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Related Experiment Video

Updated: Oct 22, 2025

Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

Published on: September 7, 2017

Human non-CpG methylation patterns display both tissue-specific and inter-individual differences suggestive of

Philip Titcombe¹, Robert Murray², Matthew Hewitt²

¹MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK.

|August 31, 2021

Summary

Non-CpG DNA methylation shows distinct patterns. CAC methylation is tissue-specific, while CAT methylation reflects individual variations, offering insights into the broader methylome.

Keywords:

CAC CAT CHG CHH CNN CpG DNA methylation HCA cluster comparison hierarchical clustering analysis human individual-specific methylation methylation patterns muscle non-CpG peripheral blood tissue-specific umbilical cord umbilical cord blood

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Immunohistochemical Detection of 5-Methylcytosine and 5-Hydroxymethylcytosine in Developing and Postmitotic Mouse Retina

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Last Updated: Oct 22, 2025

Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

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Immunohistochemical Detection of 5-Methylcytosine and 5-Hydroxymethylcytosine in Developing and Postmitotic Mouse Retina

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Published on: August 29, 2018

Area of Science:

Epigenetics
Genomics

Background:

DNA methylation (DNAm) is crucial in mammals, primarily studied at CpG sites.
Non-CpG DNAm is prevalent but less understood regarding its functional relevance, tissue distribution, and individual variability.

Purpose of the Study:

To investigate non-CpG DNAm across multiple tissues from the same individuals.
To understand the distribution of non-CpG DNAm in different tissues and individuals.
To correlate non-CpG DNAm with genomic regulatory features.

Main Methods:

Methylation sequencing (methyl-seq) of DNA from umbilical cord, cord blood, and peripheral venous blood.
Hierarchical cluster analysis (HCA) of CpG and non-CpG sites, stratified by cytosine context (CNN).
Analysis of tissue and inter-individual variation in a second dataset including muscle and cord blood samples.

Main Results:

Non-CpG methylation clustering patterns differed based on the CNN sequence context.
CAC methylation sites showed tissue-specific clustering, followed by individual clustering.
CAT methylation sites predominantly clustered by individual, indicating strong personal influence.

Conclusions:

CAC DNA methylation exhibits tissue-specific characteristics.
CAT DNA methylation is significantly influenced by individual factors, potentially genetic or environmental.
This study highlights the complex, context-dependent nature of non-CpG DNA methylation.