Can LC–MS/MS tell me the exact genomic locus or transcript position of a modification?

LC–MS/MS is primarily a quantitative measurement of modified nucleosides or PTM peptides. If you need locus-level localization (where on the transcript/genome), pair this service with mapping assays designed for site resolution.

How do I choose between mRNA, tRNA, and total RNA panels?

Choose based on what biological pool you want represented. mRNA focuses on transcript regulation; tRNA is rich in diverse modifications and informative for translation/stress responses; total RNA provides a broad screening view dominated by abundant RNA species.

Is LC–MS/MS suitable for validating enrichment-based sequencing results (e.g., MeRIP-style assays)?

Yes—LC–MS/MS is commonly used as an orthogonal readout of global abundance changes to support interpretation of enrichment/mapping results.

What is the minimum information I should provide with my samples?

Provide a sample sheet with sample IDs, groups/conditions, extraction method, buffer composition (especially detergents/salts), and any known inhibitors. This improves feasibility review and comparability.

Will I receive evidence files (chromatograms/peak integration snapshots)?

Representative evidence files can be included to support interpretability and reporting, especially for key analytes/features driving your conclusions.

Can I combine RNA/DNA modification quantification with histone and protein PTM profiling?

Yes. Multi-layer designs are common in epigenetics projects when you want to connect RNA/DNA marks with chromatin state (histone PTMs) and regulatory pathways (protein PTMs). Align sample availability and grouping upfront.

Is this clinical/diagnostic testing?

No. This service is for research use only.

Epigenetic Modification Mass Spectrometry (LC–MS/MS) Services

Quantify epigenetic and epitranscriptomic modifications across RNA, DNA, proteins, and histones using LC–MS/MS—built for condition-to-condition comparisons (treated vs. control, KO vs. WT, time series, cohorts) and for orthogonal validation alongside sequencing or antibody-based enrichment assays.

Quantifiable outputs, not just "detected/not detected": per-sample abundance tables + QC summary + interpretation-ready plots
Multi-omics coverage in one portfolio: RNA/DNA modified nucleosides + protein PTMs + histone PTMs
Flexible analysis modes: targeted (hypothesis testing) or untargeted (discovery prioritization)
Reviewer-friendly reporting: transparent processing notes and evidence files (where applicable)

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Epigenetic and epitranscriptomic LC–MS/MS services overview showing RNA/DNA modifications, GlycoRNA analysis, and protein/histone PTM quantification.

Overview

This LC–MS/MS service is designed for epigenetics and epitranscriptomics teams that need quantitative, cross-sample comparable modification readouts—especially when the key question is "how much does a modification change across conditions?" or when you want orthogonal chemical validation for sequencing- or antibody-enrichment–based results. Deliverables typically include per-sample abundance matrices (by module), an optional group-level comparison summary, and QC/processing documentation suitable for reproducible reporting.

Please note that LC–MS/MS primarily provides global/panel-level quantification and does not assign modifications to specific transcripts or genomic loci; if positional mapping is required, we recommend pairing with site-resolved sequencing assays such as MeRIP-Seq or broader Epigenomics Sequencing Services.

This service uses liquid chromatography–tandem mass spectrometry (LC–MS/MS) to quantify:

(1) nucleic-acid modifications (RNA/DNA, typically measured as modified nucleosides after controlled processing),

(2) glycoRNA-associated glycan composition and enrichment-based signals (study-dependent), and

(3) protein and histone post-translational modifications (PTMs).

Service summary table (modules + measurable feature counts)

Module	What it measures	Measurable scope (as specified)
RNA modification MS (mRNA)	Modified nucleosides in mRNA	18 modification types
RNA modification MS (tRNA)	Modified nucleosides in tRNA	37 modification types
RNA modification MS (total RNA)	Modified nucleosides in total RNA	26 modification types
GlycoRNA glycomics MS	N-/O-glycan composition in small RNA fraction	60+ N-glycans; ~10 core2-type O-glycans
GlycoRNA modification MS (enriched fraction)	Enrichment-based detection of glycoRNA-associated signals	Discovery-oriented; examples include acp3U/galQ/manQ (feasibility-dependent)
DNA modification MS	Global DNA modification quantification	5mC + 5hmC (optional exploration of 5fC where feasible)
Protein PTM MS	PTM-focused proteomics	Glyco/phospho/methyl/acetyl/ubiquitin (study-dependent)
Histone PTM MS	Histone modification profiling	150+ histone PTM peptides

