MRT-ModSeq - Rapid Detection of RNA Modifications with MarathonRT

J Mol Biol. 2023 Nov 15;435(22):168299. doi: 10.1016/j.jmb.2023.168299. Epub 2023 Oct 4.

Abstract

Chemical modifications are essential regulatory elements that modulate the behavior and function of cellular RNAs. Despite recent advances in sequencing-based RNA modification mapping, methods combining accuracy and speed are still lacking. Here, we introduce MRT-ModSeq for rapid, simultaneous detection of multiple RNA modifications using MarathonRT. MRT-ModSeq employs distinct divalent cofactors to generate 2-D mutational profiles that are highly dependent on nucleotide identity and modification type. As a proof of concept, we use the MRT fingerprints of well-studied rRNAs to implement a general workflow for detecting RNA modifications. MRT-ModSeq rapidly detects positions of diverse modifications across a RNA transcript, enabling assignment of m1acp3Y, m1A, m3U, m7G and 2'-OMe locations through mutation-rate filtering and machine learning. m1A sites in sparsely modified targets, such as MALAT1 and PRUNE1 could also be detected. MRT-ModSeq can be trained on natural and synthetic transcripts to expedite detection of diverse RNA modification subtypes across targets of interest.

Keywords: Epitranscriptomics; RNA processing; group II reverse transcriptase; machine learning; mutational profiling.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Mutation
  • RNA Processing, Post-Transcriptional*
  • RNA, Ribosomal* / chemistry
  • RNA, Ribosomal* / genetics
  • Sequence Analysis, RNA / methods

Substances

  • RNA, Ribosomal