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MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data
DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated c...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803872/ https://www.ncbi.nlm.nih.gov/pubmed/36601577 http://dx.doi.org/10.1093/nargab/lqac096 |
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author | De Riso, Giulia Sarnataro, Antonella Scala, Giovanni Cuomo, Mariella Della Monica, Rosa Amente, Stefano Chiariotti, Lorenzo Miele, Gennaro Cocozza, Sergio |
author_facet | De Riso, Giulia Sarnataro, Antonella Scala, Giovanni Cuomo, Mariella Della Monica, Rosa Amente, Stefano Chiariotti, Lorenzo Miele, Gennaro Cocozza, Sergio |
author_sort | De Riso, Giulia |
collection | PubMed |
description | DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule. Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule. By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation. Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions. |
format | Online Article Text |
id | pubmed-9803872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98038722023-01-03 MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data De Riso, Giulia Sarnataro, Antonella Scala, Giovanni Cuomo, Mariella Della Monica, Rosa Amente, Stefano Chiariotti, Lorenzo Miele, Gennaro Cocozza, Sergio NAR Genom Bioinform High Throughput Sequencing Methods DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule. Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule. By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation. Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions. Oxford University Press 2022-12-31 /pmc/articles/PMC9803872/ /pubmed/36601577 http://dx.doi.org/10.1093/nargab/lqac096 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | High Throughput Sequencing Methods De Riso, Giulia Sarnataro, Antonella Scala, Giovanni Cuomo, Mariella Della Monica, Rosa Amente, Stefano Chiariotti, Lorenzo Miele, Gennaro Cocozza, Sergio MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data |
title | MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data |
title_full | MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data |
title_fullStr | MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data |
title_full_unstemmed | MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data |
title_short | MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data |
title_sort | mc profiling: a novel approach to analyze dna methylation heterogeneity in genome-wide bisulfite sequencing data |
topic | High Throughput Sequencing Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803872/ https://www.ncbi.nlm.nih.gov/pubmed/36601577 http://dx.doi.org/10.1093/nargab/lqac096 |
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