What biofluid types are suitable for cfRNA modification sequencing?

Plasma and serum are the most commonly used sample types. Urine, cerebrospinal fluid (CSF), saliva, aqueous humor, and vitreous humor are also compatible. Each biofluid type requires specific collection and processing protocols. Contact our project scientists for sample-type-specific guidance before collection.

How many biological replicates are recommended?

A minimum of 3 biological replicates per experimental group is recommended. This enables statistical assessment of differential modification (P-value calculation requires at least 3 replicates). For pilot or exploratory studies, 2 replicates can provide initial qualitative assessment, though statistical power is limited.

What species are supported?

The workflow is compatible with any species for which reference genomes are available for both host and microbial compartments. Host cfRNA annotation is most comprehensive for human. Microbial cfRNA analysis requires reference genomes for the microbial taxa of interest.

cfRNA Modification Sequencing Services

cfRNA modification sequencing adapts modification-specific immunoprecipitation methods to the ultra-low-input constraints of cell-free RNA from biofluids. By enriching RNA fragments carrying covalent modifications — including m6A, m5C, m1A, Ψ, m7G, and ac4C — from plasma, serum, urine, CSF, saliva, and other biofluids, the approach opens RNA modification profiling to non-invasively collected liquid biopsy samples. CD Genomics provides end-to-end support from cfRNA extraction through sequencing and bioinformatics analysis, with dual Spike-In controls for IP quality monitoring at low-input scale.

Key Highlights of Our cfRNA Modification Sequencing Service:

Ultra-Low Input: Optimized for pg–ng level cfRNA from biofluids, enabling modification profiling from samples too limited for conventional MeRIP-seq.
Dual Spike-In Controls: Positive and negative synthetic reference RNAs provide internal normalization for IP efficiency at low-input scale, enabling reliable cross-sample comparison.
Host + Microbiome Co-Analysis: Modification sites profiled on both host-derived and microbiome-derived cfRNA from a single sample.
Biofluid Compatibility: Accepts plasma, serum, urine, cerebrospinal fluid, saliva, aqueous humor, and vitreous humor — covering the most common non-invasive sample types.

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cfRNA modification sequencing overview showing biofluid sample collection, cfRNA extraction, Spike-In controlled antibody IP enrichment of modified cfRNA fragments, high-throughput sequencing, and liquid biopsy data analysis for modification site mapping

Overview

What Is cfRNA Modification Sequencing?

Cell-free RNA (cfRNA) encompasses diverse RNA species — including mRNA fragments, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), transfer RNAs (tRNAs), and other small non-coding RNAs — that circulate in biofluids such as plasma, serum, urine, cerebrospinal fluid, and saliva. Released by cells through active secretion or passive leakage during cell death, cfRNAs carry molecular signatures reflective of their tissue of origin and the physiological or pathological state of the donor.

cfRNA modification sequencing adapts modification-specific immunoprecipitation methods — built on the MeRIP-seq principle — to the ultra-low-input constraints of cell-free RNA. The workflow extracts cfRNA from biofluid samples, adds dual Spike-In synthetic reference controls for IP quality monitoring, and uses modification-specific antibodies to enrich RNA fragments carrying covalent modifications such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), and pseudouridine (Ψ). High-throughput sequencing and computational analysis then map modification positions across both host-derived and microbiome-derived cfRNA transcripts.

Unlike standard MeRIP-seq, which typically requires microgram quantities of total RNA from cells or tissues, cfRNA modification sequencing operates at the pg–ng scale, opening RNA modification profiling to liquid biopsy samples that can be collected non-invasively.

cfRNA modification sequencing technology principle showing biofluid cfRNA extraction, Spike-In addition, modification-specific antibody immunoprecipitation adapted for ultra-low input, and sequencing-based modification site mapping on cell-free transcripts

Technology Principle & Advantages

Principle

The method proceeds through three sequential stages:

1 cfRNA Extraction & QC

cfRNA is extracted from biofluid samples using optimized protocols that remove proteins, genomic DNA, and other contaminants while preserving the low-abundance, fragmented cfRNA population. Extracted cfRNA is quantified and assessed for integrity.

2 Modification-Specific IP

Purified cfRNA is incubated with a modification-specific antibody (e.g., anti-m6A) to enrich fragments carrying the target modification (IP fraction). A parallel aliquot is retained as the input control for background normalization. Two classes of synthetic Spike-In RNA — one carrying the target modification (positive control) and one lacking it (negative control) — are added before IP to serve as internal references for enrichment efficiency and technical bias correction.

