Can this method quantify protein levels directly?

No. It quantifies the number of mRNA molecules associated with ribosomes. While this correlates strongly with protein synthesis (more so than Total RNA), it does not measure protein degradation or stability.

How does this differ from Ribo-seq?

Ribo-seq digests the RNA to ~30nt footprints to map ribosome positions at codon resolution. Long-read RNC-seq keeps the RNA intact to map the structure of the transcript. Ribo-seq is better for translational pausing; Long-read RNC-seq is better for isoform discovery.

Do you support clinical samples?

We accept clinical research samples (RUO only), but we require higher input amounts (fresh frozen tissue) than standard RNA-seq. FFPE samples are generally not suitable due to RNA degradation.

Is this suitable for comparative studies (e.g., Drug vs. Control)?

Yes. By including biological replicates, we can perform differential isoform usage analysis to see how treatments affect which isoforms are translated.

Translatomics
Long-read RNC-seq

Long-read RNC-seq for Full-Length Translating Transcript Profiling

Long-read RNC-seq by CD Genomics captures ribosome-associated full-length RNAs to reveal precisely which transcript isoforms are actively translated. This service overcomes the assembly limitations of short-read RNC-seq and conventional Ribo-seq by providing full-length translational resolution and isoform-specific functional insight.

True Isoform Resolution: 10kb+ reads capture full exon connectivity of translating transcripts.
Active Translation Only: Sucrose cushion enrichment eliminates non-coding/inactive RNAs.
Data Integrity: >Q30 accuracy (PacBio HiFi) for precise SNP and indel detection.

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full-length transcript isoform mapping visualization for translational profiling

Overview Comparison Workflow Bioinformatics Applications Samples FAQ

What Is Long-read RNC-seq?

Long-read RNC-seq is a specialized transcriptomic technique that combines ribosome-nascent chain (RNC) complex enrichment with third-generation long-read sequencing (TGS). It allows researchers to isolate and sequence full-length mRNA molecules actively bound to ribosomes, thereby determining the precise isoform structure and abundance of transcripts undergoing protein synthesis. Unlike short-read methods, this approach eliminates assembly steps, providing a direct, unambiguous map of the "functional translatome."

Bridging the Genotype-Phenotype Gap

For decades, researchers have relied on Total RNA-seq as a proxy for protein expression. However, the correlation between mRNA abundance (transcriptome) and protein abundance (proteome) is often low—typically around 0.4 to 0.6. This discrepancy arises from translational control mechanisms:

Translational Buffering: Cells may transcribe high levels of mRNA but suppress their translation via miRNA binding or RNA-binding proteins (RBPs).
Isoform Switching: A gene may express multiple splice variants, but only specific isoforms (e.g., those with optimal 5' UTRs) are recruited to ribosomes.
Ribosome Stalling: Some mRNAs are associated with stalled ribosomes and are not effectively producing protein.

Long-read RNC-seq solves this by physically separating the "active" pool (polysome-bound) from the "inactive" pool (free cytoplasmic/monosome), and then sequencing the active pool end-to-end. This provides the definitive link between a specific splicing event and its translational output.

Why Study Translating Isoforms?

1. Deciphering Isoform-Specific Translational Control

Alternative splicing (AS) is a major source of proteomic diversity, especially in mammals and plants. However, short-read RNA-seq cannot accurately quantify full-length isoforms, only local exon usage. This leads to the "connectivity problem"—if Exon 1 and Exon 5 are both upregulated, are they on the same molecule?

The Long-read Solution: By sequencing the entire molecule (e.g., 2kb - 10kb), Long-read RNC-seq reveals the exact combination of exons being translated. This is critical for identifying isoforms with premature termination codons (PTCs) that escape Nonsense-Mediated Decay (NMD) and produce truncated, potentially toxic proteins.

2. Identifying Non-Canonical ORFs and IncRNAs

Recent studies utilizing ribosome profiling have revealed that many "non-coding" RNAs (lncRNAs) actually contain small Open Reading Frames (sORFs) that encode micro-peptides.

Application: Long-read RNC-seq can validate which lncRNA isoforms are associated with ribosomes, distinguishing true non-coding regulatory RNAs from those acting as peptide templates.

3. Understanding Stress Responses

Under stress conditions (hypoxia, heat shock, drug treatment), cells trigger a global shutdown of translation while selectively prioritizing survival mRNAs (e.g., HIF1A, HSP70).

Mechanism: This selection is often driven by 5' UTR structures (IRES elements). Long-read sequencing captures the full 5' leader sequence, allowing researchers to correlate specific UTR variants with preferential translation under stress.

