What is RNC-seq and what does it measure?

RNC-seq measures RNA associated with ribosome–nascent chain complexes, enriching for RNAs in a translation-active state to enable profiling of translation-associated transcript composition and abundance.

RNC-seq vs RNA-seq: why can the answers differ?

RNA-seq reports total RNA abundance, whereas RNC-seq focuses on RNAs engaged with translation machinery. A transcript may be abundant but not actively engaged in translation, or vice versa.

How do I choose poly(A) enrichment vs rRNA depletion for RNC-seq?

Poly(A) enrichment is recommended for targeting translating coding mRNA in high-quality eukaryotic samples. rRNA depletion is preferred when retention of lncRNA or circRNA is required, RNA quality is lower, or the research involves non-poly(A) biology such as viruses, prokaryotes, or non-model organisms.

Can RNC-seq support circRNA translation studies?

Yes. A Nature Communications study utilized RNC-seq to identify circRNAs in RNC-associated RNA and applied defined thresholds for candidate selection and differential analysis.

How is RNC-seq different from ribosome footprinting (Ribo-seq)?

Ribo-seq sequences ribosome-protected fragments (22–35 nucleotide footprints) to infer ribosome positions on transcripts, whereas RNC-seq sequences translation-associated RNAs to profile which RNAs are actively translating. These methods reflect different aspects of translation and are not mutually replaceable.

When is rRNA depletion the safer default?

When samples lack poly(A) tails, RNA quality is compromised, or the research hypothesis depends on broader RNA classes such as lncRNA or circRNA, rRNA depletion is more appropriate according to the reference selection logic.

What translation-omics method should I add if I need global ribosome loading patterns?

Polysome profiling provides a fraction-based view of free RNA, 40S/60S, 80S, and polysomes, complementing RNC-seq when a global translation-state landscape is required.

Do I need to combine RNC-seq with other assays?

Not always. RNC-seq directly addresses the question of which RNAs are translating. It can be combined with RNA-seq for abundance context, and Ribo-seq or Disome-seq should be considered only if positional or stalling/collision mechanisms are of interest.

RNC-seq Service - Translating mRNA Profiling

RNC-seq Overview

RNC-seq is a translatome sequencing method that profiles RNA bound to ribosome–nascent chain complexes. This approach quantifies translation-active transcripts by isolating RNC-associated RNA and sequencing either poly(A)+ mRNA or rRNA-depleted total RNA, thereby enabling translation-focused comparisons across biological conditions.

RNC-seq is particularly valuable when RNA abundance measured by RNA-seq does not account for observed phenotypes, as only a subset of transcripts are actively engaged in translation at any given time. The two library preparation routes allow researchers to balance signal specificity with RNA-type breadth.

RNC-seq vs RNA-seq, Ribo-seq, and Polysome Profiling

Translation-omics methods address distinct research questions. Selecting the most appropriate method that aligns with the biological hypothesis is essential, with escalation to more complex approaches only as necessary.

RNA-seq	Total RNA / mRNA abundance	Transcript level	Expression baseline and transcript abundance	Cannot distinguish translating vs non-translating RNAs
Polysome profiling	Free mRNA, 40S, 60S, 80S, light/heavy polysomes (sucrose gradient)	Global / fraction-level	Global translation state shifts (mono vs polysome distribution)	Without sequencing, does not identify specific translated transcripts
Ribo-seq	Ribosome-protected fragments after low-dose RNase digestion	22–35 nt footprints, position/codon-level	Start sites (incl. non-AUG), uORFs, pausing, ribosome density	Measures footprints, not full-length translating RNA
Disome-seq	Disome-protected fragments	Collision/stalling-focused	Ribosome collision and co-translational stalling	Specialized; often paired with Ribo-seq
RNC-seq	RNA associated with ribosome–nascent chain complexes	Translating transcript composition; broader RNA types with rRNA depletion	"Which RNAs are actively translating?"	Does not inherently provide ribosome positional footprints

Abstract infographic titled 'Translatomics: The Functional Filter,' visually representing the filtration of total transcriptome mRNA into the active translatome, with icons for **Ribo-seq

Service Portfolio: Two RNC-seq Library Options

Option A: poly(A) Enrichment RNC-seq (RNC-mRNA)

Principle: poly(T) magnetic beads selectively capture poly(A)+ mRNAs for library preparation.

Data focus: translating protein-coding mRNAs.

What this route is best for (from your materials)

Translation activity of protein-coding genes.
High-quality eukaryotic samples (cells, animal tissues).
Studies prioritizing clean quantification with minimal interference from noncoding RNA classes.

What you should not choose this for

Projects where the hypothesis depends on non-poly(A) biology.
Projects where retaining lncRNA/circRNA in the translating pool is required.

