Nanopore Direct lncRNA Sequencing
Long non-coding RNAs (lncRNAs) regulate gene expression, chromatin dynamics, and cellular signaling across virtually every biological pathway. Yet their full-length isoforms, tissue-specific expression patterns, and native RNA modifications remain systematically under-detected by conventional short-read sequencing. CD Genomics addresses this gap with our Nanopore Direct lncRNA Sequencing service — an Oxford Nanopore Technologies (ONT)-based approach that directly sequences native RNA molecules without reverse transcription or PCR amplification bias, capturing both polyadenylated and non-polyadenylated RNA species in a single experiment.
Unlike standard poly(A)-enriched RNA-seq that preferentially recovers mRNA and loses most non-coding transcripts, our Direct lncRNA sequencing workflow employs rRNA depletion combined with optimized 3′ adapter ligation and motor protein loading, enabling simultaneous detection of lncRNA, mRNA, rRNA, tRNA, and other RNA classes. The platform delivers single-base resolution of RNA modifications — including m⁶A, m⁵C, pseudouridine (Ψ), inosine, and 2′-O-methylation — alongside full-length transcript structures, providing an integrated view of both the transcriptome and epitranscriptome from a single sequencing run.
Why Choose Nanopore Direct lncRNA Sequencing?
- Comprehensive RNA landscape — Detects lncRNA, mRNA, rRNA, and tRNA simultaneously without poly(A) enrichment bias
- Single-base modification profiling — Identifies m⁶A, m⁵C, Ψ, inosine, and 2′-O-methylation directly from native RNA signals
- Full-length isoform resolution — Spans complete transcript sequences from 5′ to 3′ end without fragmentation or assembly
- Native RNA preservation — No reverse transcription or PCR amplification preserves the original RNA modification landscape
The lncRNA Blind Spot in Standard RNA Sequencing
Conventional RNA-seq workflows rely on poly(A) enrichment to capture mRNA transcripts, intentionally or inadvertently discarding most non-polyadenylated RNA species. This bias creates a systematic blind spot for lncRNAs, a significant fraction of which lack poly(A) tails or carry short, unstable A-rich sequences that are inefficiently captured. Even when lncRNAs are polyadenylated, short-read fragmentation destroys the connectivity between distant exons, forcing computational isoform reconstruction that frequently misassembles or entirely misses low-abundance transcripts.
These technical limitations have direct biological consequences. LncRNAs are increasingly recognized as central regulators of chromatin conformation, transcriptional control, phase separation, and post-transcriptional gene regulation. Many lncRNAs function through specific RNA modifications — particularly m⁶A — that modulate their stability, localization, and protein-binding capacity. Detecting these modifications on native lncRNA molecules requires a sequencing approach that preserves the original chemical state of every base and maintains full transcript continuity. Our Nanopore Direct lncRNA Sequencing service is designed to meet this requirement.
What is Direct lncRNA Sequencing?
Direct lncRNA sequencing is an Oxford Nanopore Technology-based method that sequences native RNA molecules directly — without chemical conversion, antibody enrichment, or PCR amplification. The core innovation lies in the library preparation strategy: total RNA undergoes rRNA depletion to remove abundant ribosomal RNA, followed by 3′ adapter ligation that captures both polyadenylated and non-polyadenylated RNA molecules. This is fundamentally different from standard direct RNA sequencing, which relies on poly(A) capture and therefore only recovers poly(A)+ RNA.
By combining rRNA depletion with 3′ adapter-dependent library construction, the Direct lncRNA workflow achieves comprehensive RNA detection spanning lncRNA, mRNA, rRNA, tRNA, and other non-coding transcripts in a single run. The native RNA is then threaded through ONT nanopores, where the changing ionic current as each nucleotide passes through the pore is recorded in real time. These current signals encode not only the nucleotide sequence but also information about base modifications — because modified bases produce characteristic signal deviations from their unmodified counterparts. This dual-layer readout enables simultaneous base calling and modification detection without any additional experimental steps.
