AlkAniline-Seq for Single-Nucleotide m7G/m3C RNA Modification Mapping
Most RNA methylation assays enrich regions. AlkAniline-Seq is designed for a different question: exactly where are the m7G and m3C sites—at single-nucleotide resolution—across diverse RNA classes?
- Single-nucleotide localization via N+1 read-start signatures (site-level, not peaks)
- Positive-enrichment chemistry to reduce background and improve signal-to-noise
- One workflow delivers dual m7G + m3C site maps at single-nucleotide resolution
- Supports tRNA/rRNA/mRNA and cytosolic + mitochondrial RNA studies
AlkAniline-Seq Overview: Single-Nucleotide m7G+m3C Mapping
Key takeaways:
- Targets: m7G (N7-methylguanosine) and m3C (3-methylcytidine)
- Resolution: single-nucleotide (N+1 read-start signal)
- Mechanism: alkali/NaBH₄ → phosphatase → aniline cleavage → positive-enrichment ligation
- Primary output: separate m7G and m3C site tables + N+1 pileup tracks
RNA modifications are widespread (150+ described), yet only a small subset has mature, high-throughput sequencing readouts. AlkAniline-Seq is a chemistry-based approach developed to enable high-throughput detection and single-nucleotide localization of m7G (N7-methylguanosine) and m3C (3-methylcytidine).
At a glance: What is AlkAniline-Seq?
AlkAniline-Seq is a sequencing workflow that uses sequential chemical processing to generate cleavage products whose Read1 starts at the N+1 nucleotide adjacent to a modified base. After alignment, 5'-end read-start counts indicate cleavage position and intensity, enabling site-level calling for m7G and m3C.
Use Cases: When to Choose AlkAniline-Seq for m7G+m3C
AlkAniline-Seq is a fit when your study needs site precision and chemical specificity:
- Site-level maps of m7G and m3C across the transcriptome (high-throughput detection + single-nucleotide localization)
- Structured RNA-centric projects: tRNA and rRNA mapping in cytosolic and mitochondrial compartments
- Low-abundance RNA contexts, where positive enrichment helps concentrate informative fragments
- Studies that benefit from one dataset yielding two modification outputs (m7G + m3C) from a single workflow
Common companion assays for biological interpretation include RNA-seq (expression context) and downstream validation workflows.
Method Principle: N+1 Read-Start Chemistry for m7G+m3C
AlkAniline-Seq uses three consecutive chemistry steps to create an alignment-readable signature:
- Alkaline hydrolysis / lesion induction
Alkaline conditions promote formation of abasic (AP) sites associated with chemically labile positions (workflow descriptions include NaBH₄ handling in this step).
- Broad 5' and 3' dephosphorylation (end normalization)
Alkaline phosphatase removes existing phosphate groups to convert fragment ends to 5'-OH and 3'-OH, reducing background from unrelated breaks and standardizing ends before enrichment.
- Aniline cleavage at abasic sites (enrichment handle creation)
Aniline cleaves at abasic sites, exposing a 5'-phosphate on the N+1 nucleotide. Adapter ligation then preferentially captures these cleavage fragments, enabling positive enrichment of modification-proximal products.
Sequencing and readout
Illumina library construction produces dsDNA amplicons where Read1 begins at N+1, so mapped read-start pileups report cleavage position and strength.
Advantages: Why AlkAniline-Seq vs Region-Level Enrichment Approaches
site calls are anchored by Read1 starts at N+1 rather than broad enrichment peaks.
positive enrichment focuses library complexity on cleavage-derived fragments, improving signal-to-noise.
m7G and m3C can be distinguished in analysis to generate separate result tables from one workflow.
designed for multiple RNA classes, including tRNA/rRNA and compartment-specific mapping (cytosolic/mitochondrial).
enrichment supports detection in contexts where low abundance makes site discovery difficult.
