What types of RNA can be analyzed from exosomes?

Exosomes carry mRNA, lncRNA, circRNA, miRNA, piRNA, tsRNA, and other small non-coding RNAs. Our service offers separate small RNA and long RNA library preparations optimized for each RNA class.

What sample types and volumes are required?

We accept plasma, serum, urine, cell culture supernatant, CSF, and other biofluids. Recommended volumes: ≥500 µL plasma/serum, ≥3 mL urine, ≥10 mL cell culture supernatant.

How do you isolate exosomes from biofluids?

We offer ultracentrifugation, size exclusion chromatography, precipitation, and immunoaffinity capture methods. Method selection is based on sample type, volume, and downstream application.

What is the minimum RNA input required?

Our protocols can generate libraries from as little as 100 pg (small RNA) or 500 pg (long RNA) of exosomal total RNA using carrier-assisted extraction and reduced-cycle amplification.

Can exosomal RNA-seq be used for biomarker discovery?

Yes. Exosomal RNA sequencing is a leading approach for liquid biopsy biomarker discovery. Our service includes differential expression, ROC analysis, and machine learning-based biomarker panel identification.

Exosome RNA Sequencing Service | Biofluid & Exosomal RNA Profiling

Exosome RNA Sequencing Overview

Exosomes are nanosized extracellular vesicles (30–150 nm) secreted by virtually all cell types into surrounding biofluids. They carry a diverse repertoire of RNAs — including messenger RNA (mRNA), long non-coding RNA (lncRNA), circular RNA (circRNA), microRNA (miRNA), piwi-interacting RNA (piRNA), transfer RNA-derived small RNA (tsRNA), and other small non-coding RNAs — that can be transferred between cells and modulate recipient cell function. The RNA cargo of exosomes mirrors the transcriptomic state of their parent cells, making exosomal RNA a rich, non-invasive source of biomarkers for disease diagnosis, prognosis, and therapeutic monitoring.

Our exosome RNA sequencing service delivers comprehensive transcriptome profiling of exosomal RNA cargo using optimized workflows for both small RNA and long RNA analysis. We employ robust exosome isolation methods validated across multiple biofluid types, followed by strand-specific library preparation and high-depth Illumina sequencing (NovaSeq 6000 / X Plus). The resulting data undergo rigorous bioinformatic analysis to identify differentially expressed RNAs, construct regulatory networks, and prioritize biomarker candidates.

We offer specialized sub-services for focused exosomal RNA analysis: Exosomal microRNA Sequencing, Exosomal Small RNA Sequencing, Exosomal lncRNA Sequencing, Exosomal Long RNA Sequencing, Exosomal mRNA Sequencing, and Exosomal circRNA Sequencing.

Technical Advantages of Our Exosome RNA Sequencing Service

Multi-Method Exosome Isolation

We offer validated exosome isolation methods tailored to sample type and research goals — including ultracentrifugation (UC), polymer-based precipitation, size exclusion chromatography (SEC), and immunoaffinity capture. Each method is optimized to maximize RNA yield while minimizing contamination from non-exosomal RNA species. SEC is recommended for low-abundance RNA detection, while UC provides high-purity exosome fractions suitable for downstream sequencing applications.

Comprehensive RNA Cargo Coverage

Exosomes carry a diverse RNA payload spanning multiple size classes and modification states. Our workflow captures the full spectrum — from microRNAs (18–25 nt) and piRNAs (26–31 nt) to full-length mRNAs and lncRNAs (>2 kb). We offer separate small RNA and long RNA library preparations optimized for each RNA class, ensuring unbiased representation of the exosomal transcriptome without the size selection biases inherent to total RNA-seq approaches.

Low-Input and Low-Biofluid Optimization

Clinical biofluid samples are often limited in volume, especially in pediatric, longitudinal, or retrospective study designs. Our protocols are optimized for low-input samples — requiring as little as 200 µL of plasma or serum, 1–3 mL of urine, or 500 µL of cell culture supernatant. RNA extraction and library preparation workflows incorporate carrier strategies and reduced-cycle amplification to maintain complexity from picogram-level RNA inputs.

Bioinformatics and Data Analysis

Our bioinformatics pipeline for exosomal RNA-seq data is designed to address the unique challenges of exosomal RNA analysis, including low RNA input effects, fragmented RNA templates, and the need to integrate multi-RNA-type data for biomarker discovery.

