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Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain
Theoretical and experimental work has demonstrated that excitatory (E) and inhibitory (I) currents within cortical circuits stabilize to a balanced state. This E/I balance, observed from single neuron to network levels, has a fundamental role in proper brain function and its impairment has been link...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347860/ https://www.ncbi.nlm.nih.gov/pubmed/32647210 http://dx.doi.org/10.1038/s41598-020-68165-1 |
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author | Shen, Kevin Zeppillo, Tommaso Limon, Agenor |
author_facet | Shen, Kevin Zeppillo, Tommaso Limon, Agenor |
author_sort | Shen, Kevin |
collection | PubMed |
description | Theoretical and experimental work has demonstrated that excitatory (E) and inhibitory (I) currents within cortical circuits stabilize to a balanced state. This E/I balance, observed from single neuron to network levels, has a fundamental role in proper brain function and its impairment has been linked to numerous brain disorders. Over recent years, large amount of microarray and RNA-Sequencing datasets have been collected, however few studies have made use of these resources for exploring the balance of global gene expression levels between excitatory AMPA receptors (AMPARs) and inhibitory GABA(A) receptors. Here, we analyzed the relative relationships between these receptors to generate a basic transcriptional marker of E/I ratio. Using publicly available data from the Allen Brain Institute, we generated whole brain and regional signatures of AMPAR subunit gene expression in healthy human brains as well as the transcriptional E/I (tE/I) ratio. Then we refined the tE/I ratio to cell-type signatures in the mouse brain using data from the Gene Expression Omnibus. Lastly, we applied our workflow to developmental data from the Allen Brain Institute and revealed spatially and temporally controlled changes in the tE/I ratio during the embryonic and early postnatal stages that ultimately lead to the tE/I balance in adults. |
format | Online Article Text |
id | pubmed-7347860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73478602020-07-10 Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain Shen, Kevin Zeppillo, Tommaso Limon, Agenor Sci Rep Article Theoretical and experimental work has demonstrated that excitatory (E) and inhibitory (I) currents within cortical circuits stabilize to a balanced state. This E/I balance, observed from single neuron to network levels, has a fundamental role in proper brain function and its impairment has been linked to numerous brain disorders. Over recent years, large amount of microarray and RNA-Sequencing datasets have been collected, however few studies have made use of these resources for exploring the balance of global gene expression levels between excitatory AMPA receptors (AMPARs) and inhibitory GABA(A) receptors. Here, we analyzed the relative relationships between these receptors to generate a basic transcriptional marker of E/I ratio. Using publicly available data from the Allen Brain Institute, we generated whole brain and regional signatures of AMPAR subunit gene expression in healthy human brains as well as the transcriptional E/I (tE/I) ratio. Then we refined the tE/I ratio to cell-type signatures in the mouse brain using data from the Gene Expression Omnibus. Lastly, we applied our workflow to developmental data from the Allen Brain Institute and revealed spatially and temporally controlled changes in the tE/I ratio during the embryonic and early postnatal stages that ultimately lead to the tE/I balance in adults. Nature Publishing Group UK 2020-07-09 /pmc/articles/PMC7347860/ /pubmed/32647210 http://dx.doi.org/10.1038/s41598-020-68165-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Shen, Kevin Zeppillo, Tommaso Limon, Agenor Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain |
title | Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain |
title_full | Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain |
title_fullStr | Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain |
title_full_unstemmed | Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain |
title_short | Regional transcriptome analysis of AMPA and GABA(A) receptor subunit expression generates E/I signatures of the human brain |
title_sort | regional transcriptome analysis of ampa and gaba(a) receptor subunit expression generates e/i signatures of the human brain |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347860/ https://www.ncbi.nlm.nih.gov/pubmed/32647210 http://dx.doi.org/10.1038/s41598-020-68165-1 |
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