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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doaj-b28d19b30b484ab79e279b490f64c1ed2020-12-08T04:26:17ZengNature Publishing GroupScientific Reports2045-23222018-04-018111110.1038/s41598-018-24219-zA mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liverTobias Strunz0Felix Grassmann1Javier Gayán2Satu Nahkuri3Debora Souza-Costa4Cyrille Maugeais5Sascha Fauser6Everson Nogoceke7Bernhard H. F. Weber8Roche Innovation Center Basel, F. Hoffmann-La Roche LtdInstitute of Human Genetics, University of RegensburgRoche Innovation Center Basel, F. Hoffmann-La Roche LtdRoche Innovation Center Basel, F. Hoffmann-La Roche LtdRoche Innovation Center Basel, F. Hoffmann-La Roche LtdRoche Innovation Center Basel, F. Hoffmann-La Roche LtdRoche Innovation Center Basel, F. Hoffmann-La Roche LtdRoche Innovation Center Basel, F. Hoffmann-La Roche LtdInstitute of Human Genetics, University of RegensburgAbstract 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.https://doi.org/10.1038/s41598-018-24219-z |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tobias Strunz Felix Grassmann Javier Gayán Satu Nahkuri Debora Souza-Costa Cyrille Maugeais Sascha Fauser Everson Nogoceke Bernhard H. F. Weber |
spellingShingle |
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 Scientific Reports |
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 Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2018-04-01 |
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. |
url |
https://doi.org/10.1038/s41598-018-24219-z |
work_keys_str_mv |
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