Cargando…

Identification of deleterious and regulatory genomic variations in known asthma loci

BACKGROUND: Candidate gene and genome-wide association studies have identified hundreds of asthma risk loci. The majority of associated variants, however, are not known to have any biological function and are believed to represent markers rather than true causative mutations. We hypothesized that ma...

Descripción completa

Detalles Bibliográficos
Autores principales: Neville, Matthew D. C., Choi, Jihoon, Lieberman, Jonathan, Duan, Qing Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6292105/
https://www.ncbi.nlm.nih.gov/pubmed/30541564
http://dx.doi.org/10.1186/s12931-018-0953-2
_version_ 1783380349905010688
author Neville, Matthew D. C.
Choi, Jihoon
Lieberman, Jonathan
Duan, Qing Ling
author_facet Neville, Matthew D. C.
Choi, Jihoon
Lieberman, Jonathan
Duan, Qing Ling
author_sort Neville, Matthew D. C.
collection PubMed
description BACKGROUND: Candidate gene and genome-wide association studies have identified hundreds of asthma risk loci. The majority of associated variants, however, are not known to have any biological function and are believed to represent markers rather than true causative mutations. We hypothesized that many of these associated markers are in linkage disequilibrium (LD) with the elusive causative variants. METHODS: We compiled a comprehensive list of 449 asthma-associated variants previously reported in candidate gene and genome-wide association studies. Next, we identified all sequence variants located within the 305 unique genes using whole-genome sequencing data from the 1000 Genomes Project. Then, we calculated the LD between known asthma variants and the sequence variants within each gene. LD variants identified were then annotated to determine those that are potentially deleterious and/or functional (i.e. coding or regulatory effects on the encoded transcript or protein). RESULTS: We identified 10,130 variants in LD (r(2) > 0.6) with known asthma variants. Annotations of these LD variants revealed that several have potentially deleterious effects including frameshift, alternate splice site, stop-lost, and missense. Moreover, 24 of the LD variants have been reported to regulate gene expression as expression quantitative trait loci (eQTLs). CONCLUSIONS: This study is proof of concept that many of the genetic loci previously associated with complex diseases such as asthma are not causative but represent markers of disease, which are in LD with the elusive causative variants. We hereby report a number of potentially deleterious and regulatory variants that are in LD with the reported asthma loci. These reported LD variants could account for the original association signals with asthma and represent the true causative mutations at these loci. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12931-018-0953-2) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6292105
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-62921052018-12-17 Identification of deleterious and regulatory genomic variations in known asthma loci Neville, Matthew D. C. Choi, Jihoon Lieberman, Jonathan Duan, Qing Ling Respir Res Research BACKGROUND: Candidate gene and genome-wide association studies have identified hundreds of asthma risk loci. The majority of associated variants, however, are not known to have any biological function and are believed to represent markers rather than true causative mutations. We hypothesized that many of these associated markers are in linkage disequilibrium (LD) with the elusive causative variants. METHODS: We compiled a comprehensive list of 449 asthma-associated variants previously reported in candidate gene and genome-wide association studies. Next, we identified all sequence variants located within the 305 unique genes using whole-genome sequencing data from the 1000 Genomes Project. Then, we calculated the LD between known asthma variants and the sequence variants within each gene. LD variants identified were then annotated to determine those that are potentially deleterious and/or functional (i.e. coding or regulatory effects on the encoded transcript or protein). RESULTS: We identified 10,130 variants in LD (r(2) > 0.6) with known asthma variants. Annotations of these LD variants revealed that several have potentially deleterious effects including frameshift, alternate splice site, stop-lost, and missense. Moreover, 24 of the LD variants have been reported to regulate gene expression as expression quantitative trait loci (eQTLs). CONCLUSIONS: This study is proof of concept that many of the genetic loci previously associated with complex diseases such as asthma are not causative but represent markers of disease, which are in LD with the elusive causative variants. We hereby report a number of potentially deleterious and regulatory variants that are in LD with the reported asthma loci. These reported LD variants could account for the original association signals with asthma and represent the true causative mutations at these loci. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12931-018-0953-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-12-12 2018 /pmc/articles/PMC6292105/ /pubmed/30541564 http://dx.doi.org/10.1186/s12931-018-0953-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Neville, Matthew D. C.
Choi, Jihoon
Lieberman, Jonathan
Duan, Qing Ling
Identification of deleterious and regulatory genomic variations in known asthma loci
title Identification of deleterious and regulatory genomic variations in known asthma loci
title_full Identification of deleterious and regulatory genomic variations in known asthma loci
title_fullStr Identification of deleterious and regulatory genomic variations in known asthma loci
title_full_unstemmed Identification of deleterious and regulatory genomic variations in known asthma loci
title_short Identification of deleterious and regulatory genomic variations in known asthma loci
title_sort identification of deleterious and regulatory genomic variations in known asthma loci
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6292105/
https://www.ncbi.nlm.nih.gov/pubmed/30541564
http://dx.doi.org/10.1186/s12931-018-0953-2
work_keys_str_mv AT nevillematthewdc identificationofdeleteriousandregulatorygenomicvariationsinknownasthmaloci
AT choijihoon identificationofdeleteriousandregulatorygenomicvariationsinknownasthmaloci
AT liebermanjonathan identificationofdeleteriousandregulatorygenomicvariationsinknownasthmaloci
AT duanqingling identificationofdeleteriousandregulatorygenomicvariationsinknownasthmaloci