What is circRNA translation, and why is it important?

Circular RNAs (circRNAs) can serve as noncanonical templates for protein synthesis, producing short peptides with regulatory or signaling roles. Understanding circRNA translation helps uncover hidden layers of gene regulation and provides new biomarkers or therapeutic targets in cancer, neuroscience, and developmental biology.

How does Ribo-seq detect circRNA translation?

Ribo-seq identifies ribosome-protected fragments on RNA molecules, showing where translation actively occurs. When reads map to back-spliced junctions, this provides direct evidence that a circRNA is being translated into a peptide.

Can this service validate peptides encoded by circRNAs?

Yes. CD Genomics integrates mass spectrometry–based proteomics with Ribo-seq and RNA-seq data to experimentally confirm the existence of circRNA-derived peptides, ensuring that results are biologically verifiable and publication-ready.

What types of samples are suitable for circRNA translation analysis?

We accept cell lines, tissues, or purified RNA and protein extracts from human, mouse, and rat samples. Samples should have high RNA integrity and sufficient biomass for parallel sequencing and proteomic validation.

What advantages does this service provide over standard RNA-seq?

Unlike conventional RNA-seq, which measures transcription levels, this workflow reveals the active translation landscape of circRNAs, confirming which transcripts actually produce peptides. It provides a functional view of the transcriptome through ribosome occupancy and proteomic validation.

Can this workflow identify novel circRNA-derived peptides not annotated in public databases?

Yes. De novo peptide discovery pipelines compare ribosome footprints and LC–MS/MS spectra to reveal novel circRNA-encoded peptides that have not been previously annotated, expanding the known coding potential of the noncoding transcriptome.

How are false positives minimized in circRNA translation detection?

False-positive signals are reduced through multiple layers of verification: ribosome footprint precision mapping, junction read confirmation, long-read transcript reconstruction, and proteomic evidence. Only circRNAs with consistent support across datasets are reported as translated.

Can circRNA translation analysis be applied to cancer or clinical studies?

Absolutely. The platform is ideal for identifying tumor-specific circRNAs or neoantigens, understanding drug response, and discovering novel biomarkers associated with disease progression or therapeutic resistance.

Is bioinformatics support included?

Yes. All projects include complete data processing, quality control, and functional annotation. Custom analyses such as GO/KEGG pathway enrichment, codon usage profiling, and network construction are also available upon request.

How do I get started with a circRNA translation project?

Contact CD Genomics with a short project description and sample information. Our scientific team will design an experimental and analysis plan that matches your objectives, budget, and sample type.

Comprehensive circRNA Translation Analysis Service | Ribo-seq, RNA-seq, and Proteomics for Functional Peptide Discovery

Identification and Functional Mechanism of Circular RNA-Translated Proteins

CD Genomics provides an integrated service for the identification and functional characterization of proteins translated from circular RNAs (circRNAs). By combining Standard Ribo-seq, Enhanced Ribosome Profiling, RNA-seq, and proteomics technologies, our platform uncovers hidden translational activities within noncoding RNAs and defines their biological roles in gene regulation, cancer biology, and neurodevelopment. This service enables researchers to map the full landscape of circRNA translation and reveal novel regulatory peptides driving cell function.

Why Choose This Service

l High-resolution Ribo-seq profiling for active translation detection
A comprehensive multi-omics integration combining transcriptomics and proteomics
The discovery of novel circRNA-encoded peptides verified by LC–MS/MS
l Mechanistic insight into circRNA translation regulation and functional pathways

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circRNA translation workflow integrating Ribo-seq, RNA-seq, and proteomics for peptide identification and functional mechanism analysis.

High-resolution ribosome profiling (Ribo-seq)
Discovery of circRNA-encoded peptides
Integrated multi-omics validation
Functional mechanism interpretation

Background

Circular RNAs (circRNAs) are covalently closed RNA molecules that lack 5′ caps and 3′ tails, conferring them exceptional stability against exonuclease degradation. Once regarded as noncoding, recent studies have revealed that many circular RNAs (circRNAs) possess open reading frames (ORFs) capable of encoding functional peptides. These discoveries redefine our understanding of gene regulation and expand the landscape of translational biology.

