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)
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)
"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)
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)
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)
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).
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
