PT  - JOURNAL ARTICLE
AU  - Araujo Tavares, Rafael de Cesaris
AU  - Mahadeshwar, Gandhar
AU  - Wan, Han
AU  - Pyle, Anna Marie
TI  - MRT-ModSeq – Rapid detection of RNA modifications with MarathonRT
AID  - 10.1101/2023.05.25.542276
DP  - 2023 Jan 01
TA  - bioRxiv
PG  - 2023.05.25.542276
4099  - http://biorxiv.org/content/early/2023/05/25/2023.05.25.542276.short
4100  - http://biorxiv.org/content/early/2023/05/25/2023.05.25.542276.full
AB  - 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.Competing Interest StatementThe authors have declared no competing interest.