A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver

Abstract Genome-wide association studies (GWAS) have identified numerous genetic variants in the human genome associated with diseases and traits. Nevertheless, for most loci the causative variant is still unknown. Expression quantitative trait loci (eQTL) in disease relevant tissues is an excellent...

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Autores principales:	Tobias Strunz, Felix Grassmann, Javier Gayán, Satu Nahkuri, Debora Souza-Costa, Cyrille Maugeais, Sascha Fauser, Everson Nogoceke, Bernhard H. F. Weber
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b28d19b30b484ab79e279b490f64c1ed
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spelling	oai:doaj.org-article:b28d19b30b484ab79e279b490f64c1ed2021-12-02T15:07:58ZA mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver10.1038/s41598-018-24219-z2045-2322https://doaj.org/article/b28d19b30b484ab79e279b490f64c1ed2018-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-24219-zhttps://doaj.org/toc/2045-2322Abstract Genome-wide association studies (GWAS) have identified numerous genetic variants in the human genome associated with diseases and traits. Nevertheless, for most loci the causative variant is still unknown. Expression quantitative trait loci (eQTL) in disease relevant tissues is an excellent approach to correlate genetic association with gene expression. While liver is the primary site of gene transcription for two pathways relevant to age-related macular degeneration (AMD), namely the complement system and cholesterol metabolism, we explored the contribution of AMD associated variants to modulate liver gene expression. We extracted publicly available data and computed the largest eQTL data set for liver tissue to date. Genotypes and expression data from all studies underwent rigorous quality control. Subsequently, Matrix eQTL was used to identify significant local eQTL. In total, liver samples from 588 individuals revealed 202,489 significant eQTL variants affecting 1,959 genes (Q-Value < 0.001). In addition, a further 101 independent eQTL signals were identified in 93 of the 1,959 eQTL genes. Importantly, our results independently reinforce the notion that high density lipoprotein metabolism plays a role in AMD pathogenesis. Taken together, our study generated a first comprehensive map reflecting the genetic regulatory landscape of gene expression in liver.Tobias StrunzFelix GrassmannJavier GayánSatu NahkuriDebora Souza-CostaCyrille MaugeaisSascha FauserEverson NogocekeBernhard H. F. WeberNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-11 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tobias Strunz Felix Grassmann Javier Gayán Satu Nahkuri Debora Souza-Costa Cyrille Maugeais Sascha Fauser Everson Nogoceke Bernhard H. F. Weber A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver
description	Abstract Genome-wide association studies (GWAS) have identified numerous genetic variants in the human genome associated with diseases and traits. Nevertheless, for most loci the causative variant is still unknown. Expression quantitative trait loci (eQTL) in disease relevant tissues is an excellent approach to correlate genetic association with gene expression. While liver is the primary site of gene transcription for two pathways relevant to age-related macular degeneration (AMD), namely the complement system and cholesterol metabolism, we explored the contribution of AMD associated variants to modulate liver gene expression. We extracted publicly available data and computed the largest eQTL data set for liver tissue to date. Genotypes and expression data from all studies underwent rigorous quality control. Subsequently, Matrix eQTL was used to identify significant local eQTL. In total, liver samples from 588 individuals revealed 202,489 significant eQTL variants affecting 1,959 genes (Q-Value < 0.001). In addition, a further 101 independent eQTL signals were identified in 93 of the 1,959 eQTL genes. Importantly, our results independently reinforce the notion that high density lipoprotein metabolism plays a role in AMD pathogenesis. Taken together, our study generated a first comprehensive map reflecting the genetic regulatory landscape of gene expression in liver.
format	article
author	Tobias Strunz Felix Grassmann Javier Gayán Satu Nahkuri Debora Souza-Costa Cyrille Maugeais Sascha Fauser Everson Nogoceke Bernhard H. F. Weber
author_facet	Tobias Strunz Felix Grassmann Javier Gayán Satu Nahkuri Debora Souza-Costa Cyrille Maugeais Sascha Fauser Everson Nogoceke Bernhard H. F. Weber
author_sort	Tobias Strunz
title	A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver
title_short	A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver
title_full	A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver
title_fullStr	A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver
title_full_unstemmed	A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver
title_sort	mega-analysis of expression quantitative trait loci (eqtl) provides insight into the regulatory architecture of gene expression variation in liver
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/b28d19b30b484ab79e279b490f64c1ed
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A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver

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