Evidence map›Paper›PMID 39819850›Full record

ArticleNature communications2025

Impact of rare non-coding variants on human diseases through alternative polyadenylation outliers.

Xudong Zou, Zhaozhao Zhao, Yu Chen, Kewei Xiong, Zeyang Wang, Shuxin Chen, Hui Chen, Gong-Hong Wei, Shuhua Xu, Wei Li and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
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

12 authors.

Xudong Zou *Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China.ORCID http://orcid.org/0000-0002-2958-0438
Zhaozhao Zhao *State Key Laboratory of Genetic Engineering, Human Phenome Institute, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai, China.
Yu Chen *State Key Laboratory of Genetic Engineering, Human Phenome Institute, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai, China.
Kewei XiongInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China.
Zeyang WangInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China.ORCID http://orcid.org/0000-0001-5735-0675
Shuxin ChenInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China.
Hui ChenInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China.
Gong-Hong WeiFudan University Shanghai Cancer Center & MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0001-6546-9334
Shuhua XuState Key Laboratory of Genetic Engineering, Human Phenome Institute, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai, China.
Wei LiDivision of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, University of California, Irvine, Irvine, CA, USA. wei.li@uci.edu.ORCID http://orcid.org/0000-0001-9931-5990
Ting NiState Key Laboratory of Genetic Engineering, Human Phenome Institute, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai, China. tingni@fudan.edu.cn.ORCID http://orcid.org/0000-0001-7007-1072
Lei LiInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China. lei.li@szbl.ac.cn.ORCID http://orcid.org/0000-0003-3924-2544

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32100533National Natural Science Foundation of China (National Science Foundation of China) 32370721
6 · The paper itself

Abstract

Although rare non-coding variants (RVs) play crucial roles in complex traits and diseases, understanding their mechanisms and identifying disease-associated RVs continue to be major challenges. Here we constructed a comprehensive atlas of alternative polyadenylation (APA) outliers (aOutliers), including 1334 3' UTR and 200 intronic aOutliers, from 15,201 samples across 49 human tissues. These aOutliers exhibit unique characteristics from transcription or splicing outliers, with a pronounced RV enrichment. Mechanistically, aOutlier-RVs alter poly(A) signals and splicing sites, and perturbation indeed triggers APA events. Furthermore, we developed a Bayesian-based APA RV prediction model, which successfully pinpointed a specific set of 1799 RVs impacting 278 genes with significantly large disease effect sizes. Notably, we observed a convergence effect between rare and common cancer variants, exemplified by regulation in the DDX18 gene. Together, this study introduced an APA-enhanced framework for genome annotation, underscoring APA's role in uncovering functional RVs linked to complex traits and diseases.

Indexed as

DiseasePolyadenylation3' Untranslated RegionsAlternative SplicingBayes TheoremDEAD-box RNA HelicasesGenetic Predisposition to DiseaseHumansIntronsNeoplasmsRNA, Messenger3' Untranslated RegionsDEAD-box RNA HelicasesRNA, Messenger

Identifiers

PMID39819850
PMCPMC11739498

What OpenQuestion holds

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Registered trials

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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.