Genome-wide association studies (GWAS) have identified thousands of non-coding SNPs associated with numerous human traits and diseases. However, functional interpretation of these SNPs remains a significant challenge because GWAS data do not show how these SNPs work. Our recent study established the concept of 3′ untranslated region (UTR) alternative polyadenylation (APA) quantitative trait loci (3′aQTLs), which can be used to interpret ~16.1% of GWAS SNPs and are largely distinct from eQTLs and splicing QTLs (Nature Genetics, 2021). Despite the growing interest in 3'aQTLs, there is no comprehensive database for users to search and visualize these 3′aQTLs across human normal tissues. In 3′aQTL-atlas, we will deliver, for the first time, a comprehensive list of 3′aQTLs, containing approximately 1.49 million SNPs associated with the APA of target genes, based on 15,201 RNA-seq samples across 49 human Genotype-Tissue Expression (GTEx, version 8) normal tissues isolated from 838 individuals. 3′aQTL-atlas not only provides a ~2-fold increase in sample size compared with our published study, but also includes Gene/SNP search across tissues, 3`aQTL genome browser, 3`aQTL boxplot plot, and visualization of GWAS-3`aQTL colocalization events. 3′aQTL-atlas expect to establish APA as an emerging and important molecular phenotype to explain a large fraction of GWAS risk SNPs, leading to significant novel biological insights into the genetic basis of APA and APA-linked susceptibility genes in a wide spectrum of human traits and diseases.