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Review
. 2022 Jan 20;13(2):178.
doi: 10.3390/genes13020178.

Epigenomic Modifications in Modern and Ancient Genomes

Affiliations
Review

Epigenomic Modifications in Modern and Ancient Genomes

Laura Niiranen et al. Genes (Basel). .

Abstract

Epigenetic changes have been identified as a major driver of fundamental metabolic pathways. More specifically, the importance of epigenetic regulatory mechanisms for biological processes like speciation and embryogenesis has been well documented and revealed the direct link between epigenetic modifications and various diseases. In this review, we focus on epigenetic changes in animals with special attention on human DNA methylation utilizing ancient and modern genomes. Acknowledging the latest developments in ancient DNA research, we further discuss paleoepigenomic approaches as the only means to infer epigenetic changes in the past. Investigating genome-wide methylation patterns of ancient humans may ultimately yield in a more comprehensive understanding of how our ancestors have adapted to the changing environment, and modified their lifestyles accordingly. We discuss the difficulties of working with ancient DNA in particular utilizing paleoepigenomic approaches, and assess new paleoepigenomic data, which might be helpful in future studies.

Keywords: DNA methylation; ancient DNA; diet; epigenetics; lifestyle diseases; paleoepigenomics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schema of the regulation of protein synthesis through microRNA binding leading to mRNA degradation and downregulation of translational processes. Created with BioRender.com, accessed on 2 December 2021.
Figure 2
Figure 2
Schema of cytosine methylation by SAM in CpG positions. Created with BioRender.com, accessed on 2 December 2021.
Figure 3
Figure 3
Number of non-covered CpG positions in relation to the average genome-wide coverage. Please note that the maximum average genome-wide coverages per individual are as follows: ans017—24×, SF12—38×, and Stuttgart (Stu)—19×, respectively.
Figure 4
Figure 4
Standard deviations of Delta f in relation to the average genome-wide coverage. Trendlines are shown as dotted lines and the respective equations with accompanied R2 values are listed in the legend.

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