Nanopore signal deviations from pseudouridine modifications in RNA are sequence-specific: quantification requires...

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Chemical modifications of mRNA, such as pseudouridine (ψ), dynamically regulate gene expression in response to environmental changes.
• Nanopore direct RNA sequencing offers a method to detect ψ modifications, but current approaches lack quantitative accuracy and are sequence-context dependent.

Purpose of the Study:

• To develop a quantitative, site-specific method for measuring pseudouridine (ψ) modifications in mRNA using nanopore sequencing.
• To improve the accuracy of ψ quantification by analyzing broader sequence contexts beyond the immediate 5-nucleotide window.

Main Methods:

• Utilized direct RNA sequencing of synthetic RNAs with site-specific ψ modifications.
• Developed and applied supervised machine learning models (ModQuant) to analyze nanopore signal data.
• Investigated the sequence-dependent nature of ionic current signals for ψ classification.

Main Results:

• Achieved near-analytical, site-specific quantification of ψ modifications.
• Demonstrated that accurate ψ classification requires signal information extending beyond the conventional 5-nucleotide window.
• Successfully profiled ψ occupancy across five mRNA sites in seven human cell lines, revealing conserved and variable modification patterns.

Conclusions:

• The ModQuant pipeline provides a robust method for quantitative profiling of RNA modifications.
• Accurate pseudouridine quantification necessitates considering extended sequence contexts in nanopore signal analysis.
• This work establishes a foundation for quantitative analysis of RNA modifications using site-specifically modified RNA controls.