RNA modifications detection by comparative Nanopore direct RNA sequencing

Nanopore direct RNA Sequencing data contain information about the presence of RNA modifications, but their detection poses substantial challenges. Here the authors introduce Nanocompore, a new methodology for modification detection from Nanopore data. RNA molecules undergo a vast array of chemical post-transcriptional modifications (PTMs) that can affect their structure and interaction properties. In recent years, a growing number of PTMs have been successfully mapped to the transcriptome using experimental approaches relying on high-throughput sequencing. Oxford Nanopore direct-RNA sequencing has been shown to be sensitive to RNA modifications. We developed and validated Nanocompore, a robust analytical framework that identifies modifications from these data. Our strategy compares an RNA sample of interest against a non-modified control sample, not requiring a training set and allowing the use of replicates. We show that Nanocompore can detect different RNA modifications with position accuracy in vitro, and we apply it to profile m(6)A in vivo in yeast and human RNAs, as well as in targeted non-coding RNAs. We confirm our results with orthogonal methods and provide novel insights on the co-occurrence of multiple modified residues on individual RNA molecules.

Automated summary

Nanocompore is a new methodology for modification detection from Nanopore data, utilizing comparison between RNA samples of interest and non-modified control samples to identify modifications with positional accuracy in vitro and applicable to human and yeast RNA research.