Option B: rRNA Depletion RNC-seq (RNC-Total RNA)

Principle: remove rRNA via probe hybridization and/or enzymatic depletion while retaining other RNA types.

Data focus: translation-associated broad RNA classes, including lncRNA and circRNA.

What this route is best for (from your materials)

Screening translation potential of noncoding RNAs (lncRNA/circRNA).
Challenging samples where RNA quality is reduced.
Virus, prokaryote, and non-model organisms without reliable poly(A) tails.

What to expect

Broader information, higher dataset complexity, and a wider RNA-type composition profile compared with poly(A) enrichment.

Bioinformatic Analysis

Package A: Translating mRNA Quant	poly(A) enrichment (RNC-mRNA)	Translating coding transcript abundance; condition comparisons of translation output	Protein-coding translation regulation
Package B: Broad Translating RNA	rRNA depletion (RNC-total RNA)	RNA-type composition including lncRNA/circRNA; candidate discovery lists	Noncoding translation potential; special samples
Package C: Discovery Prioritization	Either route	Candidate filtering logic based on translation-associated enrichment and condition shifts	Disease-state discovery and hypothesis generation

Interpretation guidance

Poly(A) enrichment targets translating coding mRNA and reduces interference from abundant non-target RNAs.
rRNA depletion retains a broader range of RNA types, enabling discovery related to lncRNA and circRNA, but also increases dataset complexity.
RNC-seq answers "what is translating," while Ribo-seq adds "where ribosomes are positioned," and the two are not mutually replaceable.

Applications

RNC-seq is designed to address translation-layer research questions where total RNA abundance is insufficient. The reference materials highlight three primary use cases and several special-sample extensions.

Translational regulation mechanisms

RNC-seq is appropriate for testing whether regulation occurs between transcription and translation, including the following scenarios:

Cases where RNA-seq shows modest change but the phenotype implies altered protein output.
Projects focused on identifying which transcripts are engaged with translation machinery under a specific cell state.
Hypothesis generation for translation control when you need a direct translation-associated RNA readout.

Library strategy alignment

Poly(A) enrichment is recommended when the research focus is on protein-coding translation.
rRNA depletion is preferred when the research hypothesis includes broader RNA biotypes or noncanonical translating transcripts.

Comparing translation output across conditions

The reference materials explicitly position RNC-seq to evaluate changes in translation output across treatments or conditions. Typical experimental designs include comparisons between condition A and condition B, with outcomes such as:

Which transcripts increase or decrease in translation engagement (RNC association).
Whether the translation-active RNA composition shifts under perturbation.
Which candidates merit deeper, higher-resolution translation assays.

Escalation strategies for increased resolution

If follow-up analysis requires positional information, such as start sites, upstream open reading frames (uORFs), or translation pausing, Ribo-seq (ribosome footprinting) should be added. This method sequences 22–35 nucleotide ribosome-protected fragments as described in the reference materials.

Discovery of novel translated transcripts in disease states

The reference materials highlight RNC-seq as a tool for discovering novel translated transcripts in disease contexts. In practice, this includes:

Enriching for RNAs in the translation-associated pool to prioritize candidates beyond abundance alone.
Identifying candidates that show stronger translation engagement shifts than total RNA shifts.
Using rRNA depletion to ensure noncoding RNA classes (lncRNA/circRNA) are retained when discovery requires broad RNA inclusion.

Noncoding RNA translation potential and special sample biology

The reference materials clearly define rRNA depletion as the preferred approach when research needs extend beyond canonical mRNAs:

Translation potential screening for lncRNAs.
Translation potential screening for circRNAs.
Samples with reduced RNA quality where poly(A) capture is not the best fit.
Organisms/samples without poly(A) tails (virus, prokaryotes, non-model organisms).

Method selection within a translation-omics toolkit

The reference materials present a broader translation-omics toolkit. RNC-seq is often used as:

A direct "what is translating" assay (RNC-associated RNA composition and abundance).
A front-end discovery tool that helps decide whether deeper positional assays (Ribo-seq/Disome-seq) are necessary.
A complement to polysome profiling approaches that report a global mono/polysome landscape.
Group design: which conditions you want to compare.

Sample Requirement

Sample Scenario	Recommended Total RNA Input	RNA Quality	Typical Cell Equivalent
poly(A) enrichment RNC-seq	≥ 100–500 ng purified RNA	RIN ≥ 7.0, A260/280 ~1.8–2.0	~1×10^5–5×10^5 cells worth
rRNA depletion RNC-seq	≥ 200–1000 ng purified RNA	RIN ≥ 6.5, broader quality tolerated	~2×10^5–1×10^6 cells worth
Low-input / partial degraded samples	≥ 50–200 ng purified RNA	RIN ≥ 6.0 acceptable	~5×10^4–2×10^5 cells worth
Non-poly(A) / special samples	≥ 300–1000 ng total RNA	Any quality if using rRNA depletion	Depends on sample but similar range

Case Study: circRNA Translation Discovery with RNC-seq

Zhang et al. addressed whether endogenous circRNAs generated from long noncoding RNAs encode functional peptides in glioblastoma. They used ribosome nascent-chain complex-bound RNA sequencing (RNC-seq) to discover peptides potentially encoded by circRNAs and identified an 87–amino-acid peptide encoded by the circular form of LINC-PINT.