What this is best for

"How much does this modification change between groups?" (quantitative comparison)

"Is my sequencing/enrichment signal reflected in global abundance?" (orthogonal validation)

"Which conditions should I prioritize for deeper mapping?" (screening/prioritization)

Nucleic Acid

Nucleic Acid Modification Mass Spectrometry

A) RNA Modification Mass Spectrometry (mRNA / tRNA / total RNA)

RNA chemical modifications regulate RNA stability, structure, splicing/translation, and RNA–protein interactions. This module provides quantitative profiling of multiple modified nucleosides to support robust condition-to-condition comparisons.

Service specifications

Sample input: 0.5–1 µg RNA
Analyzable samples: mRNA, tRNA, and total RNA
MS acquisition: ~15 min per sample (method/instrument dependent)
Analysis mode: targeted or untargeted
Expected results: quantitative abundance readouts for the modification panels below (tables + QC + plots)

mRNA panel (18 detectable modifications)

#	Modification	Abbrev.
1	Dihydrouridine	D
2	5-hydroxymethylcytidine	hm5C
3	Pseudouridine	Ψ
4	3-methylcytidine	m3C
5	1-methyladenosine	m1A
6	5-methylcytidine	m5C
7	7-methylguanosine	m7G
8	2′-O-methylcytidine	Cm
9	Inosine	I

#	Modification	Abbrev.
10	5-methyluridine	m5U
11	5-formylcytidine	f5C
12	2′-O-methyluridine	Um
13	1-methylguanosine	m1G
14	2′-O-methylguanosine	Gm
15	N4-acetylcytidine	ac4C
16	2′-O-methyladenosine	Am
17	N6-methyladenosine	m6A
18	N6,2′-O-dimethyladenosine	m6Am

tRNA panel (37 detectable modifications)

#	Modification	Abbrev.
1	Dihydrouridine	D
2	Pseudouridine	Ψ
3	3-methylcytidine	m3C
4	1-methyladenosine	m1A
5	5-hydroxyuridine	ho5U
6	5-methylcytidine	m5C
7	1-methylpseudouridine	m1Ψ
8	7-methylguanosine	m7G
9	2′-O-methylcytidine	Cm
10	Inosine	I
11	5-methyluridine	m5U
12	5-formylcytidine	f5C
13	2′-O-methyluridine	Um
14	2-methyladenosine	m2A
15	1-methylguanosine	m1G
16	2′-O-methylguanosine	Gm
17	1-methylinosine	m1I
18	N2-methylguanosine	m2G
19	N4-acetylcytidine	ac4C

#	Modification	Abbrev.
20	2′-O-methyladenosine	Am
21	N6-methyladenosine	m6A
22	N2,N2-dimethylguanosine	m22G
23	N6-isopentenyladenosine	i6A
24	5-carboxymethyluridine	cm5U
25	2-thiocytidine	s2C
26	5-methoxycarbonylmethyluridine	mcm5U
27	5-carboxymethylaminomethyluridine	cmnm5U
28	5-methoxyuridine	mo5U
29	3-(3-amino-3-carboxypropyl)uridine	acp3U
30	uridine 5-oxyacetic acid	cmo5U
31	5-methoxycarbonylmethyl-2-thiouridine	mcm5s2U
32	5,2′-O-dimethyluridine	m5Um
33	2-methylthio-N6-threonylcarbamoyladenosine	ms2t6A
34	4-thiouridine	s4U
35	N6-threonylcarbamoyladenosine	t6A
36	2-thiouridine	s2U
37	5-methyl-2-thiouridine	m5s2U

total RNA panel (26 detectable modifications)

#	Modification	Abbrev.
1	Dihydrouridine	D
2	Pseudouridine	Ψ
3	3-methylcytidine	m3C
4	1-methyladenosine	m1A
5	5-methylcytidine	m5C
6	1-methylpseudouridine	m1Ψ
7	7-methylguanosine	m7G
8	2′-O-methylcytidine	Cm
9	Inosine	I
10	5-methyluridine	m5U
11	2′-O-methyluridine	Um
12	1-methylguanosine	m1G
13	2′-O-methylguanosine	Gm

