Antibody-free, chemically mild, base-resolution mapping of transcriptome-wide m6A—designed for site-focused interpretation when you need more than peak-level enrichment.
Move beyond peak-level signals: Designed to support single-nucleotide m6A site localization, helping you interpret biology at the site level rather than broad regions.
Support limited material: Low-input positioning can help when sample amount is a constraint (reported feasibility down to very low poly(A)+ RNA input in published summaries).
Reduce IP-related bias risk: A chemistry-based, antibody-free approach minimizes dependence on antibody performance and enrichment variability.
Actionable deliverables: Receive core QC summaries and site-focused outputs suitable for downstream interpretation and reporting.
What is CAM-seq for m6A Sequencing? Base-Resolution, Antibody-Free Profiling
CAM-seq is a chemically mild approach that converts adenine to hypoxanthine (read as G) while m6A resists deamination and remains A, enabling base-resolution detection logic without antibody enrichment.
m6A research has shifted from "is it present?" to "which exact sites change, and how does that connect to phenotype?" Yet many workflows still return region-level enrichment rather than site-level answers—making it hard to distinguish nearby events, prioritize follow-up targets, or explain mechanistic outcomes with confidence.
What this means for your study
Frame hypotheses around specific sites (not just enriched regions).
Compare conditions using site-level readouts for more interpretable biology.
Reduce dependence on antibody specificity and IP variability in m6A workflows.
Principle
How CAM-seq Works: Mild Chemical Deamination and A-to-G Readout for m6A Sites
CAM-seq infers m6A using an A-to-G readout: unmodified A is chemically deaminated to hypoxanthine/inosine (read as G), while m6A remains A.
CAM-seq is based on cooperative catalysis combining a carbonyl organocatalyst with a Lewis acid catalyst to enable selective deamination under mild conditions. In this workflow:
Adenine → hypoxanthine, which is read as guanine by reverse transcriptases or polymerases.
m6A resists deamination and remains identified as adenine, creating a direct base-resolution signal logic for m6A detection.
Portfolio
CAM-seq Service Options: Site Discovery and Multi-Condition Comparison
CAM-seq projects are typically designed for site discovery (build a base-resolution map) or comparative profiling (evaluate site-level differences across conditions).
1) CAM-seq Site Discovery (Single Condition)
Best for
Building a first-pass site-level m6A map
Generating candidate sites for mechanistic follow-up
Contrasting conditions (e.g., experimental condition vs control; perturbation vs WT)
Prioritizing site-level differences for downstream validation
Why CAM-seq
Base-resolution logic: supports site-level biology rather than broad regions.
Antibody-free workflow: reduces reliance on antibody specificity and IP efficiency.
Mild deamination strategy: designed to be more compatible with biological macromolecules than harsh acid-based deamination.
Applications
When to Use CAM-seq: Mechanism Studies, Low-Input Samples, and Cross-Species m6A Mapping
Choose CAM-seq when your question requires site-level m6A interpretation, especially for mechanism studies, limited-input projects, or cross-species mapping.
CAM-seq is a good fit when your question needs site-level answers:
Mechanism studies: connect m6A changes to RNA metabolism/translation regulation by focusing on specific sites.
Condition comparisons: assess how perturbations shift site-level signals across transcripts.
Cross-species mapping: published summaries highlight use across human and plant contexts (useful for motif/deposition differences).
Limited-input projects: when material is scarce and you need a workflow positioned for low input.
Workflow
CAM-seq Workflow: From poly(A)+ RNA to Illumina Libraries and Site Calling
CAM-seq follows a poly(A)+ RNA workflow—enrichment → fragmentation → chemical conversion → library prep → sequencing → site reporting.
Below is a service-ready representation aligned to the published method logic (high-level, RUO):
RNA preparation
Total RNA extraction and poly(A) enrichment (poly(A)+ RNA), followed by fragmentation (commonly ~200 nt in method summaries).
Bioinformatics for CAM-seq: QC, Alignment, A/G Metrics, and m6A Site-Level Reporting
CAM-seq bioinformatics converts sequencing data into site-focused outputs by performing QC, alignment, extracting A/G metrics, and generating annotated site tables and summary plots.
Bioinformatic Analysis Table (Standard vs. Advanced)
Site-level A/G outcome summaries and candidate site list
Artifact-focused filtering; configurable thresholds by sample type
Annotation & summaries
Transcript feature summaries; motif summaries; distribution plots
Condition overlays; motif stratification; targeted panels for manuscripts
Reporting
Structured report + tables for interpretation
Publication-format figure set and executive summary (RUO)
Samples
Sample Requirements for CAM-seq: RNA Type, Input Guidance, and Quality
CAM-seq is positioned around poly(A)+ RNA with fragmentation as part of the workflow; feasibility is driven primarily by RNA integrity, cleanliness, and achieving the target poly(A)+ input.
Sample Types & Submission Guidance
Sample Type
Accepted Format
Submission Guidance
Extracted RNA
poly(A)+ RNA
10 ng poly(A)+ RNA is reported as feasible starting input in provided summaries; practical requirements depend on study design and RNA quality.
Extracted RNA
Total RNA
Used as upstream material for poly(A) enrichment; amount depends on yield needs (project-specific).
Cells
Cell pellet
RNA-yield dependent; submit sufficient material to obtain the required poly(A)+ input.
Tissue
Fresh/frozen tissue
RNA-yield dependent; submit sufficient material to obtain the required poly(A)+ input.
Important: CAM-seq outcomes depend on RNA quality and library construction. Fragmentation is part of the described workflow, and mild reaction conditions are intended to reduce degradation risk relative to harsher chemistries.
Deliverables
Deliverables and Demo Results: What You Receive From a CAM-seq Project
Deliverables are designed to be decision-ready, combining QC, site-focused tables, and summary plots that support interpretation and reporting.
What You'll Receive (Deliverables)
Sequencing data files (FASTQ)
Alignment files (BAM) + mapping/QC summary (where included in your package)
Motif and distribution summaries (transcript feature–oriented reporting)
Comparison
CAM-seq vs MeRIP-seq vs GLORI: Resolution, Bias, Input, and Best-Fit Use Cases
Use MeRIP-seq for region-level discovery, GLORI when absolute site-level quantification is the priority, and CAM-seq when you want an antibody-free, site-oriented readout positioned for mild chemistry and low-input feasibility.
Meyer, Kate D., et al. "Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3' UTRs and near Stop Codons." Cell, vol. 149, no. 7, 2012, pp. 1635–1646.
Dominissini, Dan, et al. "Topology of the Human and Mouse m6A RNA Methylomes Revealed by m6A-seq." Nature, vol. 485, 2012, pp. 201–206.
Werner, Stephan, et al. "NOseq: Amplicon sequencing evaluation method for RNA m6A sites after chemical deamination." Nucleic Acids Research, vol. 49, no. 4, 2021, e23.
Mahdavi-Amiri, Yasaman, Kimberley Chung Kim Chung, and Ryan Hili. "Single-nucleotide resolution of N6-adenine methylation sites in DNA and RNA by nitrite sequencing." Chemical Science, vol. 12, 2021, pp. 606–612.
Gao, Y., et al. "Quantitative profiling of N6-methyladenosine at single-base resolution in stem-differentiating xylem of Populus trichocarpa using Nanopore direct RNA sequencing." Genome Biology, 2021.
