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Ribosome-associated tRNAs provide the most direct view of decoding events, translational control, and cellular adaptation. Yet conventional Ribo-seq and RNA-seq cannot capture full-length tRNAs, let alone their dense modification patterns or isoacceptor diversity. CD Genomics' Nanopore Ribosome tRNAseq service integrates ribosome-associated RNA enrichment with ONT direct tRNA sequencing, enabling researchers to sequence native, full-length, modification-rich tRNAs that are actively engaged in translation.
This service helps research teams overcome long-standing challenges in translation biology—including the inability to measure ribosome-level tRNA usage, decoding preferences, or stress-responsive tRNA modifications using traditional approaches.

At a glance:
Understanding how tRNAs function inside actively translating ribosomes is essential for decoding translational control. However, most technologies measure only total tRNA pools, missing the ribosome-bound fraction that truly reflects decoding events. CD Genomics' Nanopore Ribosome tRNA-Seq service fills this gap by combining selective ribosome enrichment with ONT direct tRNA sequencing, enabling full-length, native-state analysis of tRNAs captured directly from the translation machinery.
Our platform profiles the quantity, identity, and modification signatures of ribosome-associated tRNAs, generating molecular insights that conventional Ribo-seq, RNA-seq, or LC–MS/MS approaches cannot provide. This service is designed for research teams studying translation dynamics, stress responses, codon–anticodon regulation, tRNA modification biology, and drug-response mechanisms (research use only).
To support broad research needs, we also offer complementary Nanopore Direct RNA Sequencing and Nano tRNA Sequencing services. These related workflows allow clients to integrate ribosome-level decoding information with total tRNA pools and transcriptome-level context for deeper mechanistic interpretation.
Nanopore Ribosome tRNA-Seq is an advanced profiling strategy that captures ribosome-bound tRNAs and sequences them in their native, full-length form using Oxford Nanopore Technologies (ONT) direct RNA sequencing. Unlike conventional tRNA-seq, which measures only the total cellular pool, this method focuses specifically on tRNAs actively participating in translation—those positioned in the A, P, and E sites of translating ribosomes.
The workflow enriches ribosomes from cell lysates, isolates the associated tRNAs, and directly sequences them without reverse transcription or PCR. Because ONT reads each tRNA molecule as it passes through a nanopore, the method preserves natural chemical modifications and structural signatures—critical features that determine decoding accuracy, elongation speed, and translational response to stress.
By integrating ribosome purification with nano tRNA sequencing, this approach provides a high-resolution view of:
Nanopore Ribosome tRNA-Seq is particularly valuable for teams investigating translation control, adaptive responses, and epitranscriptomic regulation, complementing traditional Ribo-seq and our Nano tRNA Sequencing service to deliver a more complete understanding of the translational landscape.
Captures only the tRNAs positioned in the ribosome A/P/E sites, offering a real-time view of decoding events and translation dynamics.
ONT direct RNA sequencing preserves natural tRNA modifications—critical for decoding accuracy—enabling modification-aware interpretation at single-molecule resolution.
Reveals isoacceptor usage, decoding preferences, and ribosome-specific tRNA recruitment patterns that cannot be inferred from total tRNA pools.
Ribosome-associated tRNAs shift rapidly during environmental or chemical challenges, enabling the method to function as a sensitive biosensor of translational state.
Provides a functional layer that bridges mRNA codons (Ribo-seq) and native tRNA molecules (nano tRNA-seq), enabling integrated translation research.
Profile ribosome-associated tRNAs to understand elongation speed, decoding preferences, codon–anticodon matching, and ribosome pausing events.
Monitor rapid shifts in ribosome-bound tRNAs under heat shock, oxidative stress, nutrient limitation, or metabolic rewiring to uncover regulatory pathways.
Evaluate how small molecules targeting translation, mitochondria, stress pathways, or RNA metabolism alter the ribosome-associated tRNA repertoire.
Study how tRNA modification states influence ribosome recruitment and identify modification-dependent regulatory signatures.
Suitable for any organism—microbial, plant, or mammalian—enabling comparative investigation of decoding systems and translational adaptation.
Combine with Ribo-seq, nano tRNA sequencing, or Nanopore Direct RNA Sequencing for multi-layered analysis of mRNA codons, tRNA anticodons, and native modification signatures.
Cells are rapidly processed under conditions that maintain tRNA positioning within the ribosome's A/P/E sites, ensuring an accurate snapshot of active translation.
Purification steps isolate monosomes while removing unbound RNAs, yielding a clean population of ribosome-associated tRNAs.
tRNAs engaged in translation are selectively recovered from the enriched ribosomes, forming a functional tRNA pool distinct from total tRNA extracts.
Recovered tRNAs are adapted for ONT direct RNA sequencing without reverse transcription, preserving natural chemical modifications.
Each tRNA molecule passes through a nanopore, generating electrical signals that reflect both sequence and modification status.