#	Modification	Abbrev.
14	1-methylinosine	m1I
15	N2-methylguanosine	m2G
16	N4-acetylcytidine	ac4C
17	2′-O-methyladenosine	Am
18	N6-methyladenosine	m6A
19	N2,N2-dimethylguanosine	m22G
20	N6-isopentenyladenosine	i6A
21	5-carboxymethyluridine	cm5U
22	5-methoxycarbonylmethyluridine	mcm5U
23	5-carboxymethylaminomethyluridine	cmnm5U
24	5-methoxycarbonylmethyl-2-thiouridine	mcm5s2U
25	N6-threonylcarbamoyladenosine	t6A
26	3-methyluridine	m3U

How to choose the RNA module (quick, practical)

Choose mRNA: when your question is transcript regulation and you want mRNA-centric modified nucleoside quantification.
Choose tRNA: when you expect stress/translation remodeling or want a rich modification spectrum.
Choose total RNA: when you want a broad view (often dominated by abundant RNA species) for global shifts and screening.

B) GlycoRNA Glycomics Mass Spectrometry

GlycoRNA has been reported as RNA species linked to glycans and displayed at the cell surface, motivating glycan-composition profiling for hypothesis generation and comparative studies.

Service specifications

Sample input: 2–10 µg small RNA (consult for sample-type specifics)
Analyzable samples: small RNA fraction
Processing options: N-glycan profiling and/or O-glycan profiling (module selection by study goal)
MS options: LC-based analysis; MALDI can be considered for large cohorts depending on design
Expected results: composition-level quantification of 60+ N-glycans and ~10 core2-type O-glycans (reported as quantitative features suitable for group comparison)

C) GlycoRNA Modification Mass Spectrometry (Enriched Fraction)

Because glycoRNA abundance is expected to be very low, this module is designed around enrichment + LC–MS/MS detection for discovery-oriented profiling.

Service specifications

Sample input: 30–120 µg total RNA (consult recommended range by sample type)
Analyzable samples: enriched glycoRNA fraction
MS acquisition: ~20 min per sample (method/instrument dependent)
Analysis mode: untargeted/discovery-oriented
Expected results: detection of glycoRNA-linked modification signals and co-existing features (examples include acp3U/galQ/manQ, feasibility-dependent and guided by controls)

For transcript- or site-resolved mapping to complement enrichment-based LC–MS/MS signals, see our GlycoRNA-Seq service.

D) DNA Modification Mass Spectrometry

This module provides a quantitative global readout of DNA methylation and hydroxymethylation markers to support epigenetic comparisons and orthogonal validation.

Service specifications

Sample input: 0.5–1 µg
Analyzable samples: DNA
MS acquisition: ~15 min per sample (method/instrument dependent)
Analysis method: global DNA modification quantification (configured to project goals)
Expected results: standard detection of 5mC and 5hmC; optional exploration of 5fC where feasible (standards/controls may be recommended)

Protein PTM

Protein Modification Mass Spectrometry (PTM Proteomics)

Protein PTMs connect signaling, metabolism, and transcriptional control. This module supports PTM-oriented proteomics to capture PTM shifts that may regulate epigenetic writers/erasers/readers, transcription factors, and chromatin-associated complexes.

Service specifications

Analyzable samples (examples): cells, tissues, purified protein; biofluids such as serum/urine/CSF by consultation
Sample input (typical references): cells ≥ 1×10^7 per sample; protein ≥ 1 mg per sample (study dependent)
Analysis mode: PTM-focused workflows aligned to project goals (e.g., glycoproteomics, phosphoproteomics)
Expected results: quantitative outputs at peptide/site/protein level (method dependent), with PTM-category summaries and prioritized change lists

Common PTM categories supported (study dependent)

Glycosylation
Phosphorylation
Methylation
Acetylation
Ubiquitination

What you get (in practical terms)

PTM-centric quant tables (per sample) + group comparison summaries (if design supports)
Identification/confidence notes and QC summary
Top-changes list to guide mechanism experiments and targeted follow-up

Histone PTM

Histone Modification Mass Spectrometry

Histone PTMs are core epigenetic regulators. Histone MS provides a multi-mark, parallel view of chromatin state shifts and can complement ChIP-based assays by offering broad mark coverage in one measurement.