In cancer, neurodegenerative disorders, and metabolic diseases, specific circular RNAs (circRNAs) have been shown to produce peptides that regulate cell proliferation, stress response, and signaling pathways. For example, circ-FBXW7, circ-SHPRH, and circPINTexon2 encode small proteins that suppress glioma progression. However, identifying and validating these translation events remains technically challenging due to low abundance, complex splicing patterns, and limited peptide databases.

CD Genomics addresses these challenges through an integrated multi-omics approach combining Ribo-seq, RNA-seq, and proteomics. This strategy captures ribosome-protected RNA fragments, quantifies transcriptional activity, and confirms peptide expression via LC–MS/MS. Our platform delivers high-confidence evidence for circRNA translation and provides mechanistic insights into how these novel peptides contribute to disease processes.

Recommended Reading:

[Long-Read RNA Sequencing] | [m6A-seq Service]

Research Objectives

The Identification and Functional Mechanism of Circular RNA-Translated Proteins Service is designed to help researchers systematically explore the coding potential of circRNAs and reveal their biological functions across diverse systems. Our primary objectives are as follows:

Identify translatable circRNAs using high-resolution Ribo-seq to detect ribosome-protected fragments and define actively translated regions.
Characterize the peptide-coding capacity of circRNAs by integrating RNA-seq, long-read sequencing, and LC–MS/MS proteomics, ensuring precise detection of translated products.
Decode regulatory mechanisms such as m6A modification, IRES-mediated translation initiation, and alternative splicing that control circRNA-derived peptide synthesis.
Elucidate the biological functions of circRNA-encoded peptides in key pathways related to cancer, neurodevelopment, and stress response.
Provide reliable translational biomarkers and potential therapeutic targets for precision medicine and disease mechanism research.

By bridging transcriptomics and proteomics, CD Genomics enables comprehensive analysis of circRNA translation—from ribosome occupancy to peptide function—delivering data-driven insights that advance basic and translational research.

Recommended Reading: [Ribo-seq Service]

Research Contents

Our circRNA translation analysis service provides an end-to-end workflow covering experimental detection, peptide validation, and mechanistic interpretation. Each phase is carefully designed to generate comprehensive insights into the translational activity of circular RNAs.

Multi-Omics Data Generation

Perform Ribo-seq to capture ribosome-protected fragments (RPFs) and identify actively translated circRNAs.
Conduct RNA-seq and long-read sequencing to reconstruct full-length circRNA isoforms and quantify their expression levels.
Apply LC–MS/MS proteomics to detect and verify peptides derived from circRNA open reading frames.

Translational Activity Profiling

Evaluate global changes in translation efficiency between experimental and control groups.
Identify circRNAs showing differential ribosome occupancy or altered peptide expression under disease or treatment conditions.
Construct codon usage maps and translation initiation profiles for functional circRNA transcripts.

Peptide and Antigen Discovery

Discover tumor-specific or tissue-specific peptides encoded by circRNAs.
Identify neoantigens and immunogenic peptides with potential diagnostic or therapeutic value.

Functional and Mechanistic Analysis

Investigate how circRNA-derived peptides modulate signaling pathways, transcriptional networks, and protein interactions.
Integrate omics data to construct circRNA–peptide–pathway regulatory networks.
Validate candidate peptides through in vitro functional assays or immunodetection methods.

CD Genomics provides a high-confidence, reproducible framework for translating raw omics data into meaningful biological understanding—linking circular RNA translation to functional outcomes.

Recommended Reading:

[Bioinformatics Data Integration]

Scientific Questions Addressed

The circRNA Translation Identification and Mechanism Service from CD Genomics is built to resolve key biological questions that traditional transcriptomics or proteomics alone cannot answer. By integrating Ribo-seq, RNA-seq, and proteomic validation, this workflow helps researchers decode the hidden translational potential of circular RNAs.

