Improved long-transcript representation in Oxford Nanopore direct RNA sequencing with UltraMarathonRT

While most RNA-seq methods sequence amplified cDNA molecules, the advent of direct RNA sequencing (DRS) empowered the scientific community to read native RNA. This technology unlocked characterization of natural RNA modifications and long RNA isoforms without the inherent biases of PCR amplification. In the library preparation prior to Oxford Nanopore (ONT) sequencing, polyadenylated RNAs are copied by a reverse transcriptase (RT) to generate an RNA-cDNA hybrid. The step aims to eliminate the secondary and tertiary structure inherent to most RNA sequences prior to presentation of the RNA strand to the pore for sequencing. The current recommended protocol for DRS utilizes Induro<sup>®</sup> RT and requires reverse transcription at 60°C. We demonstrate that these RT conditions promote hydrolysis of the RNA strand. We further show that UltraMarathonRT<sup>®</sup> (uMRT), an ultraprocessive reverse transcriptase with intrinsic helicase activity that works optimally at 30°C, can be incorporated into a new uMRT-based DRS method that results in longer RNA reads in ONT DRS and longer final isoform predictions. We optimize this reaction along with other molecular biology steps and demonstrate the performance improvements of this new workflow on the benchmark sample, Universal Human Reference RNA, along with human brain RNA. This improved DRS protocol should empower new discoveries by the scientific community.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2025-12-12
DOI
https://doi.org/10.64898/2025.12.10.693495
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improved long-transcript representation in Oxford Nanopore direct RNA sequencing with UltraMarathonRT

Jason G. Underwood, George Maio, Sara Olson, Litao Guo et al.
bioRxiv (Cold Spring Harbor Laboratory)
RNA modifications and cancer
article

Improved long-transcript representation in Oxford Nanopore direct RNA sequencing with UltraMarathonRT

Jason G. Underwood, George Maio, Sara Olson, Litao Guo, Brenton R. Graveley
article en

Abstract

While most RNA-seq methods sequence amplified cDNA molecules, the advent of direct RNA sequencing (DRS) empowered the scientific community to read native RNA. This technology unlocked characterization of natural RNA modifications and long RNA isoforms without the inherent biases of PCR amplification. In the library preparation prior to Oxford Nanopore (ONT) sequencing, polyadenylated RNAs are copied by a reverse transcriptase (RT) to generate an RNA-cDNA hybrid. The step aims to eliminate the secondary and tertiary structure inherent to most RNA sequences prior to presentation of the RNA strand to the pore for sequencing. The current recommended protocol for DRS utilizes Induro<sup>®</sup> RT and requires reverse transcription at 60°C. We demonstrate that these RT conditions promote hydrolysis of the RNA strand. We further show that UltraMarathonRT<sup>®</sup> (uMRT), an ultraprocessive reverse transcriptase with intrinsic helicase activity that works optimally at 30°C, can be incorporated into a new uMRT-based DRS method that results in longer RNA reads in ONT DRS and longer final isoform predictions. We optimize this reaction along with other molecular biology steps and demonstrate the performance improvements of this new workflow on the benchmark sample, Universal Human Reference RNA, along with human brain RNA. This improved DRS protocol should empower new discoveries by the scientific community.

bioRxiv (Cold Spring Harbor Laboratory)
Institute for Diabetes Discovery (US), UConn Health (US)
Openalex Percentile: Top 64%
RNA modifications and cancer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.