Welcome to ipaQTL Atlas!


Genome-wide association studies (GWAS) have identified thousands of genomic non-coding variants statistically associated with many human complex traits and diseases. However, functional interpretation of these non-coding variants remains a significant challenge in the post-GWAS era. Our recent study has identified alternative polyadenylation (APA) quantitative trait loci (3′aQTLs) as an emerging molecular QTL for human disease. APA events can also occur in the intron region, and the increasing interest in genetic variants can affect disease risk through intronic polyadenylation. However, there is no comprehensive database for users to search and visualize them across human tissues. Here, we developed a comprehensive database, intronic apaQTLs atlas, as the first comprehensive portal for intronic polyadenylation, based on 15,170 sets of RNA-seq data from 838 individuals across 49 Genotype-Tissue Expression (GTEx v8) tissues. The intronic apaQTLs atlas contains ~0.98 million SNPs associated with intronic APA of target genes based on hg38 genome. It includes the intronic apaQTLs search, genome browser, and download. The users can also visualize the colocalization result based on the GWAS dataset of their interest. Intronic apaQTLs atlas provides a one-stop portal for intronic polyadenylation and could significantly advance the discovery of APA-associated disease susceptibility genes.





Reference

If you use the ipaQTLs in this wetsite, please cite the following papers:

ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues

Xuelian Ma1, Shumin Cheng1, Ruofan Ding, Zhaozhao Zhao, Xudong Zou, Shouhong Guang, Qixuan Wang, Huan Jing, Chen Yu, Ting Ni, Lei Li1* (Nucleic Acids Research, 2022).

An atlas of alternative polyadenylation quantitative trait loci contributing to complex trait and disease heritability

Lei Li# 1, Kai-Lieh Huang# 2, ..., Eric J. Wagner2,*, and Wei Li1,* (Nature Genetics, 2021).

If you have any further questions or comments, please don't hesitate to contact us.

Lei Li (Lab website):
lei.li@szbl.ac.cn
Institute of Systems and Physical Biology ,Shenzhen Bay Laboratory, China.