Genetic Basis of Alternative Polyadenylation is an Emerging Molecular Phenotype for Human Traits and Diseases

Abstract

SUMMARYGenome-wide association studies have identified thousands of non-coding variants that are statistically associated with human traits and diseases. However, functional interpretation of these variants remains a major challenge. Here, we describe the first atlas of human 3’-UTR alternative polyadenylation (APA) Quantitative Trait Loci (3’QTLs), i.e. ∼0.4 million genetic variants associated with APA of target genes across 46 Genotype-Tissue Expression (GTEx) tissues from 467 individuals. APA occurs in approximately 70% of human genes and substantively impacts cellular proliferation, differentiation and tumorigenesis. Mechanistically, 3’QTLs could alter polyA motifs and RNA-binding protein binding sites, leading to thousands of APA changes. Importantly, 3’QTLs can be used to interpret ∼16.1% of trait-associated variants and are largely distinct from other QTLs such as eQTLs. The genetic basis of APA (3’QTLs) thus represent a novel molecular phenotype to explain a large fraction of non-coding variants and to provide new insights into complex traits and disease etiologies.HighlightsThe first atlas of human 3’QTLs: ∼0.4 million genetic variants associated with alternative polyadenylation of target genes across 46 tissues from 467 individuals3’QTLs could alter polyA motifs and RNA-binding protein binding sites3’QTLs can be used to interpret ∼16.1% of trait-associated variantsMany disease-associated 3’QTLs contribute to phenotype independent of gene expression

Alternative polyadenylation mediates genetic regulation of gene expression

“…For example, previous reports have suggested that variation in the polyadenylation signal site may cause variation in PAS usage. While we found that this was the case for a small number of examples, disruption of canonical signal motifs does not appear to be a major mechanism for generating apaQTLs, an observation that is also supported by a recent study on APA in GTEx data ( Figure 2—figure supplement 5 ; Li et al, 2019 ). Other possible co-transcriptional mechanisms involved in PAS choice include competition between the spliceosome and polyadenylation factors for example mediated by the spliceosomal RNA U1 ( Oh et al, 2017 ), and RNAPII pausing ( Fusby et al, 2016 ).…”

“…Yet, existing studies that examine the role of genetic variation on APA are generally characterized by two important shortcomings. Firstly, the study of inter-individual variation in PAS usage have been mostly restricted to APA in the 3’ UTRs ( Li et al, 2019 ; Yoon et al, 2012 ; Yang et al, 2020 ), leaving genetic variants that impact PAS usage in other regions, for example intronic PAS, understudied. Secondly, nearly all existing studies use standard RNA-seq to estimate PAS usage, which not only limits the accuracy of usage quantification, but also makes it difficult to disentangle the contribution of co-transcriptional mechanisms to APA regulation from post-transcriptional mechanisms such as isoform-specific decay.…”

“…To evaluate the role of APA in mediating genetic effects on gene expression and disease, we sought to identify genetic variants associated with APA on a genome-wide scale. To date, the few studies that have used genome-wide methods to identify variants associated with APA (apaQTLs) have used existing RNA-seq data to infer PAS locations and usage ( Li et al, 2019 ; Yoon et al, 2012 ; Yang et al, 2020 ; Bonder et al, 2019 ; Mariella et al, 2019 ). While using existing RNA-seq to study APA is economical, identifying PAS and estimating usage using RNA-seq are error-prone and often imprecise ( Ha et al, 2018 ).…”

Benchmarking sequencing methods and tools that facilitate the study of alternative polyadenylation

“…The use of annotations may, at times, be a drawback as certain PAS site databases might currently be missing annotation information in particular cell types or organisms of interest, biasing analyses comparing PAU across conditions. Other methods perform de novo identification of PAS sites by using a change-point model, which is based on a generalized likelihood ratio statistic of identifying transcript length changes [ 20 , 21 , 25 ] (Fig. 1 a).…”

Cell-type-specific alternative polyadenylation (APA) genes reveal the function of dynamic APA in complex tissues

“…For this step, we redesigned multiple modules of DaPars2 38 , a widely used method estimating significance of dynamic APA events in the bulk-RNA Seq data. Since it was originally designed to compare between two conditions, such as case and control 14 , we extended this module to solve the following optimization problem as follows.…”