To build a circRNA database from both transcriptome and translatome fractions, the authors used rRNA-depleted total RNA and RNC-RNAs from normal human astrocytes (NHA) and U251 glioblastoma cells (see Fig. 1a in the paper). Total RNA and RNC-RNAs were sequenced on an Illumina HiSeq 4000. Reads were mapped to rRNA (Bowtie2) and to the genome (TopHat), followed by an anchor-based approach and find_circ circRNA calling; candidates required ≥2 unique back-spliced reads. They also note collecting 4× more data for RNC-seq than RNA-seq due to a lower identification rate. Nature

Where to display a literature figure (Methods)

Place Figure 1a immediately after the Methods paragraph above. Nature
- Figure caption (for your page): Study design using rRNA-depleted total RNA and RNC-seq (RNC-RNAs) to identify candidate circRNAs in NHA and U251 cells.
- Alt text (SEO-friendly): RNC-seq case study figure showing experimental design for RNC-associated RNA and total RNA sequencing.

Through sequencing, the authors identified 15,189 circRNAs (7,017 from RNA-seq and 12,863 from RNC-RNA sequencing), including circRNAs matched to circBase. They defined differentially expressed circRNAs between NHA and U251 with FDR ≤ 0.01 and fold-change ≥ 2 (shown in Fig. 1f). They cross-matched candidates from total RNA and RNC-RNAs and then focused on noncoding host genes to reduce false positives, prioritizing LINC-PINT for downstream validation.

RNC-seq results figure showing differential circRNA signals from RNC-associated RNA. Differential circRNA analysis between NHA and U251 using total RNA and RNC-associated RNA with FDR ≤ 0.01 and fold-change ≥ 2.

This study illustrates how rRNA depletion + RNC-seq supports circRNA translation-potential discovery by enriching translation-associated RNAs, applying explicit circRNA calling rules (≥2 back-spliced reads), and prioritizing candidates using defined statistical thresholds (FDR ≤ 0.01; fold-change ≥ 2) alongside total RNA context.

FAQ

- 1) What is RNC-seq and what does it measure?
  - RNC-seq measures RNA associated with ribosome–nascent chain complexes, enriching for RNAs in a translation-active state to enable profiling of translation-associated transcript composition and abundance.
- 2) RNC-seq vs RNA-seq: why can the answers differ?
  - RNA-seq reports total RNA abundance, whereas RNC-seq focuses on RNAs engaged with translation machinery. A transcript may be abundant but not actively engaged in translation, or vice versa.
- 3) How do I choose poly(A) enrichment vs rRNA depletion for RNC-seq?
  - Poly(A) enrichment is recommended for targeting translating coding mRNA in high-quality eukaryotic samples. rRNA depletion is preferred when retention of lncRNA or circRNA is required, RNA quality is lower, or the research involves non-poly(A) biology such as viruses, prokaryotes, or non-model organisms.
- 4) Can RNC-seq support circRNA translation studies?
  - Yes. A Nature Communications study utilized RNC-seq to identify circRNAs in RNC-associated RNA and applied defined thresholds for candidate selection and differential analysis.
- 5) How is RNC-seq different from ribosome footprinting (Ribo-seq)?
  - Ribo-seq sequences ribosome-protected fragments (22–35 nucleotide footprints) to infer ribosome positions on transcripts, whereas RNC-seq sequences translation-associated RNAs to profile which RNAs are actively translating. These methods reflect different aspects of translation and are not mutually replaceable.
- 6) When is rRNA depletion the safer default?
  - When samples lack poly(A) tails, RNA quality is compromised, or the research hypothesis depends on broader RNA classes such as lncRNA or circRNA, rRNA depletion is more appropriate according to the reference selection logic.
- 7) What translation-omics method should I add if I need global ribosome loading patterns?
  - Polysome profiling provides a fraction-based view of free RNA, 40S/60S, 80S, and polysomes, complementing RNC-seq when a global translation-state landscape is required.
- 8) Do I need to combine RNC-seq with other assays?
  - Not always. RNC-seq directly addresses the question of which RNAs are translating. It can be combined with RNA-seq for abundance context, and Ribo-seq or Disome-seq should be considered only if positional or stalling/collision mechanisms are of interest.