The resulting data supports full-length isoform identification (including novel transcripts and alternative splicing events), quantitative expression profiling, fusion gene detection, alternative polyadenylation (APA) site mapping, poly(A) tail length measurement, and single-base RNA modification calling — all from a single library preparation and sequencing run.
Key Advantages of Direct lncRNA Sequencing
Scientific Advantages
- Single-base RNA modification profiling on native RNA
Direct nanopore sequencing reads the chemical state of every base as it exists in the sample. Modifications including m⁶A, m⁵C, pseudouridine (Ψ), inosine, and 2′-O-methylation produce characteristic ionic current signatures that can be detected at single-nucleotide resolution without antibody enrichment, bisulfite conversion, or chemical labeling. This is particularly valuable for lncRNA biology, where m⁶A functions as a key regulator of lncRNA stability, nuclear retention, and phase separation behavior.
- Isoform-resolved transcript discovery
Full-length native RNA reads spanning 5′ caps to poly(A) tails eliminate the need for computational isoform assembly. Each read represents a complete transcript molecule, enabling direct detection of alternative splicing, exon skipping, intron retention, alternative transcription start sites, and fusion transcripts. This is especially critical for lncRNA genes, which frequently produce complex repertoires of low-abundance isoforms that short-read methods reconstruct poorly or miss entirely.
Business & Project Advantages
- Multiple data types from a single sequencing run
Our Direct lncRNA sequencing generates transcriptome sequence, isoform structure, and epitranscriptome modification data concurrently. Researchers receive expression quantifications, full-length isoform annotations, splice event calls, poly(A) tail profiles, and base-resolution modification calls from one library preparation — reducing both project cost and turnaround complexity compared to running separate mRNA-seq, MeRIP-seq, and isoform sequencing experiments.
- Customized bioinformatics with transparent QC
We provide end-to-end bioinformatics support aligned with your specific research goals. Standard deliverables include basecalled FASTQ files, genome-aligned BAM files with modification probability tracks, isoform-level quantification matrices, and publication-ready reports. Advanced analysis — including differential modification analysis, multi-sample Iso-Seq-style clustering, and poly(A) tail distribution profiling — is available through our long-read sequencing data analysis pipeline.
Applications of Nanopore Direct lncRNA Sequencing
LncRNA Isoform Discovery and Annotation
- Full-length isoform cataloging for lncRNA genes with complex splicing architectures
- Identification of novel intergenic lncRNAs (lincRNAs), antisense transcripts, and enhancer-derived RNAs (eRNAs)
- Cross-species lncRNA conservation analysis and de novo annotation for non-model organisms
Epitranscriptomic Regulation in Development and Disease
- Single-base m⁶A mapping on lncRNAs to identify modification-regulated transcripts in cancer, neurodevelopment, and immune response
- Co-occurrence analysis of multiple modification types on individual lncRNA molecules
- Dynamic RNA modification profiling across developmental stages or treatment conditions through long-read sequencing of RNA methylation
Alternative Splicing and Transcriptome Complexity
- Direct detection of disease-associated splicing events and fusion lncRNAs using our splice variation analysis workflow
- Comprehensive poly(A) tail length analysis and alternative polyadenylation (APA) site mapping for both coding and non-coding transcripts
- Integration with long-read transcriptomics for multi-condition splicing comparisons
Multi-Kingdom RNA Biology
- Microbial lncRNA discovery and host-pathogen interaction transcriptomics
- Plant lncRNA characterization in abiotic stress response and developmental regulation
- tRNA and rRNA modification profiling alongside lncRNA detection in the same sample
Technology Overview — How Direct lncRNA Sequencing Works
1. Total RNA Extraction and Quality Assessment
High-integrity total RNA is extracted from your biological samples using protocols optimized for the sample type (tissue, cells, biofluids, or FFPE). RNA integrity is assessed by microfluidic electrophoresis (RIN ≥ 7 recommended for standard projects; degraded RNA samples are evaluated on a case-by-case basis with modified workflows available).
2. rRNA Depletion
Ribosomal RNA is removed from total RNA using probe-based or enzymatic depletion methods tailored to the species of origin (human, mouse, plant, yeast, bacteria, etc.). This step enriches the full diversity of coding and non-coding transcripts without the bias introduced by poly(A) selection.
