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Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease

Genome-wide association studies have identified hundreds of risk loci for autoimmune disease, yet only a minority (~25%) share genetic effects with changes to gene expression (eQTLs) in immune cells. RNA-Seq based quantification at whole-gene resolution, where abundance is estimated by culminating e...

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Autores principales: Odhams, Christopher A., Cunninghame Graham, Deborah S., Vyse, Timothy J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695635/
https://www.ncbi.nlm.nih.gov/pubmed/29059182
http://dx.doi.org/10.1371/journal.pgen.1007071
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author Odhams, Christopher A.
Cunninghame Graham, Deborah S.
Vyse, Timothy J.
author_facet Odhams, Christopher A.
Cunninghame Graham, Deborah S.
Vyse, Timothy J.
author_sort Odhams, Christopher A.
collection PubMed
description Genome-wide association studies have identified hundreds of risk loci for autoimmune disease, yet only a minority (~25%) share genetic effects with changes to gene expression (eQTLs) in immune cells. RNA-Seq based quantification at whole-gene resolution, where abundance is estimated by culminating expression of all transcripts or exons of the same gene, is likely to account for this observed lack of colocalisation as subtle isoform switches and expression variation in independent exons can be concealed. We performed integrative cis-eQTL analysis using association statistics from twenty autoimmune diseases (560 independent loci) and RNA-Seq data from 373 individuals of the Geuvadis cohort profiled at gene-, isoform-, exon-, junction-, and intron-level resolution in lymphoblastoid cell lines. After stringently testing for a shared causal variant using both the Joint Likelihood Mapping and Regulatory Trait Concordance frameworks, we found that gene-level quantification significantly underestimated the number of causal cis-eQTLs. Only 5.0–5.3% of loci were found to share a causal cis-eQTL at gene-level compared to 12.9–18.4% at exon-level and 9.6–10.5% at junction-level. More than a fifth of autoimmune loci shared an underlying causal variant in a single cell type by combining all five quantification types; a marked increase over current estimates of steady-state causal cis-eQTLs. Causal cis-eQTLs detected at different quantification types localised to discrete epigenetic annotations. We applied a linear mixed-effects model to distinguish cis-eQTLs modulating all expression elements of a gene from those where the signal is only evident in a subset of elements. Exon-level analysis detected disease-associated cis-eQTLs that subtly altered transcription globally across the target gene. We dissected in detail the genetic associations of systemic lupus erythematosus and functionally annotated the candidate genes. Many of the known and novel genes were concealed at gene-level (e.g. IKZF2, TYK2, LYST). Our findings are provided as a web resource.
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spelling pubmed-56956352017-11-30 Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease Odhams, Christopher A. Cunninghame Graham, Deborah S. Vyse, Timothy J. PLoS Genet Research Article Genome-wide association studies have identified hundreds of risk loci for autoimmune disease, yet only a minority (~25%) share genetic effects with changes to gene expression (eQTLs) in immune cells. RNA-Seq based quantification at whole-gene resolution, where abundance is estimated by culminating expression of all transcripts or exons of the same gene, is likely to account for this observed lack of colocalisation as subtle isoform switches and expression variation in independent exons can be concealed. We performed integrative cis-eQTL analysis using association statistics from twenty autoimmune diseases (560 independent loci) and RNA-Seq data from 373 individuals of the Geuvadis cohort profiled at gene-, isoform-, exon-, junction-, and intron-level resolution in lymphoblastoid cell lines. After stringently testing for a shared causal variant using both the Joint Likelihood Mapping and Regulatory Trait Concordance frameworks, we found that gene-level quantification significantly underestimated the number of causal cis-eQTLs. Only 5.0–5.3% of loci were found to share a causal cis-eQTL at gene-level compared to 12.9–18.4% at exon-level and 9.6–10.5% at junction-level. More than a fifth of autoimmune loci shared an underlying causal variant in a single cell type by combining all five quantification types; a marked increase over current estimates of steady-state causal cis-eQTLs. Causal cis-eQTLs detected at different quantification types localised to discrete epigenetic annotations. We applied a linear mixed-effects model to distinguish cis-eQTLs modulating all expression elements of a gene from those where the signal is only evident in a subset of elements. Exon-level analysis detected disease-associated cis-eQTLs that subtly altered transcription globally across the target gene. We dissected in detail the genetic associations of systemic lupus erythematosus and functionally annotated the candidate genes. Many of the known and novel genes were concealed at gene-level (e.g. IKZF2, TYK2, LYST). Our findings are provided as a web resource. Public Library of Science 2017-10-23 /pmc/articles/PMC5695635/ /pubmed/29059182 http://dx.doi.org/10.1371/journal.pgen.1007071 Text en © 2017 Odhams et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Odhams, Christopher A.
Cunninghame Graham, Deborah S.
Vyse, Timothy J.
Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease
title Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease
title_full Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease
title_fullStr Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease
title_full_unstemmed Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease
title_short Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease
title_sort profiling rna-seq at multiple resolutions markedly increases the number of causal eqtls in autoimmune disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695635/
https://www.ncbi.nlm.nih.gov/pubmed/29059182
http://dx.doi.org/10.1371/journal.pgen.1007071
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