RNA processing mechanisms govern the coding and noncoding transcriptome. Recent technological advances have enabled the simultaneous measurement of distinct RNA processing modalities, including transcript starts, ends, splicing, polyadenylation, and chemical modification, at single-molecule resolution. Our ability to effectively leverage this multi-modal single-molecule information remains hampered by a dearth of bioinformatic software to integrate and quantify relationships between various RNA processing modalities. This methodological gap limits our ability to understand the diversity and coordination between different RNA processing mechanisms across various stages of the RNA life cycle, which are only represented at substoichiometric levels in typical RNA sequencing datasets.
Here, we present R1: a new an open-source toolkit for integrating, visualising, quantifying and comparing multi-modal RNA processing datasets at single-molecule resolution. R1 integrates multiple types of single- molecule RNA data into the standard BAM file format, providing an infrastructure for studying coordinated RNA processing via existing genomics data-handling, visualisation, and statistical methods. Through this integration, R1 discovers single-molecule coordination between distinct RNA processing modalities that cannot be identified via conventional gene or transcript-level analysis. We highlight this capability by characterising substoichiometric coordination between intron-retention, m6A hypermethylation and poly(A) tail length across the human transcriptome.
Following data integration, R1 summarises, classifies and quantifies multi-modal RNA processing relationships against multiple references, including at the level of genes, transcripts, poly(A) sites, exons, and single reads. These summaries enable statistical association between multiple RNA processing modalities within a single biological condition and differential analysis of multi-modal RNA processing between multiple conditions. We demonstrate R1’s utility for differential multi-modal RNA processing analysis by characterising coordinated changes in m6A deposition, intron retention and alternative polyadenylation during acute splicing inhibition in mammalian cells. R1 enables reproducible and intuitive analysis of multi- modal RNA processing datasets.