Analysis Package	Content Description
Standard Analysis
1. Raw Data QC and Preprocessing	FastQC quality assessment, adapter trimming (Cutadapt), read filtering, rRNA removal. Quality metrics including read duplication rates, GC content, and mapping statistics.
2. Read Alignment	Small RNA: alignment to miRBase, piRNABank, and genome (Bowtie). Long RNA: STAR alignment to reference genome (GRCh38), transcript quantification (Salmon / RSEM). circRNA detection by CIRCexplorer2 or CIRI2.
3. Expression Quantification	Gene/transcript-level expression counts (featureCounts), normalized expression values (TPM, FPKM). Small RNA expression profiling including isomiR annotation and arm-switching analysis.
4. Differential Expression Analysis	DESeq2 or edgeR for differential expression between experimental groups. Batch effect detection and correction. Principal component analysis (PCA) and sample clustering for quality assessment.
5. Functional Enrichment and Pathway Analysis	Gene Ontology (GO) enrichment, KEGG pathway analysis, Reactome annotation for target genes of differentially expressed RNAs. miRNA target prediction (TargetScan, miRDB, miRTarBase) and mRNA target enrichment.
Advanced Analysis
6. Alternative Splicing and Gene Fusion	rMATS for alternative splicing events (SE, A5SS, A3SS, MXE, RI). Fusion gene detection (STAR-Fusion, Arriba). Identification of tumor-specific fusion transcripts in exosomal RNA.
7. ceRNA Network Construction	Integrated miRNA-mRNA-lncRNA/circRNA competing endogenous RNA (ceRNA) network analysis. Identification of sponge interactions and regulatory axes using hypergeometric testing and correlation analysis.
8. Novel RNA Discovery	Novel miRNA prediction (miRDeep2). Novel circRNA identification from backsplicing reads. Transcript assembly (StringTie) for novel lncRNA and mRNA isoform discovery from exosomal long RNA data.
9. Biomarker Panel Identification	Machine learning-based feature selection (LASSO, Random Forest) for biomarker panel identification. ROC curve analysis, sensitivity/specificity calculation, and multi-marker panel performance evaluation.

Our bioinformatics team delivers a comprehensive analysis report with publication-ready figures, including exosomal RNA expression heatmaps, differential expression volcano plots, ceRNA network visualizations, and biomarker ROC curves. For orthogonal validation, our RNA Mass Spectrometry platform can provide independent confirmation of exosomal RNA modification profiles.

Applications

Exosomal RNA sequencing has broad applications across biomedical research, with particular impact in liquid biopsy, intercellular communication, and biomarker development. The following application areas are particularly well-suited to our approach.

Cancer Liquid Biopsy

Exosomes shed by tumor cells carry cancer-specific RNA signatures — including mutated transcripts, fusion RNAs, and aberrantly expressed non-coding RNAs — that can be detected in circulation. Exosomal RNA-seq enables non-invasive tumor profiling for early detection, minimal residual disease monitoring, treatment response assessment, and resistance mechanism identification across multiple cancer types including lung, breast, pancreatic, colorectal, and prostate cancer.

Cardiovascular Disease Biomarkers

Exosomal RNAs released by cardiomyocytes, endothelial cells, and cardiac fibroblasts reflect the molecular state of the cardiovascular system. Exosomal miRNA and lncRNA signatures have been linked to myocardial infarction, heart failure, atherosclerosis, and hypertension. Our exosomal RNA-seq service enables systematic discovery of circulating RNA biomarkers for cardiovascular risk stratification and therapeutic monitoring.

Neurological Disorders

Exosomes can cross the blood-brain barrier, carrying brain-enriched RNAs into peripheral circulation. This makes exosomal RNA sequencing a promising approach for non-invasive profiling of neurological and psychiatric conditions — including Alzheimer's disease, Parkinson's disease, glioblastoma, and traumatic brain injury. Brain-derived exosomal RNA signatures provide molecular windows into otherwise inaccessible neural tissue.

Infectious Disease and Inflammation

Exosomes play important roles in host-pathogen interactions and immune regulation. Pathogen-derived RNAs can be detected in exosomes during active infection, and host exosomal RNA profiles change in response to inflammatory stimuli. Exosomal RNA-seq has been applied to study tuberculosis, viral hepatitis, HIV, COVID-19, and autoimmune conditions — revealing diagnostic and prognostic RNA signatures in biofluids.

Cell-Cell Communication and Intercellular Signaling

Beyond biomarker discovery, exosomal RNA sequencing provides mechanistic insights into how cells communicate via extracellular vesicles. By profiling the RNA cargo of exosomes from specific cell types or under defined conditions, researchers can identify functionally transferred RNAs, characterize exosome-mediated signaling pathways, and understand how exosomal RNA reprograms recipient cell gene expression in development, tissue homeostasis, and disease.