3. 3′ Adapter Ligation and Reverse Transcription
A sequencing adapter carrying the motor protein docking site is ligated to the 3′ end of all RNA molecules — both polyadenylated and non-polyadenylated. Reverse transcription is performed at optimized temperatures using engineered RT enzymes capable of resolving structured non-coding RNAs (e.g., tRNA, snoRNA) that would otherwise stall standard reverse transcriptases.
Direct lncRNA sequencing workflow: total RNA extraction → rRNA depletion → 3′ adapter ligation → reverse transcription → motor protein adapter loading → ONT nanopore sequencing with real-time base calling and modification detection
4. Motor Protein Loading and Nanopore Sequencing
The RNA-cDNA hybrid is loaded onto an ONT flow cell (R10.4.1 or later generation). The motor protein unwinds the RNA-cDNA duplex and processively feeds the RNA strand through the nanopore. Real-time ionic current measurements are basecalled using ONT's neural-network basecallers (Dorado) configured for modified-base-aware models that simultaneously call canonical bases and flag modification-associated signal deviations.
5. Signal-Level Modification Detection and Transcript Assembly
Post-sequencing analysis applies signal-level tools (Nanocompore, m6Anet, Tombo) to compare per-read ionic current profiles against reference signals, enabling single-base modification probability estimation. Simultaneously, full-length reads are aligned to the reference genome (or assembled de novo) for isoform identification, splice junction mapping, and poly(A) tail length quantification.
Bioinformatics Analysis
| Analysis Feature | Basic | Advanced |
| Basecalling (Dorado super-accuracy) | ✓ | ✓ |
| Read QC, filtering, and adapter trimming | ✓ | ✓ |
| Reference genome alignment (minimap2) | ✓ | ✓ |
| Full-length isoform detection and quantification | ✓ | ✓ |
| lncRNA identification and classification (FEELnc, CPC2) | ✓ | ✓ |
| Single-base m⁶A modification calling | — | ✓ |
| Alternative splicing and fusion transcript detection | — | ✓ |
| Poly(A) tail length distribution analysis | — | ✓ |
| Differential isoform expression across conditions | — | ✓ |
| Custom visualization and publication-ready figures | — | ✓ |
Choosing the Right RNA Sequencing Approach
Selecting the appropriate nanopore RNA sequencing strategy depends on whether your research focuses on the primary sequence, isoform structure, or native modification landscape of RNA molecules. The table below compares our three complementary ONT-based RNA sequencing services to guide your selection.
| Feature | Direct lncRNA Sequencing | Direct RNA Sequencing | Full-Length cDNA Sequencing |
| RNA capture method | rRNA depletion + 3′ adapter ligation | Poly(A) capture | rRNA depletion + random/oligo-dT priming |
| Non-poly(A) RNA detected | ✔ Yes (lncRNA, tRNA, rRNA) | ✘ No | ✔ Yes |
| Native RNA modifications | ✔ Direct detection | ✔ Direct detection | ✘ Lost during RT-PCR |
| Read throughput | Moderate–High | Moderate | High |
| Recommended for | Comprehensive lncRNA + mRNA + modification analysis | Poly(A)+ transcriptome and modification profiling | High-throughput isoform discovery and quantification |
For projects that require native RNA modification analysis without the need for comprehensive non-coding RNA detection, our Nanopore Direct RNA Sequencing service provides a streamlined poly(A)-based workflow. If transcript isoform detection and quantification at higher throughput is the primary goal — and modification information is not required — our Nanopore Full-Length cDNA Sequencing service offers optimal read depth and cost efficiency.