Key Scientific Questions

Which circRNAs are actively translated?
Using ribosome footprinting (Ribo-seq), we identify circRNAs bound by ribosomes and quantify their translation activity across experimental conditions.
How are translation events regulated?
Our analysis explores translation control via m6A modifications, internal ribosome entry sites (IRES), and noncanonical start codons, revealing new modes of peptide synthesis.
What are the functions of circRNA-encoded peptides?
We characterize how these peptides participate in cell signaling, proliferation, differentiation, and disease progression, using integrated transcriptomic and proteomic profiling.
Can circRNA-derived peptides serve as disease biomarkers or therapeutic targets?
By identifying tumor-specific or stress-induced peptides, we support biomarker discovery and enable precision diagnostics and therapeutic development.

Scientific Impact

This service offers a systematic framework for understanding how noncoding RNAs contribute to the proteome. It bridges the gap between RNA structure and protein function, advancing both basic molecular research and translational medicine.

Key Technologies

CD Genomics integrates advanced sequencing and proteomic technologies to achieve high-confidence detection of circRNA translation and peptide validation. Each platform complements the others, ensuring data accuracy, reproducibility, and biological depth.

Ribo-seq (Standard Ribo-seq, Enhanced Ribosome Profiling)

Captures ribosome-protected RNA fragments (RPFs) to pinpoint regions actively undergoing translation.
Maps ribosome occupancy at single-nucleotide resolution, identifying translation start sites, open reading frames (ORFs), and uORFs.
Provides direct evidence of circRNA–ribosome association, revealing dynamic translation activity under physiological or disease conditions.

RNA-seq and Long-Read Sequencing

RNA-seq quantifies linear and circular RNA expression, while long-read sequencing (PacBio / Oxford Nanopore) reconstructs full-length circRNA isoforms.
Enables detection of back-splicing junctions, alternative exon usage, and noncanonical transcripts with potential coding capacity.
Offers complete transcriptome coverage to correlate transcriptional regulation with translational outcomes.

Proteomics (LC–MS/MS)

High-resolution mass spectrometry validates peptides encoded by circRNA ORFs.
Detects low-abundance, short, or tissue-specific peptides that are difficult to capture by sequencing alone.
Provides quantitative confirmation of translation events and reveals post-translational modifications relevant to peptide function.

Bioinformatics Integration Platform

Proprietary pipelines unify data from Ribo-seq, RNA-seq, and LC–MS/MS.
Conducts multi-layer feature extraction, including ORF prediction, m6A motif annotation, and functional enrichment.
Delivers interactive reports and network visualizations connecting circRNAs, peptides, and biological pathways.

Quality Control and Data Reproducibility

Stringent QC checkpoints ensure sequencing depth, read quality, and mapping accuracy.
Cross-validation between transcriptome and proteome datasets reduces the number of false-positive translation calls.
All workflows comply with international sequencing QC standards (Phred ≥ Q30) and are suitable for publication or downstream clinical research.

Experimental Workflow

CD Genomics offers a comprehensive, fully integrated multi-omics workflow for investigating circRNA translation, from initial sample preparation to peptide-level validation. Each stage of our workflow is designed for precision, reproducibility, and functional interpretation.

Sample Preparation

Step 1 – Sample Collection and Preparation

Acceptable samples include cultured cells, fresh or frozen tissues, and RNA–protein extracts.
High-quality total RNA and protein are extracted for both sequencing and mass spectrometry analysis.

Sample Preparation

Step 2 – Ribo-seq Library Construction and Sequencing

Ribosome-protected RNA fragments (RPFs, ~28 nt) are isolated following nuclease digestion.
Libraries are constructed using strand-specific protocols and sequenced to single-base resolution.
This step reveals ribosome occupancy, open reading frames (ORFs), and translation start sites.

Sample Preparation

Step 3 – RNA-seq / Long-Read Sequencing

Conducted in parallel to map full-length circRNA isoforms, quantify expression, and identify back-splicing junctions.
Long-read sequencing (Oxford Nanopore or PacBio) provides high-confidence annotation of circRNA structure and coding regions.

Sample Preparation

Step 4 – Proteomics Validation (LC–MS/MS)

Mass spectrometry confirms the existence of peptides predicted from circRNA ORFs.
Quantitative proteomic profiling detects tissue- or condition-specific translation products.