| Analysis Feature | Basic tRNAome Analysis | Advanced tRNAome Analysis |
| Basecalling for Structured RNAs | ✓ Optimised models for short, modified tRNAs | ✓ Model benchmarking + alternative basecalling modes |
| Ribosome-bound tRNA Mapping | ✓ High-confidence mapping to curated tRNA references | ✓ Custom tRNA reference building for non-model organisms |
| Isoacceptor / Isodecoder Identification | ✓ Standard assignments | ✓ Enhanced isoacceptor separation using raw signal patterns |
| Quantification of Ribosome-Bound tRNAs | ✓ Abundance estimation of A/P/E-site tRNAs | ✓ Multi-condition comparison + differential tRNA usage |
| Modification Signature Detection | ✓ Identification of modification-associated signal shifts | ✓ KL-divergence analysis for multi-modification profiling (Ψ, m¹A, m⁷G, U34 variants, i⁶A, etc.) |
| Nanopore Signal Interpretation | — | ✓ Signal-level (event-space) visualisation, motif-aware patterns |
| Ribosome-Specific tRNAome Profiling | ✓ Separation of ribosome-bound vs. total tRNA patterns | ✓ Quantitative modelling of ribosome occupancy and decoding bias |
| Codon–Anticodon Adaptation Metrics | — | ✓ Integration with ribosome profiling data (optional) |
| Modification Network Insights | — | ✓ Exploration of modification cross-talk (e.g., Ψ↔m¹A interplay; U34 pathway shifts) |
| Multi-Platform Integration (Optional) | ✓ Summary-level alignment | ✓ Deeper integration with RNA-seq or LC–MS/MS datasets |
| Feature | Traditional Ribo-seq (ribosome profiling) | Nanopore Ribosome tRNA-Seq | Nano tRNA Sequencing (ONT direct tRNA sequencing) |
| Readout target | Ribosome-protected mRNA fragments (≈28-34 nt) | tRNAs actively bound to ribosomes (A/P/E sites) – service focus | Native full-length cellular tRNAs, modification-aware |
| Captures tRNAs | ✘ | ✔ (ribosome-bound) | ✔ (all cellular) |
| Detects tRNA modifications | ✘ (via reverse transcription bias) | ✔ (via native reads) | ✔ (via native reads) |
| Provides codon–anticodon decoding context | ✔ (mRNA translation footprint) | ✔ (tRNA recruited to ribosomes) | ✘ |
| Quantifies ribosome-bound tRNA usage | ✘ | ✔ | ✘ |
| Full-length native tRNA reads | ✘ | ✔ | ✔ |
| Ideal research focus | Which mRNAs are translated, ribosome stalling | How tRNAs are used by ribosomes & how modifications modulate decoding | Global tRNAome abundance & modification landscape |
| Key limitation | Cannot detect tRNA modifications or native tRNA isoacceptors | Requires specific enrichment and nanopore signal analysis | Doesn't provide ribosome‐binding context |
Notes:
| Parameter | Requirement | Notes / References |
| Sample type | Total RNA extracted from any species (cells, tissues, microbes, plants) | Broad species support; aligns with RNA-seq guidelines |
| Minimum input quantity | ≥ 3 µg total RNA per sample | Higher input supports ribosome-tRNA enrichment and library prep; consistent with Long-read RNA guidelines |
| RNA integrity | RIN (or equivalent) ≥ 7.0, A260/280 ≈ 1.8–2.1, A260/230 ≥ 2.0 | Quality thresholds from RNA-seq core facility guidelines |
Ribo-Seq captures ribosome-protected mRNA fragments to provide a snapshot of which mRNAs are being actively translated. Unlike Ribo-Seq, tRNA-focused sequencing profiles the tRNAs themselves—especially those bound to ribosomes or in the cellular pool—and can reveal modification status and isoacceptor usage that Ribo-Seq cannot.
ONT direct RNA sequencing uses nanopores to sequence native RNA molecules without reverse transcription or PCR, enabling detection of chemical modifications and full-length reads. For tRNA analysis, this means modifications are preserved and can be interpreted, which is critical for understanding translational regulation.
Yes — by enriching ribosome-bound tRNAs and sequencing them natively, the platform quantifies which tRNAs are recruited by ribosomes and provides insights into their modification profiles, offering a combined view of abundance and modification in one experiment.
No — the workflow is designed for broad species compatibility, allowing total RNA extracted from microbes, plants, animals, or human-derived samples to be used, enabling cross-species and comparative translation studies.
We recommend high-quality total RNA (e.g., RIN ≥ 7, A260/280 ~1.8-2.1) and sufficient input (e.g., ≥ 3 µg) derived from samples handled under ribosome-preserving conditions; details should be discussed with our sales team to optimise ribosome-tRNA capture effectiveness.
This tRNAome service complements Ribo-Seq (which profiles mRNA translation) and RNA-seq or LC–MS/MS (which profiles transcriptome or chemical modifications) — enabling multi-layered insights such as codon–anticodon alignment, modification networks and translation regulation mechanisms.

References
For research purposes only, not intended for personal diagnosis, clinical testing, or health assessment