-seq data can be integrated to gain a better understanding of how ETRMs control cell specification. The analytical pipeline implemented in this study is freely accessible in the Github repository (https://github.com/Gavin-Yinld/brain_TF). Research Network of Computational and Structural Biotechnology 2020-04-10 /pmc/articles/PMC7184133/ /pubmed/32368329 http://dx.doi.org/10.1016/j.csbj.2020.04.007 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Yin, Liduo Banerjee, Sharmi Fan, Jiayi He, Jianlin Lu, Xuemei Xie, Hehuang Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data |
title | Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data |
title_full | Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data |
title_fullStr | Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data |
title_full_unstemmed | Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data |
title_short | Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data |
title_sort | epigenetic regulation of neuronal cell specification inferred with single cell “omics” data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184133/ https://www.ncbi.nlm.nih.gov/pubmed/32368329 http://dx.doi.org/10.1016/j.csbj.2020.04.007 |
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