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Assigning Co-Regulated Human Genes and Regulatory Gene Clusters

Elucidating the role of genetic variation in the regulation of gene expression is key to understanding the pathobiology of complex diseases which, in consequence, is crucial in devising targeted treatment options. Expression quantitative trait locus (eQTL) analysis correlates a genetic variant with...

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Autores principales: Strunz, Tobias, Kellner, Martin, Kiel, Christina, Weber, Bernhard H. F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470523/
https://www.ncbi.nlm.nih.gov/pubmed/34572044
http://dx.doi.org/10.3390/cells10092395
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author Strunz, Tobias
Kellner, Martin
Kiel, Christina
Weber, Bernhard H. F.
author_facet Strunz, Tobias
Kellner, Martin
Kiel, Christina
Weber, Bernhard H. F.
author_sort Strunz, Tobias
collection PubMed
description Elucidating the role of genetic variation in the regulation of gene expression is key to understanding the pathobiology of complex diseases which, in consequence, is crucial in devising targeted treatment options. Expression quantitative trait locus (eQTL) analysis correlates a genetic variant with the strength of gene expression, thus defining thousands of regulated genes in a multitude of human cell types and tissues. Some eQTL may not act independently of each other but instead may be regulated in a coordinated fashion by seemingly independent genetic variants. To address this issue, we combined the approaches of eQTL analysis and colocalization studies. Gene expression was determined in datasets comprising 49 tissues from the Genotype-Tissue Expression (GTEx) project. From about 33,000 regulated genes, over 14,000 were found to be co-regulated in pairs and were assembled across all tissues to almost 15,000 unique clusters containing up to nine regulated genes affected by the same eQTL signal. The distance of co-regulated eGenes was, on average, 112 kilobase pairs. Of 713 genes known to express clinical symptoms upon haploinsufficiency, 231 (32.4%) are part of at least one of the identified clusters. This calls for caution should treatment approaches aim at an upregulation of a haploinsufficient gene. In conclusion, we present an unbiased approach to identifying co-regulated genes in and across multiple tissues. Knowledge of such common effects is crucial to appreciate implications on biological pathways involved, specifically when a treatment option targets a co-regulated disease gene.
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spelling pubmed-84705232021-09-27 Assigning Co-Regulated Human Genes and Regulatory Gene Clusters Strunz, Tobias Kellner, Martin Kiel, Christina Weber, Bernhard H. F. Cells Article Elucidating the role of genetic variation in the regulation of gene expression is key to understanding the pathobiology of complex diseases which, in consequence, is crucial in devising targeted treatment options. Expression quantitative trait locus (eQTL) analysis correlates a genetic variant with the strength of gene expression, thus defining thousands of regulated genes in a multitude of human cell types and tissues. Some eQTL may not act independently of each other but instead may be regulated in a coordinated fashion by seemingly independent genetic variants. To address this issue, we combined the approaches of eQTL analysis and colocalization studies. Gene expression was determined in datasets comprising 49 tissues from the Genotype-Tissue Expression (GTEx) project. From about 33,000 regulated genes, over 14,000 were found to be co-regulated in pairs and were assembled across all tissues to almost 15,000 unique clusters containing up to nine regulated genes affected by the same eQTL signal. The distance of co-regulated eGenes was, on average, 112 kilobase pairs. Of 713 genes known to express clinical symptoms upon haploinsufficiency, 231 (32.4%) are part of at least one of the identified clusters. This calls for caution should treatment approaches aim at an upregulation of a haploinsufficient gene. In conclusion, we present an unbiased approach to identifying co-regulated genes in and across multiple tissues. Knowledge of such common effects is crucial to appreciate implications on biological pathways involved, specifically when a treatment option targets a co-regulated disease gene. MDPI 2021-09-12 /pmc/articles/PMC8470523/ /pubmed/34572044 http://dx.doi.org/10.3390/cells10092395 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Strunz, Tobias
Kellner, Martin
Kiel, Christina
Weber, Bernhard H. F.
Assigning Co-Regulated Human Genes and Regulatory Gene Clusters
title Assigning Co-Regulated Human Genes and Regulatory Gene Clusters
title_full Assigning Co-Regulated Human Genes and Regulatory Gene Clusters
title_fullStr Assigning Co-Regulated Human Genes and Regulatory Gene Clusters
title_full_unstemmed Assigning Co-Regulated Human Genes and Regulatory Gene Clusters
title_short Assigning Co-Regulated Human Genes and Regulatory Gene Clusters
title_sort assigning co-regulated human genes and regulatory gene clusters
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470523/
https://www.ncbi.nlm.nih.gov/pubmed/34572044
http://dx.doi.org/10.3390/cells10092395
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