Evidence map›Paper›PMID 36601577›Full record

ArticleNAR genomics and bioinformatics2022

MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data.

Giulia De Riso, Antonella Sarnataro, Giovanni Scala, Mariella Cuomo, Rosa Della Monica, Stefano Amente, Lorenzo Chiariotti, Gennaro Miele, Sergio Cocozza

Open access · goldAbstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 55% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Giulia De RisoDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.ORCID https://orcid.org/0000-0001-6096-132X
Antonella SarnataroDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.
Giovanni ScalaDepartment of Biology, University of Naples Federico II, Via Vicinale Cupa Cintia 21, 80126 Naples, Italy.
Mariella CuomoDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.
Rosa Della MonicaCEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145 Naples, Italy.ORCID https://orcid.org/0000-0002-5933-5556
Stefano AmenteDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.ORCID https://orcid.org/0000-0003-0612-6096
Lorenzo ChiariottiDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.
Gennaro MieleDepartment of Physics "E. Pancini", University of Naples "Federico II", Via Cinthia, 80126 Naples, Italy.
Sergio CocozzaDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.
University of Naples Federico II · ITCeinge Biotecnologie Avanzate (Italy) · ITIstituto Nazionale di Fisica Nucleare, Sezione di Napoli · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID36601577
PMCPMC9803872
OpenAlexW4313318481

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.