Discover Native tRNA Profiles with High-Resolution Nano tRNA Sequencing

tRNAs are some of the most heavily modified molecules in the cell, making them difficult to analyse with standard sequencing methods. CD Genomics' nano tRNA sequencing service uses ONT direct tRNA sequencing to capture full-length, native tRNA molecules, providing accurate tRNAome profiling, modification-aware analysis, and quantitative abundance measurements in a single workflow.

Our service helps research, biotech, and pharma teams address long-standing challenges in tRNA biology, including the inability to detect modification patterns, isoacceptor usage, or native structural features with traditional NGS. By sequencing tRNAs directly—without cDNA synthesis or PCR—we retain native chemical modifications and reveal molecular signatures that drive translational control.

Why researchers choose our tRNA sequencing service

• Full-length native tRNA sequencing
• Direct detection of tRNA modifications
• High-resolution tRNAome profiling
• Quantitative tRNA abundance and isoacceptor analysis
• Powered by ONT direct tRNA sequencing for modification-aware insights

At a glance:

• Introduction
• What is Nano tRNA Sequencing?
• Key Advantages of Our Nano tRNA Sequencing Service
• Applications of Nano tRNA Sequencing
• Technology Overview – How Nano tRNA Sequencing Works
• Bioinformatics Analysis
• Choosing the Right Platform for tRNA Analysis
• Sample Requirements for Nano tRNA Sequencing
• Why Choose CD Genomics
• Case Study: Quantitative Analysis of Native tRNA Modifications Using Nanopore Sequencing
• FAQs
• Demo

Introduction

tRNAs play a central role in protein synthesis, yet they remain one of the most challenging RNA classes to analyse. Their short length, strong secondary structures, and dense chemical modifications make them challenging to sequence with traditional RNA-seq or mass-spectrometry approaches. These limitations prevent many teams from understanding how tRNA abundance, isoacceptor usage, and modification patterns shape translation efficiency across cells, tissues, or disease models.

What is Nano tRNA Sequencing?

Nano tRNA sequencing is a specialised approach that uses Oxford Nanopore's direct RNA technology to read full-length, native tRNA molecules without cDNA synthesis or PCR. This capability is critical because tRNAs carry more than 150 known chemical modifications, many of which are lost, altered, or masked during reverse transcription in conventional RNA-seq.

In nano tRNA sequencing, individual tRNAs pass through a nanopore, generating electrical signals that reflect both their nucleotide sequence and their modification status. These signals allow researchers to quantify tRNA abundance, distinguish isoacceptors, and identify modification signatures across the tRNAome. Because this method captures each molecule directly, it retains the native biochemical information required for epitranscriptomic studies.

Nano tRNA sequencing is particularly valuable for projects exploring translation dynamics, stress adaptation, metabolic regulation, or drug-response mechanisms where both tRNA expression and modification states influence protein synthesis. For readers interested in nanopore-based RNA chemistry, our Nanopore Direct RNA Sequencing page provides further detail on signal interpretation and model-based modification calling.

Key Advantages of Our Nano tRNA Sequencing Service

Applications of Nano tRNA Sequencing

tRNAome Profiling Across Conditions

• Quantify global tRNA abundance and isoacceptor usage.
• Compare tRNA pools across cell types, stress states, developmental stages, or experimental treatments.
• Investigate codon–anticodon balance and translational efficiency.

Mapping tRNA Modifications

• Detect modification signatures such as Ψ, m¹A, m⁷G, i⁶A, and U34 variants from nanopore signal patterns.
• Study how modification networks respond to nutrient changes, metabolic stress, or pathway perturbation.
• Characterise modification-linked defects in genetic models.

Translation Dynamics and Adaptive Responses

• Explore how tRNA availability influences ribosome speed, decoding accuracy, and protein output.
• Analyse shifts in the tRNAome during stress adaptation, metabolic rewiring, or environmental changes.
• Identify tRNA-based regulatory pathways relevant to non-clinical research.

Drug Mechanism and Toxicology (Research Use Only)

• Profile tRNA changes in response to compounds that target translation, mitochondria, stress signalling, or RNA metabolism.
• Reveal modification-associated responses linked to compound exposure or toxicity.
• Integrate tRNA-level insights with transcriptomic or metabolomic datasets.

Cross-Species and Comparative Studies

• Suitable for bacteria, yeast, plants, model animals, and human-derived samples.
• Enables comparative analysis of tRNA evolution, decoding bias, and modification conservation.

Optional Extension: Ribo-tRNA Sequencing

• Combine nano tRNA sequencing with ribosome pulldown to investigate ribosome-associated tRNAs and decoding events in actively translating ribosomes.
• Useful for studies of translation initiation, elongation dynamics, and ribosome pausing.

Technology Overview – How Nano tRNA Sequencing Works

1. Small RNA Enrichment

tRNAs represent a small fraction of total RNA. We begin by isolating the small RNA population to enhance the proportion of tRNA molecules in the sample. This improves sequencing depth, reduces background noise, and increases the sensitivity of isoacceptor quantification.

2. tRNA Deacylation and Adapter Ligation

Native tRNAs contain aminoacylation at their 3′ ends. These chemical groups interfere with adapter ligation and must be removed. Controlled deacylation exposes the 3′ hydroxyl group, enabling efficient and specific adaptor attachment. Barcoding options support multi-sample or multi-condition studies.

3. Nanopore Direct RNA Sequencing

During sequencing, individual tRNA molecules pass through a nanopore channel embedded in a membrane. Each nucleotide—and its chemical modifications—produces distinct electrical current signatures. This enables:

• Full-length sequencing without reverse transcription
• Detection of modification-induced current shifts
• Separation of closely related isoacceptors
• Single-molecule analysis for rare species

Because nanopore sequencing captures native RNA structure, it is well suited for modification-rich tRNAs that conventional RNA-seq cannot accurately resolve.

