Computational methods for RNA modification detection from nanopore direct RNA sequencing data

The covalent modification of RNA molecules is a pervasive feature of all classes of RNAs and has fundamental roles in the regulation of several cellular processes. Mapping the location of RNA modifications transcriptome-wide is key to unveiling their role and dynamic behaviour, but technical limitations have often hampered these efforts. Nanopore direct RNA sequencing is a third-generation sequencing technology that allows the sequencing of native RNA molecules, thus providing a direct way to detect modifications at single-molecule resolution. Despite recent advances, the analysis of nanopore sequencing data for RNA modification detection is still a complex task that presents many challenges. Many works have addressed this task using different approaches, resulting in a large number of tools with different features and performances. Here we review the diverse approaches proposed so far and outline the principles underlying currently available algorithms.

Automated summary

The covalent modification of RNA molecules plays fundamental roles in cellular processes, and nanopore direct RNA sequencing technology offers a way to detect modifications at a single-molecule resolution. However, analyzing the data for RNA modification detection remains a complex task with many challenges. Various approaches have been proposed to address this issue, resulting in a diverse range of tools available.