GlycoRNA-seq: Profiling Sugar-Modified Small RNAs with Precision
Uncover sugar-modified sncRNAs with high specificity and sensitivity, beyond the limits of conventional RNA sequencing.
Key Highlights
- Detect glycosylated sncRNAs (YRNA, tRNA, snoRNA, snRNA, rRNA) with precision
- Two enrichment strategies: Ac4ManNAz metabolic labeling or rPAL chemistry
- Sensitive profiling of low-abundance GlycoRNAs across multiple sample types
- Research-ready analysis including differential expression, glycosylation sites, and functional annotation
- Support for integration with mass spectrometry for glycan structure insights
Why GlycoRNA Matters
For decades, glycosylation was thought to occur only on proteins and lipids. The discovery of glycosylated RNAs (GlycoRNAs) introduced a new layer of biology that is reshaping how we understand immune regulation, cell signaling, and molecular interactions at the cell surface.
GlycoRNAs are primarily small non-coding RNAs (sncRNAs) — including YRNAs, snoRNAs, snRNAs, tRNAs, and rRNAs — decorated with complex sugar chains. Positioned at the cell surface, these molecules are strategically placed to influence critical processes:
- Immune regulation and inflammation – GlycoRNAs interact with receptors such as Siglecs and P-selectin, modulating immune cell recruitment and inflammatory signaling.
- Cell-to-cell communication – By displaying glycan structures on RNA, cells add a new dimension to extracellular recognition and information transfer.
- Biomarker potential – Altered glycoRNA profiles are emerging as candidate indicators in immune disorders, cancer, and infection models.
Without a dedicated sequencing approach, these sugar-modified RNAs remain invisible to standard RNA-seq. GlycoRNA-seq provides the sensitivity and specificity researchers need to uncover this overlooked dimension of RNA biology.
Our Approach: Capturing GlycoRNAs
Standard RNA-seq methods fail to distinguish glycosylated RNAs from unmodified molecules. To overcome this limitation, GlycoRNA-seq combines specialized enrichment chemistries with next-generation sequencing, ensuring that sugar-modified RNAs are captured and profiled with accuracy.
We provide two complementary approaches. Choosing the right one depends on your sample type and experimental setup:
Ac4ManNAz Metabolic Labeling + Click Chemistry
- Incorporates azide-modified sugars into RNA through cellular metabolism.
- Biotinylation via click chemistry allows selective pull-down of glycosylated RNAs.
- Best choice if you work with actively growing cultured cells and can apply metabolic labeling during cell preparation.
rPAL (Periodate Oxidation and Aldehyde Labeling)
- Oxidizes terminal glycans to aldehydes, which are then coupled to biotin for capture.
- Compatible with cells, tissues, and pre-extracted RNA.
- Recommended for preserved samples, tissues, or cases where metabolic labeling is not feasible.
By offering both methods, GlycoRNA-seq ensures that whether you are analyzing living cell cultures or archival tissue samples, you can achieve reliable enrichment of glycosylated RNAs and obtain a dataset that truly represents their biological roles.
Technical Advantages
GlycoRNA-seq is designed to overcome the blind spots of conventional RNA sequencing, providing researchers with a clear and reliable view of sugar-modified RNAs. Key strengths include:
Enrichment strategies allow profiling of low-abundance glycoRNAs that are often invisible to standard small RNA-seq.
Captures multiple classes of glycosylated sncRNAs, including YRNAs, tRNAs, snoRNAs, snRNAs, and rRNAs, in a single experiment.
Enables accurate quantification of glycoRNA expression across conditions, highlighting both global changes and site-specific modifications.
Integrated analysis links glycoRNA profiles to biological pathways, with the option to combine with mass spectrometry for glycan structure and composition insights.
Together, these advantages ensure that GlycoRNA-seq delivers not only a more complete RNA profile, but also the biological context necessary to drive new discoveries.
Applications for Your Research
As a researcher, you already know the limitations of conventional RNA-seq: it cannot distinguish sugar-modified RNAs from their unmodified counterparts. GlycoRNA-seq fills that gap, giving you access to insights that would otherwise remain hidden.
- Probing immune regulation
In immune-related projects, you may need to understand why certain cells recruit or respond differently. GlycoRNA-seq allows you to track glycoRNAs binding to receptors such as Siglecs or P-selectin, helping you link molecular changes to immune cell behavior. - Studying intercellular communication
When investigating how cells exchange information, you can use this service to capture glycoRNAs displayed on the cell surface—molecules that play a direct role in recognition and signaling events. - Searching for biomarkers
If your work involves identifying markers of disease or treatment response, glycoRNA patterns uncovered by sequencing may point to previously overlooked RNA species with diagnostic or mechanistic relevance. - Evaluating experimental treatments
In drug or perturbation studies, GlycoRNA-seq lets you monitor how interventions reshape RNA glycosylation, providing a new layer of data to interpret molecular effects. - Exploring regulatory biology
For projects on RNA stability, translation, or development, glycosylation adds an unexplored regulatory dimension. Sequencing these modifications helps explain results that pure expression analysis cannot.