Platform Performance Benchmark for lncRNA Detection
The following comparison integrates findings from the LRGASP systematic benchmark (Pardo-Palacios et al., Nat Methods, 2024), the NanoncRNA-Seq study (Zhang et al., Commun Biol, 2026), and recent cross-platform evaluations to help researchers understand how Nanopore Direct lncRNA Sequencing compares with alternative approaches at the level of published, peer-reviewed performance data.
| Performance Metric | Nanopore Direct lncRNA Sequencing | Illumina Short-Read RNA-Seq | PacBio HiFi Iso-Seq |
| Read type | Full-length native RNA (single-molecule) | Fragmented cDNA (50–300 bp) | Full-length cDNA (circular consensus) |
| Raw read accuracy | Q22.35 (99.42%) — R10.4.1 flowcell | Q30–Q40 (99.9–99.99%) | Q30+ (99.9%) — HiFi CCS |
| lncRNA detection sensitivity | 260 lncRNAs / 201 lincRNAs (yeast; Pinfish) | 51 lncRNAs / 25 lincRNAs (matched sample) | ~2× more non-coding features vs. Illumina (LRGASP) |
| Isoform assignment ambiguity | Low — each read is a complete transcript | High — reads map ambiguously to multiple isoforms | Low — circular consensus resolves isoform identity |
| Novel isoform discovery | Direct detection from single reads | Requires computational assembly; high false-positive rate | Direct detection; high precision |
| Native RNA modifications | ✔ Detected simultaneously (m⁶A, m⁵C, Ψ, inosine, 2′-O-Me) | ✘ Requires separate MeRIP-seq or equivalent assay | ✘ Not detected (cDNA-based) |
| Non-poly(A) RNA capture | ✔ rRNA depletion + 3′ adapter ligation | ✘ Typically poly(A) enrichment; loses most lncRNAs | ✔ Random-primed cDNA synthesis |
| Quantification reliability (transcript level) | High — direct read-to-transcript assignment | Moderate — high inferential variability inflates false DTE calls | High — reliable DTE calls with low false positive rate |
| Recommended project scale | Focused lncRNA studies, modification profiling, small–moderate cohort sizes | Large cohort screening, gene-level expression at scale | Isoform-resolved transcript discovery, moderate cohort sizes |
Source data: LRGASP Consortium benchmark (Pardo-Palacios et al., Nat Methods 21, 1349–1363, 2024); NanoncRNA-Seq comparison (Zhang et al., Commun Biol, 2026); cross-platform transcriptome evaluation (bioRxiv 2025.09.11.675724).
Sample Requirements for Direct lncRNA Sequencing
| Category | Requirement | Notes |
| Sample type | Total RNA (fresh, frozen, or RNAlater-stabilized) | Tissue, cultured cells, or biofluids; DNase-treated recommended |
| Minimum input | ≥2 µg (standard); ≥500 ng (low-input workflow) | Low-input protocol available for precious samples; success rate varies by sample quality and complexity |
| RNA integrity | RIN ≥ 7 (standard); degraded RNA assessed case-by-case | RIN < 7 samples may proceed with reduced throughput; consult our project scientists for feasibility |
| Recommended depth | 10–20 million reads per sample | Higher depth recommended for low-abundance lncRNA isoform detection |
| Species | Human, mouse, rat, plant, yeast, bacteria, or custom | rRNA depletion probes must match the species; custom probe design available |
Why Choose CD Genomics for Direct lncRNA Sequencing
Dual-platform long-read expertise
CD Genomics operates both PacBio and ONT platforms under one service umbrella, providing unbiased technical guidance on platform selection. Our ONT Direct lncRNA sequencing benefits from continuous protocol optimization across R10.4.1 and subsequent flow cell generations, ensuring access to the latest accuracy improvements and throughput capabilities.
End-to-end project support from experimental design to publication
We manage every stage of your lncRNA sequencing project: initial feasibility assessment (including degraded or low-input RNA evaluation), library preparation and QC, ONT sequencing on PromethION or GridION instruments, and a comprehensive bioinformatics pipeline that delivers isoform annotations, modification probability tracks, and expression matrices ready for downstream analysis.
Integrated lncRNA discovery and epitranscriptomic analysis in a single workflow
Unlike providers who separate transcript sequencing from modification analysis, our Direct lncRNA sequencing service delivers both data types from the same library preparation. This integration reduces sample input requirements, simplifies project logistics, and generates a more complete molecular picture than any single-assay approach.
