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ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues

Functional interpretation of disease-associated non-coding variants remains a significant challenge in the post-GWAS era. Our recent study has identified 3′UTR alternative polyadenylation (APA) quantitative trait loci (3′aQTLs) and connects APA events with QTLs as a major driver of human traits and...

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Autores principales: Ma, Xuelian, Cheng, Shumin, Ding, Ruofan, Zhao, Zhaozhao, Zou, XuDong, Guang, Shouhong, Wang, Qixuan, Jing, Huan, Yu, Chen, Ni, Ting, Li, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825496/
https://www.ncbi.nlm.nih.gov/pubmed/36043442
http://dx.doi.org/10.1093/nar/gkac736
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author Ma, Xuelian
Cheng, Shumin
Ding, Ruofan
Zhao, Zhaozhao
Zou, XuDong
Guang, Shouhong
Wang, Qixuan
Jing, Huan
Yu, Chen
Ni, Ting
Li, Lei
author_facet Ma, Xuelian
Cheng, Shumin
Ding, Ruofan
Zhao, Zhaozhao
Zou, XuDong
Guang, Shouhong
Wang, Qixuan
Jing, Huan
Yu, Chen
Ni, Ting
Li, Lei
author_sort Ma, Xuelian
collection PubMed
description Functional interpretation of disease-associated non-coding variants remains a significant challenge in the post-GWAS era. Our recent study has identified 3′UTR alternative polyadenylation (APA) quantitative trait loci (3′aQTLs) and connects APA events with QTLs as a major driver of human traits and diseases. Besides 3′UTR, APA events can also occur in intron regions, and increasing evidence has connected intronic polyadenylation with disease risk. However, systematic investigation of the roles of intronic polyadenylation in human diseases remained challenging due to the lack of a comprehensive database across a variety of human tissues. Here, we developed ipaQTL-atlas (http://bioinfo.szbl.ac.cn/ipaQTL) as the first comprehensive portal for intronic polyadenylation. The ipaQTL-atlas is based on the analysis of 15 170 RNA-seq data from 838 individuals across 49 Genotype-Tissue Expression (GTEx v8) tissues and contains ∼0.98 million SNPs associated with intronic APA events. It provides an interface for ipaQTLs search, genome browser, boxplots, and data download, as well as the visualization of GWAS and ipaQTL colocalization results. ipaQTL-atlas provides a one-stop portal to access intronic polyadenylation information and could significantly advance the discovery of APA-associated disease susceptibility genes.
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spelling pubmed-98254962023-01-10 ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues Ma, Xuelian Cheng, Shumin Ding, Ruofan Zhao, Zhaozhao Zou, XuDong Guang, Shouhong Wang, Qixuan Jing, Huan Yu, Chen Ni, Ting Li, Lei Nucleic Acids Res Database Issue Functional interpretation of disease-associated non-coding variants remains a significant challenge in the post-GWAS era. Our recent study has identified 3′UTR alternative polyadenylation (APA) quantitative trait loci (3′aQTLs) and connects APA events with QTLs as a major driver of human traits and diseases. Besides 3′UTR, APA events can also occur in intron regions, and increasing evidence has connected intronic polyadenylation with disease risk. However, systematic investigation of the roles of intronic polyadenylation in human diseases remained challenging due to the lack of a comprehensive database across a variety of human tissues. Here, we developed ipaQTL-atlas (http://bioinfo.szbl.ac.cn/ipaQTL) as the first comprehensive portal for intronic polyadenylation. The ipaQTL-atlas is based on the analysis of 15 170 RNA-seq data from 838 individuals across 49 Genotype-Tissue Expression (GTEx v8) tissues and contains ∼0.98 million SNPs associated with intronic APA events. It provides an interface for ipaQTLs search, genome browser, boxplots, and data download, as well as the visualization of GWAS and ipaQTL colocalization results. ipaQTL-atlas provides a one-stop portal to access intronic polyadenylation information and could significantly advance the discovery of APA-associated disease susceptibility genes. Oxford University Press 2022-08-31 /pmc/articles/PMC9825496/ /pubmed/36043442 http://dx.doi.org/10.1093/nar/gkac736 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Ma, Xuelian
Cheng, Shumin
Ding, Ruofan
Zhao, Zhaozhao
Zou, XuDong
Guang, Shouhong
Wang, Qixuan
Jing, Huan
Yu, Chen
Ni, Ting
Li, Lei
ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues
title ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues
title_full ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues
title_fullStr ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues
title_full_unstemmed ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues
title_short ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues
title_sort ipaqtl-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825496/
https://www.ncbi.nlm.nih.gov/pubmed/36043442
http://dx.doi.org/10.1093/nar/gkac736
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