Sample Preparation

Step 5 – Bioinformatics and Multi-Omics Integration

Ribosome footprint data, transcriptome information, and proteomic spectra are integrated into a unified database.
Computational pipelines identify translation efficiency, m6A sites, codon usage, and functional pathways.

Sample Preparation

Step 6 – Reporting and Functional Interpretation

Deliverables include detailed reports on translated circRNAs, peptide sequences, expression profiles, and pathway enrichment analysis.
Optional downstream validation (e.g., luciferase assay, Western blot) can be performed upon request.

Technical Highlights

Precision Sequencing: Dual-platform Ribo-seq + RNA-seq ensures accurate detection of active translation events.
Comprehensive Validation: LC–MS/MS proteomics confirms translation at the protein level.
Cross-Omics Integration: Bioinformatics links RNA features to peptide evidence and biological function.
Customizable Modules: Flexible design to support cancer, neuroscience, or developmental biology research.

circRNA-encoded peptide research workflow integrating Ribo-seq, RNA-seq, proteomics, and functional validation.

Analysis Components

Our circRNA Translation Analysis Service delivers an integrated suite of bioinformatics and statistical analyses, converting raw sequencing and proteomic data into interpretable biological insights. Each analytical layer contributes to precise identification, validation, and functional annotation of circRNA-derived peptides.

Analysis Category	Description	Key Outcomes / Deliverables
Data Preprocessing & Quality Control	Trimming, adaptor removal, and quality assessment of Ribo-seq, RNA-seq, and proteomics datasets.	High-quality, clean reads ready for downstream analysis.
circRNA Identification	Detection of circular RNAs through back-splice junction mapping and de novo assembly.	Annotated list of circRNAs with genomic coordinates and expression levels.
Ribosome Footprint Mapping	Alignment of ribosome-protected fragments (RPFs) to identify actively translated circRNAs.	Translation efficiency matrix and ribosome occupancy plots.
Open Reading Frame (ORF) Prediction	Computational detection of canonical and noncanonical start sites within circRNAs.	Catalog of predicted ORFs with coding potential scores.
Translation Efficiency & Codon Usage Analysis	Quantitative assessment of translational activity and codon bias profiling.	Global translation landscape and circRNA-specific codon usage maps.
m6A and IRES Element Annotation	Prediction of m6A modification motifs and internal ribosome entry sites driving translation.	Regulatory feature table linking translation initiation to RNA modification.
Proteomic Validation (LC–MS/MS)	Peptide-spectrum matching and quantitative analysis using mass spectrometry data.	Experimentally confirmed circRNA-derived peptides with confidence scores.
Functional Enrichment Analysis	GO and KEGG pathway analysis to determine biological processes regulated by translated circRNAs.	Functional annotation report and pathway enrichment visualization.
Network Construction	Integration of circRNA–peptide–protein interaction networks.	Network diagrams and functional connectivity models.
Comprehensive Reporting	Consolidated visual summaries, figures, and interpretable tables.	Publication-ready report containing results, methods, and data interpretation.

This multi-tiered analysis pipeline ensures that every circRNA translation event is validated, quantified, and functionally contextualized, providing researchers with actionable insights into translational regulation and peptide function.

Key Advantages

Integrated Multi-Omics Workflow – Combines Ribo-seq, RNA-seq, and LC–MS/MS proteomics for complete coverage from RNA to peptide.

High Sensitivity and Specificity – Detects low-abundance circRNA translation events and minimizes false positives through cross-omics validation.

Comprehensive Mechanistic Insights – Links transcription, translation, and function, uncovering how circRNA-derived peptides regulate cellular pathways.

Flexible and Customizable Design – Supports a wide range of research areas, from cancer biology to neuroscience and metabolic regulation.

Publication-Ready Reporting – Delivers clear visualizations, data summaries, and functional annotations suitable for journal submission or grant applications.

Applications

The circRNA Translation Identification and Functional Mechanism Service supports a broad range of research fields by revealing how circular RNAs contribute to the proteome and cellular regulation.

