Background: A-to-I RNA editing diversifies the transcriptome and has multiple downstream functional effects. Genetic variation contributes to RNA editing variability between individuals and has the potential to impact phenotypic variability.
Results: We analyze matched genetic and transcriptomic data in 49 tissues across 437 individuals to identify RNA editing events that are associated with genetic variation. Using an RNA editing quantitative trait loci (edQTL) mapping approach, we identify 3117 unique RNA editing events associated with a cis genetic polymorphism. Fourteen percent of these edQTL events are also associated with genetic variation in their gene expression. A subset of these events are associated with genome-wide association study signals of complex traits or diseases. We determine that tissue-specific levels of ADAR and ADARB1 are able to explain a subset of tissue-specific edQTL events. We find that certain microRNAs are able to differentiate between the edited and unedited isoforms of their targets. Furthermore, microRNAs can generate an expression quantitative trait loci (eQTL) signal from an edQTL locus by microRNA-mediated transcript degradation in an editing-specific manner. By integrative analyses of edQTL, eQTL, and microRNA expression profiles, we computationally discover and experimentally validate edQTL-microRNA pairs for which the microRNA may generate an eQTL signal from an edQTL locus in a tissue-specific manner.
Conclusions: Our work suggests a mechanism in which RNA editing variability can influence the phenotypes of complex traits and diseases by altering the stability and steady-state level of critical RNA molecules.
Keywords: A-to-I RNA editing; Allele-specific RNA editing; GWAS; Genetic variation; RNA editing quantitative trait loci; RNA-seq; Single-nucleotide polymorphism; Transcript stability; Transcriptome; microRNA.