3 Sequencing & Analysis

IP and input RNA are separately converted to cDNA libraries using ultra-low-input-adapted protocols, amplified, and sequenced. Reads are aligned to host and microbial reference genomes. Enriched modification regions are identified by comparing IP signal against input (peak calling). Modification sites are annotated to genomic features. Differential modification analysis between sample groups identifies condition-dependent changes.

Advantages

Ultra-Low Input Compatibility

The workflow is designed to work with pg–ng quantities of cfRNA — two to three orders of magnitude lower than conventional MeRIP-seq input requirements. This enables modification profiling from biofluid samples collected non-invasively, supporting longitudinal study designs and clinical cohort studies where repeated sampling is required.

Spike-In Quantitative Framework

The dual-control design — using both a modified and an unmodified synthetic reference RNA — provides internal normalization for IP efficiency at low-input scale, where technical variation can otherwise dominate biological signal. This enables more reliable cross-sample comparison.

Biofluid Sample Compatibility

The workflow accepts plasma, serum, urine, cerebrospinal fluid, saliva, aqueous humor, and vitreous humor — covering the most commonly collected biofluid types in clinical and translational research.

Host & Microbiome Dual Analysis

A single cfRNA sample contains both host-derived and microbiome-derived transcripts. The bioinformatics pipeline maps modification sites to both compartments, enabling integrated host-microbiome epitranscriptomic analysis from one sample.

Modification Types

Supported Modification Types

Modification	Full Name	Detection Method
m6A	N6-methyladenosine	Anti-m6A antibody IP
m5C	5-methylcytosine	Anti-m5C antibody IP
m1A	N1-methyladenosine	Anti-m1A antibody IP
Ψ	Pseudouridine	Anti-Ψ antibody IP
m7G	N7-methylguanosine	Anti-m7G antibody IP
ac4C	N4-acetylcytidine	Anti-ac4C antibody IP

Additional modification types may be accommodated upon consultation. Each modification type requires its own IP and input library pair.

Workflow

Experimental Workflow

The cfRNA modification sequencing workflow spans six stages, each with integrated quality control checkpoints. The complete process — from cfRNA extraction to bioinformatics analysis — is outlined below.

cfRNA Extraction. cfRNA is extracted from biofluid samples using optimized protocols designed to remove proteins, genomic DNA, and other contaminants while preserving the low-abundance, fragmented cfRNA population. QC: cfRNA yield quantified; size distribution assessed.
cfRNA Quality Control. Extracted cfRNA is quantified and its size profile is assessed by capillary electrophoresis. Samples are checked for genomic DNA contamination. QC: cfRNA concentration ≥ 1 ng/µL recommended; absence of high-molecular-weight DNA confirmed.
Spike-In Addition and Immunoprecipitation. Synthetic Spike-In controls (positive: carries the target modification; negative: lacks it) are added to the purified cfRNA. A modification-specific antibody captures fragments carrying the target modification (IP). A parallel aliquot is retained as the input control. QC: IP efficiency monitored by qPCR against Spike-In references; input sample preserved for peak calling.
Library Preparation. IP and input RNA are separately converted to cDNA libraries using ultra-low-input-adapted protocols. Libraries are amplified with minimum PCR cycles to preserve complexity. QC: Library size distribution, adapter dimer content, and amplification uniformity assessed.
Sequencing. Libraries are sequenced on an Illumina platform with sufficient depth to capture the low-complexity cfRNA modification landscape. QC: Q30 scores, duplication rate, and read distribution assessed.
Bioinformatics Analysis. Reads are aligned to both host and microbial reference genomes. Peak calling identifies modification-enriched regions by comparing IP versus input signal. Modification sites are annotated to genomic features. Differential modification analysis compares modification levels between experimental groups. Downstream analyses include GO/KEGG enrichment, motif discovery, classification distribution, metagene profiling, and Venn diagram analysis.

Sample

Sample Requirements

Sample quality and quantity directly affect cfRNA yield, IP specificity, and modification detection sensitivity. Recommended input amounts and storage conditions are summarized below.

