bioRxivBioinformaticsPreprint
MC profiling: a novel approach to analyze DNA methylation heterogeneity from bulk bisulfite sequencing data
Giulia De RisoiD, Antonella SarnataroiD, Giovanni ScalaiD, Mariella CuomoiD, Rosa Della MonicaiD, Stefano AmenteiD, Lorenzo ChiariottiiD, Gennaro MieleiD, Sergio CocozzaiD
Abstract
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.
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- High-coverage allele-resolved single-cell DNA methylation profiling by scDEEP-mC reveals cell lineage, X-inactivation state, and replication dynamics
Nathan J. Spix, Walid Abi Habib, … Peter W. Laird·Nature CommunicationsPeer-reviewed·Jul 7, 2025
- BSImp: imputing partially observed methylation patterns for evaluating methylation heterogeneity
Ya-Ting Sabrina Chang, Ming‐Ren Yen, Pao‐Yang Chen·Frontiers in BioinformaticsPeer-reviewed·Feb 10, 2022
- Simultaneous profiling of DNA methylation and chromatin architecture in mixed populations and in single cells
Guoqiang Li, Yaping Liu, … Bing Ren·bioRxiv·Nov 15, 2018
- Melissa: Bayesian clustering and imputation of single cell methylomes
Chantriolnt-Andreas Kapourani, Guido Sanguinetti·Genome biologyPeer-reviewed·Mar 21, 2019
- scMET: Bayesian modelling of DNA methylation heterogeneity at single-cell resolution
Chantriolnt-Andreas Kapourani, Ricard Argelaguet, … Catalina A. Vallejos·Genome biologyPeer-reviewed·Apr 20, 2021
- Droplet-based bisulfite sequencing for high-throughput profiling of single-cell DNA methylomes
Qiang Zhang, Sai Ma, … Chang Lu·Nature CommunicationsPeer-reviewed·Aug 3, 2023