Literature DB >> 32613387

A Mathematical Model for Inheritance of DNA Methylation Patterns in Somatic Cells.

Kiersten Utsey1, James P Keener2,3.   

Abstract

DNA methylation is an essential epigenetic mechanism used by cells to regulate gene expression. Interestingly, DNA replication, a function necessary for cell division, disrupts the methylation pattern. Since perturbed methylation patterns are associated with aberrant gene expression and many diseases, including cancer, restoration of the correct pattern following DNA replication is crucial. However, the exact mechanisms of this restoration remain under investigation. DNA methyltransferases (Dnmts) perform methylation by adding a methyl group to cytosines at CpG sites in the DNA. These CpG sites are found in regions of high density, termed CpG islands (CGIs), and regions of low density in the genome. Nearly, every CpG site in a CGI has the same state, either methylated or unmethylated, and almost all CpG sites in regions of low CpG density are methylated. We propose a stochastic model for the dynamics of the post-replicative restoration of methylation patterns. The model considers the recruitment of Dnmts and demethylating enzymes to regions of hyper- and hypomethylation, respectively. The model also includes the interaction between Dnmt1 and PCNA, an enzyme that localizes Dnmt1 to the replication complex. Using our model, we predict that the methylation of regions of DNA can be bistable. Further, we predict that recruitment mechanisms maintain methylation in CGIs, whereas the Dnmt1-PCNA interaction maintains methylation in low-density regions.

Entities:  

Keywords:  Bistability; CpG island; DNA methyltransferase; Mean field approximation; Stochastic chemical reactions

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Year:  2020        PMID: 32613387     DOI: 10.1007/s11538-020-00765-4

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  2 in total

1.  Melatonin-induced suppression of DNA methylation promotes odontogenic differentiation in human dental pulp cells.

Authors:  Jingzhou Li; Qianyi Deng; Wenguo Fan; Qi Zeng; Hongwen He; Fang Huang
Journal:  Bioengineered       Date:  2020-12       Impact factor: 3.269

2.  Cluster mean-field theory accurately predicts statistical properties of large-scale DNA methylation patterns.

Authors:  Lyndsay Kerr; Duncan Sproul; Ramon Grima
Journal:  J R Soc Interface       Date:  2022-01-26       Impact factor: 4.118

  2 in total

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