Sample Type	Recommended Amount	Notes
Plasma	≥ 2 mL	Collected in EDTA or citrate tubes; processed within 4 h of collection
Serum	≥ 2 mL	Collected in serum separator tubes; processed within 4 h of collection
Urine	≥ 10 mL	Midstream collection recommended; centrifuge to remove cells and debris
Cerebrospinal fluid	≥ 5 mL	Collect in sterile tubes; avoid repeated freeze-thaw
Saliva	≥ 5 mL	Collect with RNA stabilization reagent where possible
Vitreous humor	≥ 500 µL	Collect in sterile tubes; contact us for collection protocol
Aqueous humor	≥ 500 µL	Collect in sterile tubes; contact us for collection protocol
Purified cfRNA	≥ 100 ng	Concentration ≥ 1 ng/µL recommended; dissolved in nuclease-free water

Shipping and storage:

Samples should be placed in 15 mL tubes or cryovials, sealed with parafilm, and shipped on dry ice.
Biofluid samples should be aliquoted into cryovials immediately after collection and stored at −80°C.
For long-term preservation, storage in liquid nitrogen is recommended.
Purified cfRNA should be dissolved in nuclease-free water and stored at −80°C; avoid repeated freeze-thaw cycles.

Bioinformatics

Bioinformatics Analysis Pipeline

The standard analysis pipeline covers raw data processing through functional enrichment. Each module produces publication-ready outputs.

Raw data processing. Adapter trimming, low-quality read removal, read length filtering. Q30 scores and sequencing statistics reported.
Read alignment. Clean reads aligned to host and microbial reference genomes.
Modification site identification and annotation. Peak calling identifies modification-enriched regions by comparing IP against input. Modification sites are annotated to genomic features and classified by host transcript type — non-coding (lncRNA, circRNA, snoRNA, snRNA, miRNA, tRNA) or coding (mRNA).
Differential modification analysis. Modification levels compared between sample groups, identifying significantly differentially modified sites based on fold change and statistical significance (P-value calculation requires ≥ 3 biological replicates per group).
GO and KEGG enrichment. Genes associated with differentially modified cfRNA transcripts are analyzed for Gene Ontology (molecular function, cellular component, biological process) and KEGG pathway enrichment.
Motif analysis. Sequence motifs enriched at modification sites are identified, revealing sequence preferences of the modification machinery.
Classification and distribution. Pie charts show the distribution of modification sites across host cfRNA categories. Metagene profiles display modification density along transcript features. Venn diagrams show modification site overlap across samples or conditions.
Microbiome analysis (optional). For projects requiring microbial cfRNA profiling, modification sites detected on microbiome-derived reads are separately annotated to microbial genomes and analyzed for differential modification between conditions.

Optional advanced analyses — including integration with cfRNA expression data, comparison with tissue-derived RNA modification profiles, and machine learning-based biomarker panel development — are available upon request.

Demo

Demo Results

The following representative visualizations illustrate the types of results delivered with each cfRNA modification sequencing project. All panels are labeled "Representative data."

Representative cfRNA modification sequencing analysis outputs delivered with each project. (A) Peak calling output showing enrichment of modification signal (IP vs. input) with cfRNA-type annotation. (B) Pie chart displaying modification site distribution across host cfRNA categories (mRNA, miRNA, lncRNA, tRNA, etc.). (C) Volcano plot highlighting significantly hyper- and hypo-modified cfRNA sites between experimental groups. (D) GO and KEGG enrichment bar charts for genes associated with differentially modified cfRNAs. (E) Sequence logo of enriched nucleotide motif at modification sites. (F) Metagene plot showing modification signal distribution along gene body coordinates. (G) Venn diagram of modification site overlap across multiple samples or conditions.

Deliverables

Data Deliverables

Deliverable	Description
Raw sequencing data	FASTQ files for each IP and input library
Quality control report	Read quality metrics, alignment statistics, library complexity assessment
Peak calling results	Modification-enriched regions identified with coordinates and enrichment scores
cfRNA annotation table	Classification of each modification site by host cfRNA type and genomic feature
Differential modification results	Significantly changed modification sites between conditions, with fold change and P-values
GO/KEGG enrichment report	Functional enrichment analysis for genes associated with differentially modified cfRNAs
Motif analysis results	Enriched sequence motifs at modification sites with significance scores
Visualization package	Classification pie charts, volcano plots, metagene profiles, Venn diagrams, and heatmaps
Methods and analysis report	Detailed description of all data processing and analysis steps

Applications

cfRNA modification sequencing addresses a growing need in translational research: how to access epitranscriptomic information from non-invasively collected biofluid samples for biomarker discovery, disease monitoring, and host-microbiome studies.

Liquid Biopsy Biomarker Discovery

cfRNA modification profiles carry information about the tissue of origin and pathological state. Differential modification analysis between disease and control cohorts identifies cfRNA modification events — such as altered m6A or m5C levels on specific circulating transcripts — that may serve as non-invasive biomarkers for disease detection, monitoring, and prognosis.