By framing your research questions in terms of glycoRNAs, you gain a powerful tool to connect surface-level RNA modifications with cellular function.
Service Workflow: From Inquiry to Data Delivery
When you choose GlycoRNA-seq, you want a workflow that is clear, reliable, and easy to follow. We keep the process straightforward, so you can stay focused on your science:
1. Initial Consultation
- Share your research goals and sample type with us.
- We help you decide whether Ac4ManNAz metabolic labeling or rPAL chemistry is the best fit for your project.
2. Sample Submission
- You prepare and ship your cells, tissues, or RNA according to our simple guidelines.
- Our team provides clear instructions for handling and shipping, so your samples arrive in optimal condition.
3. Enrichment & Library Preparation
- Your samples are processed with the selected enrichment strategy.
- We construct high-quality small RNA libraries to maximize sequencing accuracy.
4. Sequencing & Data Analysis
- Deep sequencing is performed, followed by a comprehensive bioinformatics pipeline.
- Results include detection, quantification, and annotation of glycoRNAs, with clear comparisons across your experimental conditions.
5. Data Delivery & Support
- You receive raw data, processed files, and a detailed analysis report.
- Our specialists remain available to discuss results and support your next steps.
This workflow ensures that from the moment you contact us to the moment you analyze your results, the process is transparent and designed around the needs of researchers.
Data Analysis
Our bioinformatics pipeline provides both standard and advanced analysis options, ensuring that your GlycoRNA-seq data are processed, annotated, and interpreted with clarity.
Basic Analysis
- Filtering of raw reads and quality control
- Genome alignment for accurate mapping
- Comparison against non-coding RNA databases (tRNA, rRNA, etc.)
- Length distribution and classification of sncRNAs
- Quantification of each sncRNA category
- Differential expression analysis across sample groups (e.g., tsRNA, rsRNA, piRNA)
- Clustering of differentially expressed sncRNAs (for biological replicates only)
Advanced Analysis
- Top 20 sncRNA profiles presented in pie charts and bar charts
- Custom analysis for up to 50 user-selected sncRNAs
- Target gene prediction for selected sncRNAs
- Functional enrichment via Gene Ontology (GO) analysis
- Pathway interpretation through KEGG analysis
This two-tiered approach ensures that you receive both essential quality-driven insights and in-depth functional interpretations, adaptable to the scope of your project.
What You'll Get from Our GlycoRNA-seq Service
Clear, structured outputs designed to accelerate your glycoRNA research.
Comprehensive GlycoRNA Profiles
Fully annotated datasets covering glycosylated sncRNAs (YRNA, tRNA, snoRNA, snRNA, rRNA), including sequence information, classification, and abundance levels—ready for direct comparison across conditions.
Differential Expression & Functional Insights
Quantitative expression tables, differential analysis results, and clustering outputs, complemented by GO and KEGG enrichment to link glycoRNA dynamics with biological pathways.
Publication-Ready Visualizations
High-quality charts and plots, including sncRNA length distributions, top-ranked sequence charts, heatmaps, and clustering diagrams—optimized for both data interpretation and scientific presentations.
Transparent Analysis Records
Detailed documentation of the bioinformatics pipeline, including QC metrics, alignment statistics, and database references, ensuring reproducibility and traceability.
Optional Add-Ons
Custom target gene predictions, advanced motif discovery, glycan structure interpretation (via MS integration), or tailored data formats (Excel, Cytoscape-ready files) to fit your downstream research needs.
Sample Requirements
To ensure reliable enrichment and sequencing, please prepare your samples according to the following guidelines. Both Ac4ManNAz and rPAL capture methods are supported; select the method that best fits your study design.
| Sample Type | Ac4ManNAz Method | rPAL Method | Notes |
|---|---|---|---|
| Cells | ≥ 3 × 10⁶ cells | ≥ 2 × 10⁶ cells | Use actively growing cells for Ac4ManNAz labeling |
| Tissue | Not applicable | RNA later–preserved tissue (≥ 0.2 cm; ~25 mg yields ~30 μg RNA) | Suitable for rPAL only |
| Whole Blood | Not applicable | Recommended ≥ 5 mL (minimum 3 mL) | rPAL-compatible |
| Total RNA | ≥ 50 μg (Ac4ManNAz-labeled RNA) | ≥ 30 μg | RNA integrity recommended (RIN ≥ 6) |
Experimental Design
- At least 2 vs 2 biological replicates are required.
- 3 vs 3 or higher replicate numbers are strongly encouraged for robust statistical analysis.
Additional Notes
- For Ac4ManNAz labeling, culture media should contain 100 μM Ac4ManNAz during incubation.
- Detailed pre-treatment protocols and shipping instructions are available upon request.