Case Study: rRNA-Depleted Full-Length Transcriptome Strategy for Novel lncRNA Isoform Discovery
Zhang T, Chen J, Hou H, Yousuf S, Ji J, Li Y, et al. An rRNA-depleted full-length transcriptome strategy using nanopore sequencing for identification of novel lncRNA isoforms. Commun Biol. 2026. DOI: 10.1038/s42003-026-10214-y. (CC BY 4.0)
1. Background
Short-read RNA sequencing systematically underrepresents lncRNAs, particularly non-polyadenylated isoforms and low-abundance transcripts that cannot be reliably reconstructed from fragmented reads. The authors developed NanoncRNA-Seq, an rRNA-depleted full-length transcriptome workflow using ONT R10.4.1 flowcells, to determine whether long-read direct transcript sequencing could recover lncRNA isoforms missed by Illumina sequencing in the model eukaryote Saccharomyces cerevisiae under glucose (fermentative) and ethanol (respiratory) metabolic states.
2. Methods
Total RNA from yeast cultures under both metabolic conditions was rRNA-depleted and processed for ONT full-length transcript sequencing on R10.4.1 flowcells (NanoncRNA-Seq) alongside Illumina NovaSeq short-read sequencing. ONT data were basecalled with Dorado, aligned with minimap2, and used for isoform detection with Pinfish, FLAIR, and IsoQuant. Short-read data were processed with standard Illumina transcriptome pipelines for comparison. LncRNA classification was performed using FEELnc and CPC2.
3. Results
NanoncRNA-Seq identified 260 lncRNAs compared to 51 by Illumina, including 201 lincRNAs versus 25 — demonstrating approximately five-fold and eight-fold improvements in lncRNA and lincRNA recovery, respectively. Data representative of the published study (CC BY 4.0).
Key Findings
- ONT NanoncRNA-Seq identified 260 lncRNAs versus 51 by Illumina (Pinfish)
- Intergenic lncRNA (lincRNA) detection was particularly improved: 201 lincRNAs by ONT compared to 25 by Illumina
- ONT achieved a median Q-score of 22.35 (99.42% raw read accuracy) on R10.4.1 flowcells
- Expression profiles were highly consistent within each platform and moderately consistent across platforms
- ONT detected more novel isoforms and fewer SNPs than Illumina; Illumina reported fewer INDELs
4. Conclusions
This study demonstrates that rRNA-depleted full-length nanopore sequencing (NanoncRNA-Seq) recovers substantially more lncRNA diversity than short-read sequencing, particularly for low-abundance and non-polyadenylated transcripts. The two platforms are complementary: ONT excels at capturing full-length isoform architectures and novel lncRNAs, while Illumina provides higher per-base accuracy for variant calling. For researchers whose primary goal is lncRNA discovery and isoform-resolved transcriptome analysis, the NanoncRNA-Seq approach represents a significant methodological advance over short-read-only strategies.
FAQs
Q: What is the difference between Direct lncRNA Sequencing and standard Direct RNA Sequencing?
Standard direct RNA sequencing relies on poly(A) capture, which only recovers mRNA and a subset of polyadenylated lncRNAs. Direct lncRNA sequencing replaces poly(A) selection with rRNA depletion followed by 3′ adapter ligation, enabling capture of both polyadenylated and non-polyadenylated RNA molecules — including lncRNA, tRNA, rRNA, and other non-coding transcripts that would be missed by the poly(A)-based workflow.
Q: Which RNA modifications can be detected using this service?
Our standard modification analysis detects m⁶A across the transcriptome using Nanocompore and m6Anet pipelines. Extended analysis can additionally profile m⁵C, pseudouridine (Ψ), inosine, and 2′-O-methylation signal patterns upon request. Modification calling is performed at single-base resolution by comparing per-read ionic current profiles against unmodified reference signals, with validation through replicate consistency and orthogonal data integration where available.
Q: What is the minimum RNA input required, and can degraded RNA be used?
The standard protocol requires ≥2 µg of total RNA with RIN ≥ 7. For precious or limited samples, a low-input workflow (≥500 ng) is available. Degraded RNA samples (RIN < 7) can be assessed on a case-by-case basis — reduced full-length read throughput is expected, and modified library preparation conditions may be recommended. We strongly recommend consulting our project scientists before submitting degraded or very low-input samples to evaluate feasibility and expected deliverable quality.
