MRT-ModSeq - Rapid detection of RNA modifications with MarathonRT.

Area of Science:

• Molecular Biology
• Genomics
• Biochemistry

Background:

• Chemical modifications regulate RNA function, but accurate and rapid mapping methods are needed.
• Existing sequencing-based methods lack a combination of speed and precision for comprehensive RNA modification analysis.

Approach:

• Introduced MRT-ModSeq, a rapid method for simultaneous detection of multiple RNA modifications using MarathonRT.
• Utilized distinct divalent cofactors to generate 2-D mutational profiles sensitive to nucleotide identity and modification type.
• Developed a general workflow using MRT fingerprints for RNA modification detection, including mutation-rate filtering and machine learning.

Key Points:

• MRT-ModSeq rapidly detects diverse modifications across RNA transcripts, assigning locations for m1acp3Y, m1A, m3U, m7G, and 2'-OMe.
• Successfully detected m1A sites in sparsely modified targets like MALAT1 and PRUNE1.
• The method is adaptable and can be trained on natural and synthetic transcripts for various RNA modification subtypes.

Conclusions:

• MRT-ModSeq provides a fast and accurate solution for mapping multiple RNA modifications simultaneously.
• This technique enhances the study of RNA regulation and function by enabling precise identification of diverse modifications.
• The platform's trainability offers broad applicability for future RNA modification research across different targets.