Service specifications

Sample input: 1–10 µg histone extract
Analyzable samples: histone extracts from cells or tissues
Sample processing: histone extraction + MS pre-processing (workflow depends on sample type)
MS acquisition: ~20 min per sample (method/instrument dependent)
Analysis method: quantitative histone PTM profiling
Expected results: detection and quantification of 150+ histone PTM peptides (module definition), supporting cross-mark interpretation and follow-up mark selection

Representative histone marks frequently reported (illustrative subset)

H3K4me1/2/3, H3K9me1/2/3, H3K9ac, H3S10ph, H3K14ac, H3K18ac, H3K27me1/2/3, H3K27ac, H3K36me1/2/3, H3K56me1/2/3, H3K56ac, H3K79me1/2/3, H4K5ac, H4K8ac, H4K12ac, H4K16ac, H4K20me1/2/3, etc.

Applications

This service is typically selected when you need quantitative, decision-ready outputs:

Mechanism studies: evaluate how perturbing writers/erasers/readers changes RNA/DNA marks and histone/protein PTMs.
Orthogonal validation: confirm whether sequencing/enrichment signals reflect real abundance shifts at the nucleoside/PTM level.
Screening & prioritization: rank treatments/conditions before deeper locus mapping (e.g., which condition shows the strongest global shift).
Multi-layer regulation: align RNA modification trends with histone marks and protein PTM pathways for coherent interpretation.
GlycoRNA exploration: compare glycan composition and enrichment-based signals across conditions.

Quick selection guide

Your question	Suggested module
"Is global m6A/m5C/m7G changing across conditions?"	RNA modification MS (mRNA)
"Do tRNA modifications remodel under stress?"	RNA modification MS (tRNA)
"I want a broad screening readout of RNA modifications."	RNA modification MS (total RNA)
"Is DNA methylation/hydroxymethylation shifting globally?"	DNA modification MS
"Which histone marks shift in parallel?"	Histone PTM MS
"Are PTM pathways changing with epigenetic perturbation?"	Protein PTM MS
"I want glycoRNA-related glycan composition profiles."	GlycoRNA glycomics MS
"I want enrichment-based glycoRNA signal exploration."	GlycoRNA modification MS

Workflow

Service Workflow

Project definition (study goal → module choice)
We align the module(s) to your biology question, sample types, and comparison design (groups, replicates, and expected effect sizes). This step determines whether targeted confirmation or untargeted discovery is the best fit.
Sample intake and QC/feasibility review
We review sample matrix, extraction background, and feasibility for each module. Where needed, we recommend cleanup/enrichment to reduce confounders (e.g., salts, detergents, carryover).
Module-specific sample processing
- RNA/DNA modules: processed into measurable analytes for LC–MS/MS quantification.
- Protein/histone modules: extraction/digestion workflows and PTM-appropriate preparation (project-defined).
- GlycoRNA modules: small RNA fraction processing or enrichment-based preparation (study-defined).
LC–MS/MS acquisition and run-level QC
Run design includes appropriate QC checks and method settings aligned to the selected module. Acquisition parameters are selected to support quantitative comparability across groups.
Data processing, normalization, and QC reporting
Peak integration, QC checks, and normalization strategy (when applicable). Replicate consistency and outlier flags are documented so your team can trust the comparisons.
Reporting and handoff
You receive a report package with tables, QC summaries, and plots that can be directly used for internal decisions, presentations, and manuscript figures (RUO).

Six-step LC–MS/MS workflow from project definition and sample QC to processing, acquisition, data QC, and reporting.

Bioinfo

Bioinformatics & Data Analysis

Your outputs are designed to be "action-ready": easy to compare groups, defend in peer review, and select follow-up experiments.

