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Experimental and Computational Approaches for Non-CpG Methylation Analysis
Cytosine methylation adjacent to adenine, thymine, and cytosine residues but not guanine of the DNA is distinctively known as non-CpG methylation. This CA/CT/CC methylation accounts for 15% of the total cytosine methylation and varies among different cell and tissue types. The abundance of CpG methy...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9397002/ https://www.ncbi.nlm.nih.gov/pubmed/35997370 http://dx.doi.org/10.3390/epigenomes6030024 |
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author | Ramasamy, Deepa Rao, Arunagiri Kuha Deva Magendhra Rajkumar, Thangarajan Mani, Samson |
author_facet | Ramasamy, Deepa Rao, Arunagiri Kuha Deva Magendhra Rajkumar, Thangarajan Mani, Samson |
author_sort | Ramasamy, Deepa |
collection | PubMed |
description | Cytosine methylation adjacent to adenine, thymine, and cytosine residues but not guanine of the DNA is distinctively known as non-CpG methylation. This CA/CT/CC methylation accounts for 15% of the total cytosine methylation and varies among different cell and tissue types. The abundance of CpG methylation has largely concealed the role of non-CpG methylation. Limitations in the early detection methods could not distinguish CpG methylation from non-CpG methylation. Recent advancements in enrichment strategies and high throughput sequencing technologies have enabled the detection of non-CpG methylation. This review discusses the advanced experimental and computational approaches to detect and describe the genomic distribution and function of non-CpG methylation. We present different approaches such as enzyme-based and antibody-based enrichment, which, when coupled, can also improve the sensitivity and specificity of non-CpG detection. We also describe the current bioinformatics pipelines and their specific application in computing and visualizing the imbalance of CpG and non-CpG methylation. Enrichment modes and the computational suites need to be further developed to ease the challenges of understanding the functional role of non-CpG methylation. |
format | Online Article Text |
id | pubmed-9397002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93970022022-08-24 Experimental and Computational Approaches for Non-CpG Methylation Analysis Ramasamy, Deepa Rao, Arunagiri Kuha Deva Magendhra Rajkumar, Thangarajan Mani, Samson Epigenomes Review Cytosine methylation adjacent to adenine, thymine, and cytosine residues but not guanine of the DNA is distinctively known as non-CpG methylation. This CA/CT/CC methylation accounts for 15% of the total cytosine methylation and varies among different cell and tissue types. The abundance of CpG methylation has largely concealed the role of non-CpG methylation. Limitations in the early detection methods could not distinguish CpG methylation from non-CpG methylation. Recent advancements in enrichment strategies and high throughput sequencing technologies have enabled the detection of non-CpG methylation. This review discusses the advanced experimental and computational approaches to detect and describe the genomic distribution and function of non-CpG methylation. We present different approaches such as enzyme-based and antibody-based enrichment, which, when coupled, can also improve the sensitivity and specificity of non-CpG detection. We also describe the current bioinformatics pipelines and their specific application in computing and visualizing the imbalance of CpG and non-CpG methylation. Enrichment modes and the computational suites need to be further developed to ease the challenges of understanding the functional role of non-CpG methylation. MDPI 2022-08-16 /pmc/articles/PMC9397002/ /pubmed/35997370 http://dx.doi.org/10.3390/epigenomes6030024 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Ramasamy, Deepa Rao, Arunagiri Kuha Deva Magendhra Rajkumar, Thangarajan Mani, Samson Experimental and Computational Approaches for Non-CpG Methylation Analysis |
title | Experimental and Computational Approaches for Non-CpG Methylation Analysis |
title_full | Experimental and Computational Approaches for Non-CpG Methylation Analysis |
title_fullStr | Experimental and Computational Approaches for Non-CpG Methylation Analysis |
title_full_unstemmed | Experimental and Computational Approaches for Non-CpG Methylation Analysis |
title_short | Experimental and Computational Approaches for Non-CpG Methylation Analysis |
title_sort | experimental and computational approaches for non-cpg methylation analysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9397002/ https://www.ncbi.nlm.nih.gov/pubmed/35997370 http://dx.doi.org/10.3390/epigenomes6030024 |
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