4. tRNAome-Focused Bioinformatics

The resulting signal and sequence data are processed through tRNA-optimised computational tools. These specialised algorithms improve read mapping, detect modification signatures, and quantify isoacceptor abundance with higher confidence than general RNA-seq pipelines. Together, these steps produce a complete molecular profile of the tRNAome.

Workflow of nano tRNA sequencing, integrating small RNA enrichment, tRNA preparation, nanopore-based direct RNA sequencing, and tRNAome-focused bioinformatics.

Bioinformatics Analysis

Choosing the Right Platform for tRNA Analysis

Different analytical technologies reveal different aspects of tRNA biology. The table below compares nano tRNA sequencing, Illumina RNA-seq, and LC–MS/MS, helping research teams select the most suitable method for their study design.

At CD Genomics, we provide all three platforms—ONT direct RNA sequencing, Illumina RNA-seq, and LC–MS/MS—allowing clients to combine tools or build integrated workflows for deeper insight.

RNA Sequencing Platform Comparison

How to interpret this comparison

• Use nano tRNA sequencing when the goal is to study translational regulation, modification networks, or isoacceptor-level biology.
• Use Illumina RNA-seq when profiling the transcriptome broadly (mRNAs, lncRNAs, small RNAs other than tRNA).
• Use LC–MS/MS when the chemical identity of a modification is needed but positional mapping is not required.

Because CD Genomics supports ONT, Illumina, and LC–MS/MS platforms, clients can build integrated research strategies—for example, combining nano tRNA sequencing with RNA-seq for transcriptome context or LC–MS/MS for chemical confirmation.

Sample Requirements for Nano tRNA Sequencing

Why Choose CD Genomics

Expertise in tRNA Biology

Skilled in nano tRNA sequencing, short RNA processing, and nanopore signal analysis.

Multi-Platform Integration

Supports ONT, Illumina RNA-seq, and LC–MS/MS for combined multi-layer datasets.

Custom Bioinformatics

Offers basic and advanced analysis for mapping, modification detection, and comparative tRNAome studies.

High Quality & Reproducibility

Rigorous QC ensures accurate data, minimal artefacts, and preservation of native tRNA modifications.

End-to-End Scientific Support

Works with research, biotech, and pharma teams to design and interpret translation-focused studies.

Case Study: Quantitative Analysis of Native tRNA Modifications Using Nanopore Sequencing

Lucas, M.C., Pryszcz, L.P., Medina, R. et al. Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing. Nature Biotechnology42, 72–86 (2024).

1. Background

tRNAs carry a dense network of chemical modifications that regulate their folding, decoding activity, and stability. Until recently, researchers relied on indirect methods—such as mass spectrometry or cDNA-based RNA-seq—to infer these marks. These approaches either lacked positional information or erased modifications during reverse transcription.

This study tested whether Oxford Nanopore's direct RNA sequencing could deliver a unified view of tRNA abundance, isoacceptor usage, and modification signatures within a single experiment.

This work provides one of the strongest proof-of-concept demonstrations for native tRNA sequencing, offering insights now routinely leveraged in our nano tRNA sequencing service.

2. Methods

Native tRNAs were extracted from Schizosaccharomyces pombe (wild-type and enzyme-knockout strains). The workflow included:

• tRNA deacylation & adapter ligation to linearise tRNAs for sequencing
• ONT direct RNA sequencing to preserve native modifications
• Dorado basecalling models (Ψ, m⁶A, m⁵C, inosine)
• Both on-label (Ψ model detecting Ψ) and off-label (Ψ model detecting other U-modifications) strategies
• Orthogonal validation using JACUSA2 to compare WT and knockout-induced basecalling errors

This approach allowed the authors to characterise modification probabilities and assign modification sites to specific enzymes.

3. Results

The authors demonstrated that nanopore sequencing can distinguish modified from unmodified tRNA positions with high confidence. Using the Ψ model, they visualised clear probability peaks at known pseudouridine sites, while knockout strains displayed corresponding signal loss.

Nanopore-derived probability distribution for Ψ55 in native tRNAs, showing a strong high-probability peak consistent with known pseudouridine modification.

Key Findings

• High-resolution modification detection:
• ONT signals generated near-binary Ψ probabilities at validated sites.
• Novel modification discovery:
• Two previously unreported pseudouridine sites—Ψ8 (Pus7-dependent) and Ψ22 (Pus1-dependent)—were identified.
• Multi-modification mapping:
• Off-label use of the Ψ model detected U34 variants and m⁷G46 by analysing KL-divergence patterns.
• Enzyme-modification networks:
• Integration of knockout data revealed cross-talk, such as Ψ55 influencing m¹A58 formation.
• Accurate tRNA quantification:
• tRNA abundance values matched orthogonal measurements, confirming quantitative reliability.

4. Conclusions

This study confirms that nanopore direct RNA sequencing is a powerful single-molecule approach for analysing both tRNA abundance and modification landscapes. Importantly:

• Native modifications remain intact
• Modification probabilities correlate with known enzymatic dependencies
• Novel tRNA modifications can be identified
• Single-nucleotide resolution is achievable across the tRNAome
• Quantification is reproducible across replicates and conditions

FAQs

Demo

1. tRNA Abundance Bar Plot (Isoacceptor Profiling)

2. Modification Probability Heatmap

3. Nanopore Signal Trace (Squiggle Plot) for Modification Detection

Poly(A) Tail Length Analysis

Full-Length Transcript Sequencing (Iso-Seq)

Nanopore Direct RNA Sequencing

Nanopore Full-Length cDNA Sequencing

Nanopore Ribosome tRNA Sequencing