Technical Principle

RNC Enrichment by Sucrose Cushion Ultracentrifugation

Cells or tissues are stabilized with translation inhibitors
Ribosome–mRNA complexes are pelleted through a sucrose cushion
Free RNA and non-translating transcripts are removed
Only actively translating mRNAs are recovered

This enrichment strategy yields high-integrity RNA suitable for long-read sequencing, unlike gradient-based polysome fractionation.

Core Comparison: Second-Generation RNC-seq vs Long-read RNC-seq

We offer two distinct long-read platforms depending on the research goal:

Feature	RNC-seq (Second-generation)	Long-read RNC-seq
Sequencing Strategy	Short-read (NGS)	Long-read (Nanopore)
RNA State Captured	Ribosome-associated mRNA	Ribosome-associated full-length transcripts
Isoform Resolution	Limited (inferred)	Direct, full-length isoform resolution
Alternative Splicing Analysis	Partial	Comprehensive, end-to-end
Assembly Required	Yes	No assembly required
Translation Insight	Which genes are translated	Which isoforms are translated
Translation Efficiency (TE)	Gene-level	Isoform-level (optional)
Key Advantage	High-throughput screening	Decoding splicing–translation regulation

Key Advantages Over Short-read Translation Profiling

Isoform Resolution	High (Full-lengtd)	Limited (Inferred)	Low (Fragment based)
Splicing Analysis	Direct observation	Computational prediction	Difficult
Assembly Required	No	Yes	Yes
Read Length	1kb – 10kb+	150bp (PE)	~30bp
Quantification	Isoform-level	Gene-level	Codon-level

Key Benefit: By avoiding fragmentation, we eliminate the "isoform ambiguity" problem. You know exactly which splice variant is engaged with the ribosome.

Our Service Capabilities

CD Genomics provides a complete translatomics service portfolio, including:

We offer end-to-end support, from experimental design and sample processing to custom bioinformatics analysis.

Experimental Workflow

Step 1: Sample Lysis and Stabilization

Input: Fresh tissue is ground in liquid nitrogen. Cultured cells are lysed directly on the plate.
Lysis Buffer: Contains Tris-HCl, NaCl, MgCl2, Detergents (Triton X-100), DTT, RNase Inhibitors (critical), and Cycloheximide.
Quality Check 1: A small aliquot of lysate is checked to ensure complete cell lysis.

Step 2: RNC Enrichment (Sucrose Cushion)

The cleared lysate is carefully layered on top of a 30% sucrose cushion in an ultracentrifuge tube.
Centrifugation: 100,000 × g at 4°C for 4 hours.
Recovery: The supernatant (containing free RNA) is discarded. The glassy, translucent pellet (Ribosome-Nascent Chain Complex) is resuspended.
Protein Digestion: Proteinase K is added to digest the ribosomal proteins, releasing the protected mRNA.

Step 3: RNA Extraction and QC

RNA is purified using Trizol or column-based methods.
Rigorous QC:
- Nanodrop: A260/280 ratio must be 1.8–2.0.
- Agilent Bioanalyzer/TapeStation: We require a RIN (RNA Integrity Number) ≥ 7.0.
- DIN (DNA Integrity Number): For Nanopore, we check for DNA contamination.
Note: RNC-derived RNA often shows distinct 18S and 28S rRNA peaks, confirming ribosomal recovery.

Step 4: Library Preparation (Iso-Seq Example)

cDNA Synthesis: Uses the NEBNext® Single Cell/Low Input cDNA Synthesis & Amplification Module or PacBio Iso-Seq Express kit.
- Template Switching Oligo (TSO) ensures only full-length mRNAs with a 5' cap and 3' poly(A) tail are reverse transcribed.
Amplification: Limited PCR cycles (optimized to prevent bias) generate sufficient dsDNA.
SMRTbell Construction: Hairpin adapters are ligated to the double-stranded cDNA.
Size Selection: (Optional) BluePippin size selection to remove transcripts <1kb if the goal is to target long isoforms.

Step 5: Sequencing and Primary Analysis

Sequencing: Performed on PacBio Revio or Sequel IIe.
CCS Generation: Raw subreads are processed into Circular Consensus Reads (HiFi reads) with >99% accuracy.
Demultiplexing: Removal of barcode sequences.

Bioinformatics Analysis Pipeline

Raw long-read data requires specialized tools distinct from the standard STAR or HISAT2 pipelines used for Illumina data.

1. Data Processing (The "Iso-Seq3" Workflow)

Refinement: Removal of poly(A) tails and concatemers using Lima and IsoSeq3 refine.
Clustering: Clustering similar reads to generate high-quality consensus transcripts.
Mapping: Alignment to the reference genome using Minimap2 or deSALT, which are optimized for splice-aware long-read alignment.