Project Workflow: From Samples to m7G+m3C Site Tables
Wet-lab workflow
- Project intake & study design (organism, RNA class focus, replicates/controls)
- Sample QC (RNA quantity/quality review; acceptance criteria)
- Sequential chemistry (alkali/NaBH₄ handling → phosphatase → aniline cleavage)
- Adapter ligation & library construction
- Illumina sequencing
- Bioinformatics site calling and reporting for m7G and m3C
Recommended experimental design
- Use biological replicates for condition comparisons
- Include appropriate controls for interpretation of enrichment-derived signals (study-design dependent)
- Pre-specify whether your primary focus is mRNA/lncRNA or tRNA/rRNA, and whether you need cytosolic vs mitochondrial stratification
Bioinformatics: N+1 Pileups, Site Calling
AlkAniline-Seq analysis is centered on:
- Alignment to appropriate references
- Quantification of 5'-end read-start pileups at N+1 positions
- Generation of site-level tables and summary statistics for m7G and m3C
Bioinformatic Analysis Table (Standard vs. Advanced)
| Module | Standard (Included) | Advanced (Add-on) |
|---|---|---|
| Data QC | Read quality checks, adapter/quality trimming | Cohort-level QC across many batches/conditions |
| Mapping | Alignment to appropriate references for the study scope | Specialized mapping strategies for structured RNAs (tRNA/rRNA-focused) |
| Signal extraction | 5'-end read-start counts and N+1 signal metrics | Enhanced background modeling and signal normalization |
| Site calling | Candidate site tables with signal metrics and annotations | Differential site analysis across conditions/groups |
| Annotation | RNA biotype and feature annotation, summary distributions | Compartment- or RNA-class–stratified reporting (e.g., mitochondrial vs cytosolic) |
| Reporting | Tables + publication-ready summary figures | Customized visuals, integration guidance with RNA-seq |
Sample Requirements: Accepted Sample Types, Inputs, and Shipping
Sample Requirement Table (Cells / Tissue / Fluid)
| Sample Type | Input Requirement | Quality Notes |
|---|---|---|
| Cells | 1 × 10⁷ | Preserve RNA integrity; ship frozen on dry ice |
| Tissue | 500 mg – 5 g | Fresh/frozen tissue; stabilize RNA (e.g., RNA protectant or TRIzol) |
| Purified RNA | 100–300 µg | OD260/280 1.6–2.3; no obvious degradation |
| Other samples | Consult required | Other sample types are supported upon consultation; requirements depend on RNA yield and integrity |
Shipping & storage
- Ship samples in 1.5 mL tubes, sealed and packed on dry ice
- Store at −80°C, avoid repeated freeze–thaw
- Cells/fresh tissues may be processed in TRIzol or RNA preservative prior to freezing
Deliverables & Demo Outputs: What You'll Receive from AlkAniline-Seq
Core deliverables:
- Separate m7G and m3C site tables (coordinates, signal metrics, annotations)
- N+1 read-start pileup tracks for visualization and site inspection
- QC summary (library complexity, mapping overview, replicate concordance)
- Standard report + complete data package for downstream analysis
What the selected demo outputs demonstrate:
- Clear N+1 read-start pileups supporting single-nucleotide site calls
- Clean separation of m7G vs m3C results in separate deliverable tables
- RNA-class composition summaries across tRNA/rRNA/mRNA/lncRNA
- Replicate concordance views to support high-confidence site calls
Method Selection: AlkAniline-Seq vs m7G MeRIP vs TRAC-Seq
| Decision Factor | AlkAniline-Seq | RNA m7G Methylation Sequencing (MeRIP + Single-Base options) | TRAC-Seq |
|---|---|---|---|
| Primary question it answers | "Where exactly are the m7G and m3C sites?" | "Where is m7G enriched (MeRIP) or where are m7G sites at base resolution (single-base option)?" | "Where are m7G sites in tRNA at single-base resolution?" |
| Typical resolution | Single-nucleotide (N+1 read-start signature) | Two modes: peak/region-level (MeRIP) or single-nucleotide (single-base option) | Single-nucleotide (tRNA-focused) |
| Key principle | Chemistry-driven positive enrichment via cleavage-derived ligation products | Two modes: antibody enrichment (MeRIP) or single-base route described in the service | tRNA-optimized single-base mapping workflow |
| Outputs | Separate m7G and m3C site tables from one workflow | m7G peaks (MeRIP) and/or m7G site-level outputs (single-base option) | tRNA m7G site list with tRNA-centric QC |
| Best-fit RNA classes | Broad RNA classes; structured RNAs supported | Broad (especially mRNA/lncRNA for MeRIP); single-base option positioned for internal m7G mapping | tRNA-first projects |
| When to choose | You want single-nucleotide m7G+m3C site maps from one workflow | You want either fast peak screening (MeRIP) or a single-base m7G option within one service family | You need tRNA-specialized depth and analysis |
Quick selection rules
- Choose AlkAniline-Seq for single-nucleotide m7G+m3C mapping with a positive-enrichment readout.
- Choose RNA m7G Methylation Sequencing when your decision is between peak screening (MeRIP) and an m7G single-base option.
- Choose TRAC-Seq when the biology is tRNA-centric.
Case Study
FAQ: AlkAniline-Seq Service Questions
References
- Marchand, Virginie, et al. "AlkAniline-Seq: Profiling of m7G and m3C RNA Modifications at Single Nucleotide Resolution." Angewandte Chemie International Edition, vol. 57, no. 51, 2018, pp. 16785–16790.
- Marchand, Virginie, et al. "AlkAniline-Seq: A Highly Sensitive and Specific Method for Simultaneous Mapping of 7-Methyl-guanosine (m7G) and 3-Methyl-cytosine (m3C) in RNAs by High-Throughput Sequencing." In RNA Modifications, edited by Mary McMahon, Methods in Molecular Biology, vol. 2298, Humana, 2021, pp. 77–95.
- Zhang, Li Sheng, et al. "Transcriptome-wide Mapping of Internal N7-Methylguanosine Methylome in Mammalian mRNA." Molecular Cell, vol. 74, no. 6, 2019, pp. 1304–1316.e8.
- Pandolfini, Luca, et al. "METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation." Molecular Cell, vol. 74, no. 6, 2019, pp. 1278–1290.e9.
- Hardy, Léo, et al. "The tRNA Epitranscriptomic Landscape and RNA Modification Enzymes in Vibrio cholerae." PLOS Genetics, vol. 21, no. 10, 31 Oct. 2025, e1011937.
- Sordyl, Dominik, et al. "MODOMICS: a Database of RNA Modifications and Related Information. 2025 Update and 20th Anniversary." Nucleic Acids Research, 24 Nov. 2025, gkaf1284.
- Lin, Shuibin, et al. "Nucleotide Resolution Profiling of m7G tRNA Modification by TRAC-Seq." Nature Protocols, vol. 14, no. 11, 2019, pp. 3220–3242.