Q: Can Direct lncRNA Sequencing be applied to non-model organisms?
Yes. The rRNA depletion step requires species-matched or closely related probes; we maintain a panel of standard probes for human, mouse, rat, yeast, Arabidopsis, E. coli, and other common species, and can design custom depletion probes for non-model organisms. De novo transcriptome assembly from ONT long reads is available for species without a reference genome, enabling lncRNA discovery and isoform annotation independently of existing gene models.
Q: What bioinformatics deliverables will I receive?
Standard deliverables include: (1) basecalled FASTQ files with quality metrics, (2) genome-aligned BAM files, (3) isoform-level quantification tables (TPM/gene counts), (4) lncRNA classification reports (FEELnc/CPC2), (5) splice junction and alternative splicing event calls, and (6) a comprehensive project report with QC metrics. Advanced deliverables add single-base m⁶A modification probability tracks (BED/bigWig), differential isoform expression analysis, poly(A) tail length distributions, and custom visualization. All data are provided with full methods documentation for publication support.
Demo Data and Deliverable Examples
Below are representative output examples from Nanopore Direct lncRNA sequencing projects. Actual results vary by sample type, input quality, and sequencing depth.
Deliverable 1 — Full-length lncRNA isoform annotation
Genome browser tracks (IGV) showing complete lncRNA isoform architectures identified from ONT direct sequencing reads. Each row represents a single full-length read spanning from the transcription start site through splice junctions to the poly(A) site, enabling direct visualization of alternative promoter usage, exon skipping events, and intron retention patterns without computational reconstruction.
Deliverable 2 — Single-base m⁶A modification probability profiles
Per-nucleotide modification probability tracks (bigWig format) along individual lncRNA transcripts. Modification probabilities range from 0 (unmodified) to 1 (fully modified) at each position, derived from Nanocompore comparative analysis against unmodified controls. Visualization includes read-level modification status (modified vs. unmodified per read) stacked along the transcript coordinate, revealing modification heterogeneity across individual RNA molecules.
Deliverable 3 — Poly(A) tail length distribution analysis
Violin plots and cumulative distribution curves showing poly(A) tail lengths for lncRNA and mRNA populations under control versus treatment conditions. Tail lengths are measured directly from ONT raw signal dwell times during translocation through the nanopore, providing single-nucleotide resolution of poly(A) tail architecture without the PCR amplification bias that truncates tail measurements in short-read protocols.
Deliverable 4 — Isoform-level expression quantification matrix
Transcript-level count and TPM matrix across all samples, annotated with lncRNA classification (intergenic, antisense, sense-overlapping, processed transcript), biotype, and confidence score. Quantification is performed using long-read-aware tools (Bambu, IsoQuant) that assign multimapping reads probabilistically based on full-length isoform evidence.
Representative deliverable examples from Nanopore Direct lncRNA sequencing projects, including isoform annotation tracks, modification probability profiles, and poly(A) tail length distributions.
References
- Zhang T, Chen J, Hou H, Yousuf S, Ji J, Li Y, et al. An rRNA-depleted full-length transcriptome strategy using nanopore sequencing for identification of novel lncRNA isoforms. Commun Biol. 2026. DOI: 10.1038/s42003-026-10214-y. (CC BY 4.0)
- Saville L, Wu L, Habtewold J, Cheng Y, Gollen B, Mitchell L, et al. NERD-seq: a novel approach of Nanopore direct RNA sequencing that expands representation of non-coding RNAs. Genome Biol. 2024;25:233. DOI: 10.1186/s13059-024-03375-8. (CC BY 4.0)
- Leger A, Amaral PP, Pandolfini L, Capitanchik C, Capraro F, Miano V, et al. RNA modifications detection by comparative Nanopore direct RNA sequencing. Nat Commun. 2021;12:7198. DOI: 10.1038/s41467-021-27393-3. (CC BY 4.0)
For Research Use Only. Not for diagnostic procedures.