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AhR Gene Expression in Immune cell subtypes

Authors: Rutkovsky, Alexandria C;

AhR Gene Expression in Immune cell subtypes

Abstract

Benjamin J. Schmiedel, Divya Singh, Ariel Madrigal, Alan G. Valdovino-Gonzalez, Brandie M. White, Jose Zapardiel-Gonzalo, Brendan Ha, Gokmen Altay, Jason A. Greenbaum, Graham McVicker, Grégory Seumois, Anjana Rao, Mitchell Kronenberg, Bjoern Peters, Pandurangan Vijayanand, Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression, Cell, Volume 175, Issue 6, 2018, Pages 1701-1715.e16, ISSN 0092-8674, https://doi.org/10.1016/j.cell.2018.10.022. (http://www.sciencedirect.com/science/article/pii/S009286741831331X) Abstract: Summary While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (database of immune cell expression, expression quantitative trait loci [eQTLs], and epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (https://dice-database.org). Keywords: DICE; immunology; GWAS; genetic variants; human immune cells; gene expression; eGenes; eQTLs; sex https://dice-database.org/genes/ahr#boxplot

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DICE, AhR

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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