Cancer and Disease Research

Identify oncogenic or tumor-suppressive circRNA-derived peptides in cancer models.
Identify tumor-specific neoantigens for immunotherapy or the development of diagnostic biomarkers.
Explore how abnormal circRNA translation contributes to disease progression, drug resistance, and metabolic reprogramming.

Neurobiology and Development

Characterize brain-specific circRNA translation involved in neuronal differentiation and synaptic function.
Uncover peptides regulating neurodegenerative pathways or stress responses in model organisms.

Functional Genomics and Transcriptome Regulation

Study noncanonical translation mechanisms such as IRES- or m6A-driven initiation.
Link transcriptional regulation to protein-level outcomes using integrated RNA and peptide data.

Biomarker and Therapeutic Discovery

Discover circRNA-encoded peptides as potential biomarkers for disease diagnosis and prognosis.
Identify peptide candidates with therapeutic relevance for targeted drug development.

By bridging RNA sequencing and proteomics, CD Genomics enables researchers to uncover hidden coding functions within the noncoding transcriptome—transforming basic molecular findings into actionable biomedical insights.

Deliverables

CD Genomics provides a complete set of outputs designed for scientific publication and downstream research. All results are fully annotated, quality-controlled, and ready for integration into your laboratory workflow.

Annotated circRNA catalog — including genomic coordinates, expression levels, and predicted ORFs.
Ribo-seq and RNA-seq datasets — cleaned, aligned, and normalized read files with translation efficiency metrics.
Proteomics validation report — verified circRNA-derived peptides with confidence scores and spectra.
Functional analysis summary — GO/KEGG pathway enrichment and circRNA–peptide network visualization.
Comprehensive data report — publication-ready figures, tables, and interpretation notes in Excel/PDF format.

Our deliverables ensure transparency, reproducibility, and easy integration with your existing bioinformatics or proteomics pipelines.

Sample Requirements

Sample Type	Requirements	Notes
Cell Samples	≥ 1 × 10⁷ cells per sample	Fresh, viable cells preferred; provide both control and experimental groups.
Tissue Samples	≥ 100 mg per sample (fresh or frozen)	Avoid repeated freeze–thaw cycles; RNase-free handling required.
RNA Samples	≥ 5 µg total RNA, concentration ≥ 100 ng/µL, OD₂₆₀/₂₈₀ = 1.8–2.2	DNase-treated, RIN ≥ 7.0; RNA integrity is critical for Ribo-seq and circRNA detection.
Protein Extracts (optional)	≥ 100 µg total protein per sample	Used for LC–MS/MS validation of circRNA-derived peptides.
Species Supported	Human, mouse, rat (other species require evaluation)	Reference genome and annotation must be available.
Replicates	≥ 3 biological replicates per group	Recommended design: Control vs. Treatment (3 vs. 3) or larger.

Additional Notes:

For clinical or low-yield samples, please contact us to discuss customized extraction and library construction strategies.
Both Ribo-seq and RNA-seq libraries are constructed using rRNA-depleted protocols to ensure accurate circRNA detection.
All samples should be shipped on dry ice with complete metadata (sample ID, treatment, and biological context).

Frequently Asked Questions (FAQs)

