Evidence map›Paper›PMID 36043442›Full record

ArticleNucleic acids research2023

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

Xuelian Ma, Shumin Cheng, Ruofan Ding, Zhaozhao Zhao, XuDong Zou, Shouhong Guang, Qixuan Wang, Huan Jing, Chen Yu, Ting Ni and 1 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Xuelian MaInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.
Shumin ChengInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.
Ruofan DingInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.
Zhaozhao ZhaoState Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai 200438, China.
XuDong ZouInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.ORCID 0000-0002-2958-0438
Shouhong GuangMinistry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, School of Life Sciences, Department of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Biomedical Sciences and Health Laboratory of Anhui Province, University of Science and Technology of China, Hefei, Anhui 230027, P.R. China.ORCID 0000-0001-7700-9634
Qixuan WangInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.
Huan JingDepartment of Stomatology, Peking University Shenzhen Hospital, Shenzhen 518036, China.
Chen YuInstitute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen 518055, China.
Ting NiState Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai 200438, China.ORCID 0000-0001-7007-1072
Lei LiInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.ORCID 0000-0003-3924-2544

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

IntronsPolyadenylationQuantitative Trait Loci3' Untranslated RegionsAtlases as TopicGene Expression ProfilingHumans3' Untranslated Regions

Identifiers

PMID36043442
PMCPMC9825496

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.