Cancer Early Detection

cfRNA modification patterns can distinguish cancer patients from healthy controls. Modification signatures on both host-derived and microbiome-derived cfRNAs have shown high accuracy for cancer detection, including at early stages. cfRNA modification sequencing provides transcriptome-wide modification maps to support biomarker panel development.

Host-Microbiome Epitranscriptomics

A substantial fraction of plasma cfRNA originates from the microbiome. cfRNA modification sequencing simultaneously profiles modifications on both host and microbial transcripts, enabling investigation of host-microbe interactions through RNA epitranscriptomics — including how microbial RNA modifications correlate with host immune status or disease progression.

Drug Response Monitoring

Longitudinal cfRNA modification profiling during treatment can capture dynamic epitranscriptomic changes reflecting therapeutic response or resistance. Modification-level changes may precede changes in cfRNA abundance, offering an early pharmacodynamic readout.

For complementary epitranscriptomic analyses, MeRIP-Seq provides transcriptome-wide modification profiling from total cellular RNA, and caRNA Modification Sequencing targets chromatin-associated RNA modifications from cells and tissues. For native RNA modification detection without amplification, ONT Direct RNA Sequencing provides nanopore-based modification calling.

Method Comparison

Method Comparison: cfRNA Modification Sequencing vs. Standard MeRIP-Seq

cfRNA modification sequencing and standard MeRIP-seq share the same modification-specific immunoprecipitation principle but differ fundamentally in starting material, input scale, and the breadth of RNA populations profiled.

Feature	cfRNA Modification Sequencing	Standard MeRIP-Seq
Starting material	Plasma, serum, urine, CSF, saliva, and other biofluids	Total RNA from cells or tissues
Input amount	pg–ng cfRNA	µg total RNA
RNA population profiled	Cell-free circulating RNA	Total cellular RNA
Sample collection	Non-invasive or minimally invasive	Requires cell/tissue harvest
Internal quantification	Dual Spike-In controls	Typically none or single Spike-In
Host + microbiome analysis	Yes — both compartments profiled	Not standard
Longitudinal sampling	Feasible (non-invasive collection)	Limited (requires repeated biopsy)
Suitable for	Liquid biopsy, biomarker discovery, clinical cohort studies	Tissue/cell-based transcriptome-wide modification surveys

Selection guidance:

Choose cfRNA modification sequencing when you need to profile RNA modifications from non-invasively collected biofluids, or when longitudinal sampling is required for biomarker discovery or treatment monitoring studies.
Choose standard MeRIP-Seq when you have access to cell or tissue samples and need a broad transcriptome-wide modification survey without the input constraints of cfRNA workflows.
Choose caRNA Modification Sequencing when your research focuses on chromatin-associated RNA modifications and their role in local transcriptional regulation.

FAQ

Frequently Asked Questions (FAQ)

Q: What is cell-free RNA (cfRNA) and why profile its modifications?

A: cfRNA refers to RNA molecules released by cells into the circulation and other biofluids. These include mRNA fragments, miRNAs, lncRNAs, tRNAs, and other non-coding RNA species. Because cfRNA carries molecular information about its tissue of origin — and because RNA modifications such as m6A influence RNA stability, translation, and function — profiling cfRNA modifications provides a layer of biological information beyond transcript abundance. Modification patterns may reflect disease state more specifically than expression levels alone.

Q: How do the Spike-In controls work for low-input cfRNA samples?

A: Two classes of synthetic RNA are added before immunoprecipitation: one carrying the target modification (positive control) and one without it (negative control). At low-input scale, technical variation in IP efficiency can dominate biological signal. By tracking the recovery ratio of these Spike-In controls in the IP and input libraries, we can assess IP efficiency, monitor technical variation between samples, and normalize signals for more reliable quantitative comparison across experimental conditions.

Q: What is the difference between cfRNA modification sequencing and cfRNA-Seq?

A: cfRNA-Seq (expression profiling) measures the abundance of circulating transcripts. cfRNA modification sequencing applies the same cfRNA extraction step but then uses modification-specific immunoprecipitation to detect chemical modifications on those transcripts. The two approaches are complementary: cfRNA-Seq reveals which circulating transcripts are present and at what levels; cfRNA modification sequencing reveals how those transcripts are chemically modified.

Q: Can I profile multiple modifications from the same cfRNA sample?

References

The services described are for research use only. They are not intended for diagnostic, therapeutic, or clinical applications.