Analysis component	What you receive	Why it matters
Quantification matrices	per-sample abundance tables (CSV/XLSX) + group summaries	immediate comparisons, plotting, and downstream stats
QC summary	run-level QC notes, flagged items, consistency checks	confidence in comparability across groups
Evidence files (as applicable)	representative chromatograms / peak integration snapshots	supports interpretability and reporting
Visualization	box/bar plots, heatmaps, PCA/cluster (when appropriate)	fast decision-making and presentation-ready outputs
Comparative outputs (optional)	fold-change summaries, effect size tables	helps prioritize conditions/targets
Interpretation notes	short, study-aligned summary of key findings	turns numbers into next-step actions

Deliverables

You receive a deliverable set intended for fast decisions and easy collaboration:

Results tables
- per-sample quantification matrix
- group summary table (if grouping provided)
- optional comparison table (fold change / effect size, if requested)
QC package
- run-level QC summary and any exceptions
- replicate consistency notes (where applicable)
- evidence snapshots (representative, as applicable)
Figure set
- plots suitable for internal review and manuscript drafting (RUO)
- optional PCA/heatmap if sample design supports
Methods snapshot
- concise process summary suitable for a Methods section (RUO)
- module-specific notes that support reproducibility

Epigenetic modification mass spectrometry demo collage with RNA modification heatmap, LC–MS/MS chromatogram QC, histone PTM volcano plot, and deliverables table preview.

Samples

Sample Requirements

Accepted sample types

RNA: mRNA, tRNA, total RNA; small RNA fraction (for glycoRNA glycomics)
DNA: genomic DNA
Protein: cells/tissues/purified protein; selected biofluids by consultation
Histones: histone extracts from cells or tissues

Sample requirement table

Module	Sample type	Input amount (as specified)
RNA modification MS (mRNA/tRNA/total RNA)	RNA	0.5–1 µg
GlycoRNA glycomics MS	small RNA fraction	2–10 µg
GlycoRNA modification MS (enriched fraction)	total RNA	30–120 µg
DNA modification MS	DNA	0.5–1 µg
Protein PTM MS	cells or protein (examples)	cells ≥ 1×10^7; protein ≥ 1 mg
Histone PTM MS	histone extract	1–10 µg

Case

Case Study: LC–MS/MS Quantifies tRNA m⁷G Remodeling in Esophageal Cancer

Title: N7-methylguanosine tRNA modification promotes esophageal squamous cell carcinoma tumorigenesis via the RPTOR/ULK1/autophagy axis

Han H et al. Nature Communications, 2022.

Background

ESCC models show a strong reliance on tRNA m⁷G regulation, making quantitative m⁷G measurement important for linking epitranscriptomic changes to phenotype.

Methods

The authors used LC–MS to quantify tRNA m⁷G (nucleoside-level readout) alongside tRNA m⁷G mapping and functional assays, comparing METTL1 perturbation versus control.

Results

LC–MS confirmed that METTL1 depletion reduces tRNA m⁷G abundance, supporting a causal chain from "writer perturbation → mark loss → downstream pathway effects."

Conclusions

This work illustrates why LC–MS/MS is a preferred orthogonal validation + quantification layer in epitranscriptomics: it converts modification signals into comparable numbers across conditions.

LC–MS quantification confirms reduced tRNA m⁷G following METTL1 perturbation in ESCC models (adapted from Han H et al., Nature Communications, 2022; Fig. 3d)

FAQ

References

Xie Y, Brás-Costa C, Lin Z, Garcia BA. Mass Spectrometry Analysis of Nucleic Acid Modifications: From Beginning to Future. Mass Spectrometry Reviews. 2024.
Xie Y, Chai P, Till NA, et al. The modified RNA base acp3U is an attachment site for N-glycans in glycoRNA. Cell. 2024.
Kellner S. et al. Absolute and relative quantification of RNA modifications via biosynthetic isotopomers. Nucleic Acids Research (2014).
Mathur L. et al. Quantitative analysis of m6A RNA modification by LC–MS. STAR Protocols (2021).
Flynn RA, Pedram K, Malaker SA, et al. Small RNAs are modified with N-glycans and displayed on the surface of living cells. Cell. 2021.

! For research purposes only. Not intended for clinical diagnosis, treatment, or individual health assessments.