- What is circRNA translation, and why is it important?
  - Circular RNAs (circRNAs) can serve as noncanonical templates for protein synthesis, producing short peptides with regulatory or signaling roles. Understanding circRNA translation helps uncover hidden layers of gene regulation and provides new biomarkers or therapeutic targets in cancer, neuroscience, and developmental biology.
- How does Ribo-seq detect circRNA translation?
  - Ribo-seq identifies ribosome-protected fragments on RNA molecules, showing where translation actively occurs. When reads map to back-spliced junctions, this provides direct evidence that a circRNA is being translated into a peptide.
- Can this service validate peptides encoded by circRNAs?
  - Yes. CD Genomics integrates mass spectrometry–based proteomics with Ribo-seq and RNA-seq data to experimentally confirm the existence of circRNA-derived peptides, ensuring that results are biologically verifiable and publication-ready.
- What types of samples are suitable for circRNA translation analysis?
  - We accept cell lines, tissues, or purified RNA and protein extracts from human, mouse, and rat samples. Samples should have high RNA integrity and sufficient biomass for parallel sequencing and proteomic validation.
- What advantages does this service provide over standard RNA-seq?
  - Unlike conventional RNA-seq, which measures transcription levels, this workflow reveals the active translation landscape of circRNAs, confirming which transcripts actually produce peptides. It provides a functional view of the transcriptome through ribosome occupancy and proteomic validation.
- Can this workflow identify novel circRNA-derived peptides not annotated in public databases?
  - Yes. De novo peptide discovery pipelines compare ribosome footprints and LC–MS/MS spectra to reveal novel circRNA-encoded peptides that have not been previously annotated, expanding the known coding potential of the noncoding transcriptome.
- How are false positives minimized in circRNA translation detection?
  - False-positive signals are reduced through multiple layers of verification: ribosome footprint precision mapping, junction read confirmation, long-read transcript reconstruction, and proteomic evidence. Only circRNAs with consistent support across datasets are reported as translated.
- Can circRNA translation analysis be applied to cancer or clinical studies?
  - Absolutely. The platform is ideal for identifying tumor-specific circRNAs or neoantigens, understanding drug response, and discovering novel biomarkers associated with disease progression or therapeutic resistance.
- Is bioinformatics support included?
  - Yes. All projects include complete data processing, quality control, and functional annotation. Custom analyses such as GO/KEGG pathway enrichment, codon usage profiling, and network construction are also available upon request.
- How do I get started with a circRNA translation project?
  - Contact CD Genomics with a short project description and sample information. Our scientific team will design an experimental and analysis plan that matches your objectives, budget, and sample type.

References:

Zhang H., Jiang L., Sun D., Hou J., Ji Z. (2018). CircRNA: a novel type of biomarker for cancer. Breast Cancer (Tokyo, Japan), 25(1).
Chen H., Liu Y., Li P., Zhu D. (2018). Novel role of FBXW7 circular RNA in repressing glioma tumorigenesis. Journal of the National Cancer Institute.
Zhang M., Huang N., Luo J., Yan S., Xiao F., Chen W., Gao X., Zhao K., Zhou H., Li Z., Liu X., Bo Z. (2018). A novel protein encoded by the circular form of the SHPRH gene suppresses glioma tumorigenesis. Oncogene, 37(13).
Wu Y., Zhang Y., Zhang Y., Wang J. (2017). CircRNA hsa_circ_0005105 upregulates NAMPT expression and promotes chondrocyte extracellular matrix degradation by sponging miR-26a. Cell Biology International, 41(12).
Yang Q., Du W., Van Weining, Awan F., Fang L., Ma J., Li X., Zeng Y., Yang Z., Dong J., Khorshidi Azam, Yang B. (2017). A circular RNA promotes tumorigenesis by inducing c-myc nuclear translocation. Cell Death and Differentiation, 24(9).
Xia W., Qiu M., Chen R., Wang S., Leng X., Wang J., Xu G., Lin Y., Yin R. (2016). Circular RNA has_circ_0067934 is upregulated in esophageal squamous cell carcinoma and promotes proliferation. Scientific Reports, 6.
Chen J., Li Q., Zheng Q., Bao C., Chen B., Zheng L., Xu Y., Long Z., Zhou Y., Zhu H., Wang X., Huang Y. (2017). Circular RNA profile identifies circPVT1 as a proliferative factor and prognostic marker in gastric cancer. Journal of Cancer Letters, 388.
Ruiz-Orera J., Messeguer X., Subirana J. A., Alba M. M. (2014). Long non-coding RNAs as a source of new peptides. eLife, 3:e03523.
Xu L., Wang W., Chen J. (2017). Recent progress in mass spectrometry proteomics for biomedical research. Science China Life Sciences, 60(10):1093–1113.
Zhang M., Zhao K., Xu X., Yan S., Wei P., Liu H., Zhou H., Yang X., Huang N., Liu X., Bo Z. (2018). A peptide encoded by circular form of LINC-PINT suppresses oncogenic transcriptional elongation in glioma. Nature Communications, 9(1): 4475.