Sarnataro, Antonella (2024) Dissecting DNA methylation patterns at single-molecule level from bulk bisulfite sequencing experiments. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Dissecting DNA methylation patterns at single-molecule level from bulk bisulfite sequencing experiments |
| Autori: | Autore Email Sarnataro, Antonella antonella.sarnataro@unina.it |
| Data: | 10 Marzo 2024 |
| Numero di pagine: | 70 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Ingegneria Elettrica e delle Tecnologie dell'Informazione |
| Dottorato: | Computational and quantitative biology |
| Ciclo di dottorato: | 36 |
| Coordinatore del Corso di dottorato: | nome email Ceccarelli, Michele michele.ceccarelli@unina.it |
| Tutor: | nome email Cocozza, Sergio [non definito] Giovanni, Scala [non definito] |
| Data: | 10 Marzo 2024 |
| Numero di pagine: | 70 |
| Parole chiave: | DNA methylation, epigenetics, cell-to-cell heterogeneity |
| Settori scientifico-disciplinari del MIUR: | Area 06 - Scienze mediche > MED/03 - Genetica medica |
| Depositato il: | 19 Giu 2024 12:21 |
| Ultima modifica: | 18 Mar 2026 10:48 |
| URI: | http://www.fedoa.unina.it/id/eprint/15499 |
Abstract
DNA methylation is one of the most well-studied epigenetic modifications and plays a central role in important biological processes, such as gene expression regulation, genome imprinting, and genome stability. In the mammalian genome, this modification occurs predominantly at CpG dinucleotides, with non-CpG methylation described only in specific cell lineages, such as neurons and embryonic stem cells. DNA methylation is a highly reversible and dynamic process, so there can be high variability in DNA methylation patterns between distinct cells. This variability in cell-to-cell DNA methylation has been depicted as a major driver of cellular plasticity, which in turn contributes to several pathophysiological processes. Over the last decade, several computational tools have been developed to extract DNA methylation heterogeneity information from bulk bisulfite sequencing, avoiding the experimental and practical limitations of single-cells assays. However, most of these tools lack additional functionalities for a comprehensive analysis of DNA methylation heterogeneity. This work contributes to the previous research in this field by developing a novel computational workflow designed for the analysis of both CpG and non-CpG-based DNA methylation patterns. Offering customizable user-driven analyses, strand-specific heterogeneity assessments, locus annotation, and gene set enrichment analyses, EpiStatProfiler adds versatility to the exploration of DNA methylation patterns. Finally, it is also shown that extending the workflow for extracting and analyzing DNA methylation patterns to third-generation sequencing experiments can be valuable to provide novel insights into the foundation of epigenetic heterogeneity in both normal and pathological conditions.
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