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 (), Ting Ni () and Lei Li ()
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Xudong Zou: Shenzhen Bay Laboratory
Zhaozhao Zhao: Fudan University
Yu Chen: Fudan University
Kewei Xiong: Shenzhen Bay Laboratory
Zeyang Wang: Shenzhen Bay Laboratory
Shuxin Chen: Shenzhen Bay Laboratory
Hui Chen: Shenzhen Bay Laboratory
Gong-Hong Wei: Shanghai Medical College of Fudan University
Shuhua Xu: Fudan University
Wei Li: Irvine
Ting Ni: Fudan University
Lei Li: Shenzhen Bay Laboratory

Nature Communications, 2025, vol. 16, issue 1, 1-17

Abstract: 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.

Date: 2025
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DOI: 10.1038/s41467-024-55407-3

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