3′aQTL-atlas: an atlas of 3′UTR alternative polyadenylation quantitative trait loci across human normal tissues
Ya Cui, Fanglue Peng, Dan Wang, Yumei Li, Jason Sheng Li, Lei Li, Wei Li
Abstract
Genome-wide association studies (GWAS) have identified thousands of non-coding single-nucleotide polymorphisms (SNPs) associated with human traits and diseases. However, functional interpretation of these SNPs remains a significant challenge. Our recent study established the concept of 3' untranslated region (3'UTR) alternative polyadenylation (APA) quantitative trait loci (3'aQTLs), which can be used to interpret ∼16.1% of GWAS SNPs and are distinct from gene expression QTLs and splicing QTLs. Despite the growing interest in 3'aQTLs, there is no comprehensive database for users to search and visualize them across human normal tissues. In the 3'aQTL-atlas (https://wlcb.oit.uci.edu/3aQTLatlas), we provide a comprehensive list of 3'aQTLs containing ∼1.49 million SNPs associated with APA of target genes, based on 15,201 RNA-seq samples across 49 human Genotype-Tissue Expression (GTEx v8) tissues isolated from 838 individuals. The 3'aQTL-atlas provides a ∼2-fold increase in sample size compared with our published study. It also includes 3'aQTL searches by Gene/SNP across tissues, a 3'aQTL genome browser, 3'aQTL boxplots, and GWAS-3'aQTL colocalization event visualization. The 3'aQTL-atlas aims to establish APA as an emerging molecular phenotype to explain a large fraction of GWAS risk SNPs, leading to significant novel insights into the genetic basis of APA and APA-linked susceptibility genes in human traits and diseases.