Open AccessPopulation‐scale genetic control of alternative polyadenylation and its association with human diseases
Author(s) -
Li Lei,
Li Yumei,
Zou Xudong,
Peng Fuduan,
Cui Ya,
Wagner Eric J.,
Li Wei
Publication year - 2022
Publication title -
quantitative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.707
H-Index - 15
eISSN - 2095-4697
pISSN - 2095-4689
DOI - 10.15302/j-qb-021-0252
Subject(s) - biology , genome wide association study , genetics , computational biology , genetic association , polyadenylation , phenotype , human genome , genomics , population , gene , genome , single nucleotide polymorphism , rna , genotype , medicine , environmental health
Background Genome‐wide association studies (GWAS) have identified thousands of genomic non‐coding variants statistically associated with many human traits and diseases, including cancer. However, the functional interpretation of these non‐coding variants remains a significant challenge in the post‐GWAS era. Alternative polyadenylation (APA) plays an essential role in post‐transcriptional regulation for most human genes. By employing different poly(A) sites, genes can either shorten or extend the 3′‐UTRs that contain cis ‐regulatory elements such as miRNAs or RNA‐binding protein binding sites. Therefore, APA can affect the mRNA stability, translation, and cellular localization of proteins. Population‐scale studies have revealed many inherited genetic variants that potentially impact APA to further influence disease susceptibility and phenotypic diversity, but systematic computational investigations to delineate the connections are in their earliest states. Results Here, we discuss the evolving definitions of the genetic basis of APA and the modern genomics tools to identify, characterize, and validate the genetic influences of APA events in human populations. We also explore the emerging and surprisingly complex molecular mechanisms that regulate APA and summarize the genetic control of APA that is associated with complex human diseases and traits. Conclusion APA is an intermediate molecular phenotype that can translate human common non‐coding variants to individual phenotypic variability and disease susceptibility.