Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data

Simple item page
dc.contributor.authorYin, Liduoen
dc.contributor.authorBanerjee, Sharmien
dc.contributor.authorFan, Jiayien
dc.contributor.authorHe, Jianlinen
dc.contributor.authorLu, Xuemeien
dc.contributor.authorXie, Hehuangen
dc.date.accessioned2021-10-06T12:08:15Zen
dc.date.available2021-10-06T12:08:15Zen
dc.date.issued2020-01-01en
dc.date.updated2021-10-06T12:08:11Zen
dc.description.abstractThe 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).en
dc.description.versionPublished versionen
dc.format.extentPages 942-952en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1016/j.csbj.2020.04.007en
dc.identifier.eissn2001-0370en
dc.identifier.issn2001-0370en
dc.identifier.orcidXie, Hehuang [0000-0001-5739-1653]en
dc.identifier.otherPMC7184133en
dc.identifier.otherS2001-0370(19)30558-6 (PII)en
dc.identifier.pmid32368329en
dc.identifier.urihttp://hdl.handle.net/10919/105178en
dc.identifier.volume18en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pubmed/32368329en
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectEpigeneticsen
dc.subjectSingle cell RNA-seqen
dc.subjectSingle cell methylomeen
dc.subjectTranscription factoren
dc.subject0103 Numerical and Computational Mathematicsen
dc.subject0802 Computation Theory and Mathematicsen
dc.titleEpigenetic regulation of neuronal cell specification inferred with single cell “Omics” dataen
dc.title.serialComputational and Structural Biotechnology Journalen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherJournal Articleen
dcterms.dateAccepted2020-04-05en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Veterinary Medicineen
pubs.organisational-group/Virginia Tech/Veterinary Medicine/Biomedical Sciences and Pathobiologyen
pubs.organisational-group/Virginia Tech/University Research Institutesen
pubs.organisational-group/Virginia Tech/University Research Institutes/Biocomplexity Instituteen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciencesen
pubs.organisational-group/Virginia Tech/Faculty of Health Sciencesen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Veterinary Medicine/CVM T&R Facultyen
pubs.organisational-group/Virginia Tech/University Research Institutes/Biocomplexity Institute/SelectedFaculty1en
pubs.organisational-group/Virginia Tech/University Research Institutes/Biocomplexity Institute/Researchersen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciences/Durelle Scotten
pubs.organisational-group/Virginia Tech/Veterinary Medicine/Biomedical Sciences and Pathobiology/Otheren

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Epigenetic regulation of neuronal cell specification inferred with single cell Omics data.pdf
Size:
4.69 MB
Format:
Adobe Portable Document Format
Description:
Published version
Download

Collections

All Faculty Deposits
Scholarly Works, Biomedical Sciences and Pathobiology
Scholarly Works, Electrical and Computer Engineering
Scholarly Works, Fralin Life Sciences Institute
Scholarly Works, School of Neuroscience