2. Transcriptome Characterization (SQANTI3)

Classification: We use SQANTI3 (Structural and Quality Annotation of Novel Transcript Isoforms) to categorize every detected transcript into:
- FSM (Full Splice Match): Matches a known reference transcript perfectly.
- ISM (Incomplete Splice Match): Matches part of a known transcript.
- NIC (Novel In Catalog): New combination of known splice sites.
- NNC (Novel Not in Catalog): Contains new splice sites.
Filtering: Removal of potential artifacts (e.g., intra-priming events) based on SQANTI3 QC flags.

3. Translation Quantification

Abundance Estimation: While long reads are not ideal for "counting" in the same way short reads are due to lower throughput, we calculate CPM (Counts Per Million) or TPM for each isoform.
RNC vs Total Comparison: If matched Total RNA-seq data is available, we calculate the Translation Efficiency (TE) for each isoform.

4. Functional Annotation

Coding Potential: Tools like CPAT or CPC2 predict if novel isoforms have coding potential.
Protein Domain Mapping: Mapping predicted ORFs to Pfam databases to see if AS events disrupt functional domains.

Applications

1. Oncology: Neoantigen Discovery

Tumors often utilize aberrant splicing to produce neoantigens. Short-read RNA-seq might identify a "retained intron," but it cannot confirm if that intron is included in the full transcript that is actually translated.

Impact: Long-read RNC-seq definitively identifies full-length, translated, tumor-specific isoforms. These are prime targets for mRNA vaccine development because they are confirmed to be processed by the ribosome, increasing the likelihood of MHC presentation.

2. Neuroscience: Synaptic Plasticity

Neurons rely on the transport of specific mRNA isoforms to dendrites for local translation.

Impact: RNC-seq on synaptoneurosomes (synaptic fractions) reveals which specific isoforms (often with specific 3' UTR "zipcodes") are being translated at the synapse. Long reads are essential here because 3' UTR variants are difficult to link to specific coding sequences with short reads.

3. Plant Science: Hybrid Vigor and Stress

In polyploid crops (like Wheat or Maize), distinguishing between homeologs (A, B, D genomes) is difficult with short reads due to high sequence similarity.

Impact: Long reads span the polymorphisms that distinguish homeologs. Researchers can determine if the ribosome prefers the "A-genome" isoform over the "B-genome" isoform under drought stress, providing targets for breeding resilient crops.

Sample Requirements and Recommendations

To ensure high-quality long-read data, the input material must have high RNA integrity (RIN) and sufficient mass, as the RNC enrichment process results in material loss compared to total RNA extraction.

Cultured Cells	≥ 5 × 10⁷ cells	≥ 2 × 10⁷ cells	Cells must be in log phase (actively growing).
Fresh Tissue	≥ 200 mg	≥ 100 mg	Process immediately or flash freeze in liquid N2.
Frozen Tissue	≥ 300 mg	≥ 150 mg	Avoid any freeze-thaw cycles. RNCs are fragile.
Plant Tissue	≥ 500 mg	≥ 300 mg	High polysaccharide/phenolic samples require optimization.

Critical Notes:

RIN Value: Starting RNA RIN should be ≥ 7.0 (Mammalian) for optimal full-length library construction.
Biological Replicates: We strongly recommend a minimum of 3 biological replicates per condition to perform statistical differential analysis.
Inhibitors: Please consult with our technical team regarding the specific translation inhibitor suitable for your organism before sampling.

Data Delivery

We deliver data in industry-standard formats compatible with major visualization tools (IGV, UCSC Genome Browser):

Raw Data: BAM/FASTQ files (CCS reads for PacBio, POD5/FASTQ for Nanopore).
Processed Files:
- GFF3/GTF: Polished annotation files of reconstructed translating isoforms.
- SQANTI Classification Report: Detailed CSV categorizing every isoform.
Quantification Matrices: Isoform-level expression tables (TPM).
Final Report: A detailed PDF report containing QC metrics (Read length distribution, completeness), methods, and figure interpretations.

Frequently Asked Questions (FAQ)

- Q: Can this method quantify protein levels directly?
  - A: No. It quantifies the number of mRNA molecules associated with ribosomes. While this correlates strongly with protein synthesis (more so than Total RNA), it does not measure protein degradation or stability.
- Q: How does this differ from Ribo-seq?
  - A: Ribo-seq digests the RNA to ~30nt footprints to map ribosome positions at codon resolution. Long-read RNC-seq keeps the RNA intact to map the structure of the transcript. Ribo-seq is better for translational pausing; Long-read RNC-seq is better for isoform discovery.
- Q: Do you support clinical samples?
  - A: We accept clinical research samples (RUO only), but we require higher input amounts (fresh frozen tissue) than standard RNA-seq. FFPE samples are generally not suitable due to RNA degradation.
- Q: Is this suitable for comparative studies (e.g., Drug vs. Control)?
  - A: Yes. By including biological replicates, we can perform differential isoform usage analysis to see how treatments affect which isoforms are translated.