Sample Requirements

Sample Type	Recommended Volume	Notes
Plasma (EDTA or citrate)	≥500 µL (standard); ≥200 µL (low-input)	Hemolyzed samples not recommended; avoid heparin anticoagulant
Serum	≥500 µL (standard); ≥200 µL (low-input)	Consistent clotting protocol recommended
Urine	≥3 mL (standard)	First morning void preferred; protease inhibitors recommended
Cell culture supernatant	≥10 mL (standard)	Serum-free or exosome-depleted culture media recommended
CSF, saliva, other biofluids	≥1 mL (consultation recommended)	Feasibility assessment required for non-standard biofluids

Important Notes:

A minimum of two experimental groups (e.g., disease vs. control) with ≥3–5 biological replicates per group is recommended for robust differential expression analysis.
Matched biofluid collection and processing protocols across all samples are critical for minimizing pre-analytical variability.
Freeze-thaw cycles should be avoided — aliquot biofluid samples before freezing and use each aliquot once.
For plasma samples, EDTA is the preferred anticoagulant. Heparin inhibits downstream enzymatic reactions including reverse transcription and library preparation.
Exosome-depleted control samples (e.g., ultracentrifuged supernatant) are recommended for projects requiring confirmation of exosomal RNA enrichment.
Non-standard sample types or challenging study designs: please consult with our team for feasibility assessment and protocol optimization.

Case Study: Multi-RNA Profiling of Plasma Exosomes by RNA Sequencing

A 2023 study published in Scientific Data by Liu and colleagues performed comprehensive long non-coding RNA, circular RNA, and coding RNA profiling of plasma exosomes from osteosarcoma patients and healthy controls using RNA sequencing — demonstrating the feasibility and biomarker potential of exosomal multi-RNA analysis in cancer liquid biopsy.

Osteosarcoma is the most common primary bone malignancy in children and adolescents, yet non-invasive biomarkers for early detection and treatment monitoring remain limited. Exosomes released by tumor cells carry tumor-specific RNA cargo into the circulation, providing a potential liquid biopsy source for cancer biomarkers. However, comprehensive profiling of multiple exosomal RNA types — including lncRNAs, circRNAs, and mRNAs — from the same plasma samples had been technically challenging due to the low yield and fragmented nature of exosomal RNA.

Study design and experimental workflow for plasma exosomal RNA profiling

Figure 1. Study design and exosomal RNA profiling workflow.
Plasma exosomes were isolated from osteosarcoma patients and healthy controls, characterized by NTA and TEM, and subjected to RNA extraction and sequencing. Long RNA libraries were prepared by ribo-depletion and sequenced on Illumina NovaSeq to profile lncRNA, circRNA, and mRNA expression. Adapted from Liu et al. 2023 (CC BY 4.0).

Methods: Plasma samples were collected from osteosarcoma patients (n = 12) and age-matched healthy controls (n = 12). Exosomes were isolated by ultracentrifugation and characterized by NTA (size distribution), TEM (morphology), and exosomal marker immunoblotting (CD63, CD81). Total exosomal RNA was extracted using TRIzol LS reagent with glycogen carrier. Long RNA libraries were constructed using a ribo-depletion protocol to capture fragmented exosomal RNA, sequenced on Illumina NovaSeq 6000 (PE150), and analyzed for lncRNA, circRNA, and mRNA expression profiles using standard bioinformatic pipelines.

Differential exosomal RNA expression analysis results

Figure 2. Differential exosomal RNA expression analysis.
Volcano plots and heatmaps showing significantly dysregulated mRNAs, lncRNAs, and circRNAs identified in plasma exosomes of osteosarcoma patients compared with healthy controls, demonstrating the feasibility of multi-RNA-type exosomal biomarker discovery from limited plasma volumes. Adapted from Liu et al. 2023 (CC BY 4.0).

Results: The study demonstrated successful exosomal RNA profiling from plasma, identifying hundreds of dysregulated lncRNAs, circRNAs, and mRNAs in osteosarcoma patient exosomes compared to healthy controls. The exosomal RNA profiles reflected known osteosarcoma-associated transcriptomic alterations, including dysregulation of genes involved in extracellular matrix remodeling, cell proliferation, and angiogenesis pathways. The study provided a valuable resource dataset (deposited in GEO, accession GSE184132) for the exosomal RNA research community and established a technical framework for multi-RNA-type exosomal biomarker discovery. This case study highlights the potential of our exosomal RNA sequencing service to support similar biomarker discovery and liquid biopsy research across diverse disease contexts.

