Abstract
An intricate network of cis- and trans-elements acts on RNA N (6)-methyladenosine (m(6)A), which in turn may affect gene expression and, ultimately, human health. A complete understanding of this network requires new approaches to accurately measure the subtle m(6)A differences arising from genetic variants, many of which have been associated with common diseases. To address this gap, we developed a method to accurately and sensitively detect transcriptome-wide allele-specific m(6)A (ASm(6)A) from MeRIP-seq data and applied it to uncover 12,056 high-confidence ASm(6)A modifications from 25 human tissues. We also identified 1184 putative functional variants for ASm(6)A regulation, a subset of which we experimentally validated. Importantly, we found that many of these ASm(6)A-associated genetic variants were enriched for common disease-associated and complex trait-associated risk loci, and verified that two disease risk variants can change m(6)A modification status. Together, this work provides a tool to detangle the dynamic network of RNA modifications at the allelic level and highlights the interplay of m(6)A and genetics in human health and disease.