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Sequencing of mRNA from Whole Blood using Nanopore Sequencing

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Dogme: A nextflow pipeline for reprocessing nanopore RNA and DNA modifications.

Elnaz Abdollahzadeh, Ali Mortazavi

Biorxiv : the Preprint Server for Biology

|June 12, 2025

Summary

Dogme is a Nextflow workflow that automates Oxford Nanopore Technologies data processing for reproducible RNA and DNA modification detection and transcript quantification. It enables comprehensive analysis of direct RNA, cDNA, and genomic DNA sequencing data.

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Area of Science:

Genomics
Epigenomics
Bioinformatics

Background:

Oxford Nanopore Technologies (ONT) enables direct RNA and DNA modification detection from unamplified nucleic acids.
Rapid updates in ONT basecalling models and computational tools challenge reproducible analysis.
Standardized and automated workflows are needed for accurate modification detection and transcript quantification.

Purpose of the Study:

To develop Dogme, a Nextflow-based workflow for automated processing of ONT data.
To enable reproducible detection of RNA and DNA modifications and transcript quantification.
To support direct RNA (dRNA), complementary DNA (cDNA), and genomic DNA (gDNA) sequencing data.

Main Methods:

Dogme automates ONT POD5 file processing, including basecalling with Dorado and read mapping with minimap2.
Integrates modification detection using modkit for various RNA modifications (m6A, m5C, inosine, pseudouridine, Nm) and DNA methylation.
Performs full-length transcript isoform quantification using LR-Kallisto for dRNA and cDNA data.

Main Results:

Applied Dogme to mouse C2C12 myoblasts using direct RNA sequencing.
Detected thousands of RNA modification sites (m6A, m5C, inosine, pseudouridine, 2'-O-methylation) across replicates.
Demonstrated reproducible modification profiles and transcript expression levels, highlighting utility for integrative analyses.

Conclusions:

Dogme provides a robust and reproducible solution for analyzing ONT sequencing data.
Facilitates comprehensive transcriptomic and epigenomic studies using long-read sequencing.
The workflow is freely available, promoting standardization in the field.