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Global gene expression profiling of healthy human brain and its application in studying neurological disorders
Brain function is governed by precise regulation of gene expression across its anatomically distinct structures; however, the expression patterns of genes across hundreds of brain structures are not clearly understood. Here, we describe a gene expression model, which is representative of the healthy...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429860/ https://www.ncbi.nlm.nih.gov/pubmed/28420888 http://dx.doi.org/10.1038/s41598-017-00952-9 |
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author | Negi, Simarjeet K. Guda, Chittibabu |
author_facet | Negi, Simarjeet K. Guda, Chittibabu |
author_sort | Negi, Simarjeet K. |
collection | PubMed |
description | Brain function is governed by precise regulation of gene expression across its anatomically distinct structures; however, the expression patterns of genes across hundreds of brain structures are not clearly understood. Here, we describe a gene expression model, which is representative of the healthy human brain transcriptome by using data from the Allen Brain Atlas. Our in-depth gene expression profiling revealed that 84% of genes are expressed in at least one of the 190 brain structures studied. Hierarchical clustering based on gene expression profiles delineated brain regions into structurally tiered spatial groups and we observed striking enrichment for region-specific processes. Further, weighted co-expression network analysis identified 19 robust modules of highly correlated genes enriched with functional associations for neurogenesis, dopamine signaling, immune regulation and behavior. Also, structural distribution maps of major neurotransmission systems in the brain were generated. Finally, we developed a supervised classification model, which achieved 84% and 81% accuracies for predicting autism- and Parkinson’s-implicated genes, respectively, using our expression model as a baseline. This study represents the first use of global gene expression profiling from healthy human brain to develop a disease gene prediction model and this generic methodology can be applied to study any neurological disorder. |
format | Online Article Text |
id | pubmed-5429860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54298602017-05-15 Global gene expression profiling of healthy human brain and its application in studying neurological disorders Negi, Simarjeet K. Guda, Chittibabu Sci Rep Article Brain function is governed by precise regulation of gene expression across its anatomically distinct structures; however, the expression patterns of genes across hundreds of brain structures are not clearly understood. Here, we describe a gene expression model, which is representative of the healthy human brain transcriptome by using data from the Allen Brain Atlas. Our in-depth gene expression profiling revealed that 84% of genes are expressed in at least one of the 190 brain structures studied. Hierarchical clustering based on gene expression profiles delineated brain regions into structurally tiered spatial groups and we observed striking enrichment for region-specific processes. Further, weighted co-expression network analysis identified 19 robust modules of highly correlated genes enriched with functional associations for neurogenesis, dopamine signaling, immune regulation and behavior. Also, structural distribution maps of major neurotransmission systems in the brain were generated. Finally, we developed a supervised classification model, which achieved 84% and 81% accuracies for predicting autism- and Parkinson’s-implicated genes, respectively, using our expression model as a baseline. This study represents the first use of global gene expression profiling from healthy human brain to develop a disease gene prediction model and this generic methodology can be applied to study any neurological disorder. Nature Publishing Group UK 2017-04-18 /pmc/articles/PMC5429860/ /pubmed/28420888 http://dx.doi.org/10.1038/s41598-017-00952-9 Text en © The Author(s) 2017 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 Negi, Simarjeet K. Guda, Chittibabu Global gene expression profiling of healthy human brain and its application in studying neurological disorders |
title | Global gene expression profiling of healthy human brain and its application in studying neurological disorders |
title_full | Global gene expression profiling of healthy human brain and its application in studying neurological disorders |
title_fullStr | Global gene expression profiling of healthy human brain and its application in studying neurological disorders |
title_full_unstemmed | Global gene expression profiling of healthy human brain and its application in studying neurological disorders |
title_short | Global gene expression profiling of healthy human brain and its application in studying neurological disorders |
title_sort | global gene expression profiling of healthy human brain and its application in studying neurological disorders |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429860/ https://www.ncbi.nlm.nih.gov/pubmed/28420888 http://dx.doi.org/10.1038/s41598-017-00952-9 |
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