期刊
NUCLEIC ACIDS RESEARCH
卷 50, 期 D1, 页码 D39-D45出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab740
关键词
-
资金
- Common Fund of theOffice of the Director of the National Institutes of Health
- NCI
- NHGRI
- NHLBI
- NIDA
- NIMH
- NINDS
- National Institutes of Health [R01CA193466]
Genome-wide association studies have identified numerous non-coding SNPs associated with human traits and diseases, with functional interpretation remaining a challenge. The concept of 3'UTR alternative polyadenylation (APA) quantitative trait loci (3'aQTLs) has been established to interpret a portion of GWAS SNPs. The 3'aQTL-atlas provides a comprehensive database of nearly 1.49 million SNPs associated with APA across 49 human tissues, aiming to explain genetic basis of APA and APA-linked susceptibility genes in human traits and diseases.
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 similar to 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 similar to 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 similar to 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.
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