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Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks

Recent genome-wide association studies have identified numerous loci associated with neuropsychiatric disorders. The majority of these are in non-coding regions, and are commonly assigned to the nearest gene along the genome. However, this approach neglects the three-dimensional organisation of the...

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Autores principales: Barešić, Anja, Nash, Alexander Jolyon, Dahoun, Tarik, Howes, Oliver, Lenhard, Boris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906185/
https://www.ncbi.nlm.nih.gov/pubmed/31616042
http://dx.doi.org/10.1038/s41380-019-0518-x
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author Barešić, Anja
Nash, Alexander Jolyon
Dahoun, Tarik
Howes, Oliver
Lenhard, Boris
author_facet Barešić, Anja
Nash, Alexander Jolyon
Dahoun, Tarik
Howes, Oliver
Lenhard, Boris
author_sort Barešić, Anja
collection PubMed
description Recent genome-wide association studies have identified numerous loci associated with neuropsychiatric disorders. The majority of these are in non-coding regions, and are commonly assigned to the nearest gene along the genome. However, this approach neglects the three-dimensional organisation of the genome, and the fact that the genome contains arrays of extremely conserved non-coding elements termed genomic regulatory blocks (GRBs), which can be utilized to detect genes under long-range developmental regulation. Here we review a GRB-based approach to assign loci in non-coding regions to potential target genes, and apply it to reanalyse the results of one of the largest schizophrenia GWAS (SWG PGC, 2014). We further apply this approach to GWAS data from two related neuropsychiatric disorders—autism spectrum disorder and bipolar disorder—to show that it is applicable to developmental disorders in general. We find that disease-associated SNPs are overrepresented in GRBs and that the GRB model is a powerful tool for linking these SNPs to their correct target genes under long-range regulation. Our analysis identifies novel genes not previously implicated in schizophrenia and corroborates a number of predicted targets from the original study. The results are available as an online resource in which the genomic context and the strength of enhancer–promoter associations can be browsed for each schizophrenia-associated SNP.
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spelling pubmed-69061852019-12-13 Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks Barešić, Anja Nash, Alexander Jolyon Dahoun, Tarik Howes, Oliver Lenhard, Boris Mol Psychiatry Perspective Recent genome-wide association studies have identified numerous loci associated with neuropsychiatric disorders. The majority of these are in non-coding regions, and are commonly assigned to the nearest gene along the genome. However, this approach neglects the three-dimensional organisation of the genome, and the fact that the genome contains arrays of extremely conserved non-coding elements termed genomic regulatory blocks (GRBs), which can be utilized to detect genes under long-range developmental regulation. Here we review a GRB-based approach to assign loci in non-coding regions to potential target genes, and apply it to reanalyse the results of one of the largest schizophrenia GWAS (SWG PGC, 2014). We further apply this approach to GWAS data from two related neuropsychiatric disorders—autism spectrum disorder and bipolar disorder—to show that it is applicable to developmental disorders in general. We find that disease-associated SNPs are overrepresented in GRBs and that the GRB model is a powerful tool for linking these SNPs to their correct target genes under long-range regulation. Our analysis identifies novel genes not previously implicated in schizophrenia and corroborates a number of predicted targets from the original study. The results are available as an online resource in which the genomic context and the strength of enhancer–promoter associations can be browsed for each schizophrenia-associated SNP. Nature Publishing Group UK 2019-10-15 2020 /pmc/articles/PMC6906185/ /pubmed/31616042 http://dx.doi.org/10.1038/s41380-019-0518-x Text en © The Author(s) 2019 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 Perspective
Barešić, Anja
Nash, Alexander Jolyon
Dahoun, Tarik
Howes, Oliver
Lenhard, Boris
Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks
title Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks
title_full Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks
title_fullStr Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks
title_full_unstemmed Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks
title_short Understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks
title_sort understanding the genetics of neuropsychiatric disorders: the potential role of genomic regulatory blocks
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906185/
https://www.ncbi.nlm.nih.gov/pubmed/31616042
http://dx.doi.org/10.1038/s41380-019-0518-x
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