Abstract The significance of RNA modification in gene regulation has been widely recognized. To understand the transcriptome-wide landscape and its underlying mechanisms, prevailing mapping strategies have been developed. However, these short-reads based techniques are primarily focused at the gene level, overlooking the nature of RNA as multiple copies within one cell. Third-generation sequencing (TGS) platforms provide direct RNA sequencing at the resolution of individual RNA molecules, offering the promise of detecting RNA modifications and RNA processing events simultaneously. In this study, we introduce SingleMod, a deep learning model tailored for the precise mapping of m6A modifications within single RNA molecules using nanopore direct RNA sequencing (DRS). We systematically dissect the transcriptome-wide m6A profiles in single-molecule and single-base resolution, refining our understanding of the genomics of m6A and revealing an additive mode through which m6A shapes the epitranscriptome. Through comparative analyses across diverse species, we identify three distinct m6A distribution patterns and unveil an exclusion-inclusion deposition mode that governs m6A biogenesis. Furthermore, we introduce a unified quantitative model that delineates this dual-mode in various species. This study pioneers single-molecule m6A landscape exploration across multiple species, deepening our understanding of m6A, including its genomics, biogenesis, mechanisms, and biological implications.
