MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data.
Journal
NAR genomics and bioinformatics
ISSN: 2631-9268
Titre abrégé: NAR Genom Bioinform
Pays: England
ID NLM: 101756213
Informations de publication
Date de publication:
Dec 2022
Dec 2022
Historique:
received:
13
09
2022
revised:
24
11
2022
accepted:
08
12
2022
entrez:
5
1
2023
pubmed:
6
1
2023
medline:
6
1
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 36601577
doi: 10.1093/nargab/lqac096
pii: lqac096
pmc: PMC9803872
doi:
Types de publication
Journal Article
Langues
eng
Pagination
lqac096Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.
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