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Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules
BACKGROUND: In the recent studies, it is suggested that the analysis of transcriptomic change of functional modules instead of individual genes would be more effective for system-wide identification of cellular functions. This could also provide a new possibility for the better understanding of diff...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681143/ https://www.ncbi.nlm.nih.gov/pubmed/26671687 http://dx.doi.org/10.1186/s40659-015-0061-4 |
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author | Oh, Kimin Hwang, Taeho Cha, Kihoon Yi, Gwan-Su |
author_facet | Oh, Kimin Hwang, Taeho Cha, Kihoon Yi, Gwan-Su |
author_sort | Oh, Kimin |
collection | PubMed |
description | BACKGROUND: In the recent studies, it is suggested that the analysis of transcriptomic change of functional modules instead of individual genes would be more effective for system-wide identification of cellular functions. This could also provide a new possibility for the better understanding of difference between human and chimpanzee. RESULTS: In this study, we analyzed to find molecular characteristics of human brain functions from the difference of transcriptome between human and chimpanzee’s brain using the functional module-centric co-expression analysis. We performed analysis of brain disease association and systems-level connectivity of species-specific co-expressed functional modules. CONCLUSIONS: Throughout the analyses, we found human-specific functional modules and significant overlap between their genes in known brain disease genes, suggesting that human brain disorder could be mediated by the perturbation of modular activities emerged in human brain specialization. In addition, the human-specific modules having neurobiological functions exhibited higher networking than other functional modules. This finding suggests that the expression of neural functions are more connected than other functions, and the resulting high-order brain functions could be identified as a result of consolidated inter-modular gene activities. Our result also showed that the functional module based transcriptome analysis has a potential to expand molecular understanding of high-order complex functions like cognitive abilities and brain disorders. |
format | Online Article Text |
id | pubmed-4681143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46811432015-12-17 Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules Oh, Kimin Hwang, Taeho Cha, Kihoon Yi, Gwan-Su Biol Res Short Report BACKGROUND: In the recent studies, it is suggested that the analysis of transcriptomic change of functional modules instead of individual genes would be more effective for system-wide identification of cellular functions. This could also provide a new possibility for the better understanding of difference between human and chimpanzee. RESULTS: In this study, we analyzed to find molecular characteristics of human brain functions from the difference of transcriptome between human and chimpanzee’s brain using the functional module-centric co-expression analysis. We performed analysis of brain disease association and systems-level connectivity of species-specific co-expressed functional modules. CONCLUSIONS: Throughout the analyses, we found human-specific functional modules and significant overlap between their genes in known brain disease genes, suggesting that human brain disorder could be mediated by the perturbation of modular activities emerged in human brain specialization. In addition, the human-specific modules having neurobiological functions exhibited higher networking than other functional modules. This finding suggests that the expression of neural functions are more connected than other functions, and the resulting high-order brain functions could be identified as a result of consolidated inter-modular gene activities. Our result also showed that the functional module based transcriptome analysis has a potential to expand molecular understanding of high-order complex functions like cognitive abilities and brain disorders. BioMed Central 2015-12-16 /pmc/articles/PMC4681143/ /pubmed/26671687 http://dx.doi.org/10.1186/s40659-015-0061-4 Text en © Oh et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Short Report Oh, Kimin Hwang, Taeho Cha, Kihoon Yi, Gwan-Su Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules |
title | Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules |
title_full | Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules |
title_fullStr | Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules |
title_full_unstemmed | Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules |
title_short | Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules |
title_sort | disease association and inter-connectivity analysis of human brain specific co-expressed functional modules |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681143/ https://www.ncbi.nlm.nih.gov/pubmed/26671687 http://dx.doi.org/10.1186/s40659-015-0061-4 |
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