FAQs — Frequently Asked Questions

- 1) What types of RNA can be analyzed from exosomes?
  - Exosomes carry a diverse RNA cargo that includes messenger RNA (mRNA), long non-coding RNA (lncRNA), circular RNA (circRNA), microRNA (miRNA), piwi-interacting RNA (piRNA), transfer RNA-derived small RNA (tsRNA), and other small non-coding RNAs. Our service offers separate library preparations optimized for small RNA analysis (miRNA, piRNA, tsRNA) and long RNA analysis (mRNA, lncRNA, circRNA), or can be customized for whole transcriptome coverage depending on your research goals.
- 2) What sample types and volumes are required?
  - We accept plasma (EDTA or citrate), serum, urine, cell culture supernatant, CSF, saliva, and other biofluids. Recommended volumes: ≥500 µL for plasma/serum (≥200 µL for low-input protocols), ≥3 mL for urine, ≥10 mL for cell culture supernatant. For non-standard biofluid types, please consult with our team for feasibility assessment and protocol optimization.
- 3) How do you isolate exosomes from biofluids?
  - We offer multiple validated exosome isolation methods: ultracentrifugation (UC), size exclusion chromatography (SEC), polymer-based precipitation, and immunoaffinity capture. The optimal method depends on your sample type, volume, and downstream application. SEC is recommended for preserving small RNA profiles and minimizing protein contamination, while UC provides higher exosome purity suitable for comprehensive RNA analysis. We provide method consultation based on your specific project requirements.
- 4) What is the minimum RNA input required for library preparation?
  - Our optimized protocols can generate high-quality libraries from as little as 100 pg of exosomal total RNA for small RNA libraries and 500 pg for long RNA libraries. We use carrier-assisted RNA extraction and reduced-cycle amplification strategies to maximize library complexity from low-input samples. For the best results, we recommend ≥1 ng of exosomal total RNA where sample volume permits.
- 5) How do you distinguish exosomal RNA from cellular RNA contamination?
  - We employ multiple strategies to ensure exosomal RNA enrichment: (1) exosome characterization by NTA, TEM, and marker validation (CD63/CD81/CD9) confirms the absence of cellular debris; (2) RT-qPCR for exosomal marker miRNAs (miR-451a, miR-16) vs. cellular contamination markers (U6 snRNA, 18S rRNA) provides quantitative purity assessment; (3) bioinformatic filtering can identify and flag reads derived from abundant cellular RNA species. Where required, exosome-depleted controls can be included for direct comparison.
- 6) What bioinformatics analysis is included?
  - Our standard bioinformatics package includes raw data QC, alignment, expression quantification, differential expression analysis, and functional enrichment. Advanced analysis options include alternative splicing and gene fusion detection, ceRNA network construction, novel miRNA and circRNA discovery, and machine learning-based biomarker panel identification. All analysis is delivered with publication-ready figures and comprehensive reporting.
- 7) Can exosomal RNA-seq be used for biomarker discovery?
  - Yes — exosomal RNA sequencing is one of the most promising approaches for liquid biopsy biomarker discovery. Exosomal RNA reflects the transcriptomic state of parent cells and can be obtained non-invasively from biofluids. Our service includes differential expression analysis, ROC curve evaluation, and multi-marker panel identification using machine learning approaches to prioritize candidate biomarkers for further validation. We have supported biomarker discovery studies across cancer, cardiovascular disease, neurological disorders, and infectious disease applications.
- 8) How does exosomal RNA-seq differ from total RNA-seq?
  - Standard total RNA-seq analyzes RNA extracted directly from cells or tissues, which includes ribosomal RNA as the dominant species. Exosomal RNA-seq specifically profiles the RNA cargo packaged within extracellular vesicles, which is typically enriched in small non-coding RNAs (miRNAs, piRNAs, tsRNAs) and fragmented mRNA/lncRNA/circRNA fragments, with minimal ribosomal RNA content. Exosomal RNA-seq requires specialized isolation, extraction, and library preparation protocols optimized for low-yield, fragmented RNA — which are all standard components of our service.

References:

Liu Y, Tang H, Li C, et al. Long non-coding RNA and circular RNA and coding RNA profiling of plasma exosomes of osteosarcoma by RNA seq. Sci Data. 2023;10:395.
San Lucas FA, Allenson K, Bernard V, et al. Minimally invasive genomic and transcriptomic profiling of visceral cancers by next-generation sequencing of circulating exosomes. Ann Oncol. 2016;27(4):635-641.
Nakamura K, Zhu Z, Roy S, et al. An exosome-based transcriptomic signature for noninvasive, early detection of patients with pancreatic ductal adenocarcinoma. Gastroenterology. 2022;163(4):1013-1025.
Riffo-Campos AL, Perez-Hernandez J, Ortega A, et al. Exosomal and plasma non-coding RNA signature associated with urinary albumin excretion in hypertension. Int J Mol Sci. 2022;23(2):823.

For Research Use Only. This service is intended for exploratory and mechanistic research applications, including exosomal RNA profiling, biomarker discovery, liquid biopsy development, and intercellular communication studies. It is not intended for clinical diagnosis, treatment selection, patient stratification, or therapeutic decision-making.