2017
DOI: 10.1101/gr.225896.117
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Evolutionary expansion of DNA hypomethylation in the mammalian germline genome

Abstract: DNA methylation in the germline is among the most important factors influencing the evolution of mammalian genomes. Yet little is known about its evolutionary rate or the fraction of the methylome that has undergone change. We compared whole-genome, single-CpG DNA methylation profiles in sperm of seven species-human, chimpanzee, gorilla, rhesus macaque, mouse, rat, and dog-to investigate epigenomic evolution. We developed a phylo-epigenetic model for DNA methylation that accommodates the correlation of states … Show more

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Cited by 34 publications
(68 citation statements)
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“…Germline DNA methylation can potentially leave an evolutionary signature in the genome due to the hypermutability of methylated cytosines and less mutable nature of unmethylated cytosines. A comparison of sperm methylome data across human, chimpanzee, gorilla, rhesus, mouse, rat and dog found a genome wide evolutionary expansion of hypomethylation at CpG sites [29]. Primates and dog show a pattern of widening hypomethylation around transcription start sites into promoter flanking regions while rodents evolve new hypomethylated regions.…”
Section: Primate Sperm Methylome Datamentioning
confidence: 99%
See 2 more Smart Citations
“…Germline DNA methylation can potentially leave an evolutionary signature in the genome due to the hypermutability of methylated cytosines and less mutable nature of unmethylated cytosines. A comparison of sperm methylome data across human, chimpanzee, gorilla, rhesus, mouse, rat and dog found a genome wide evolutionary expansion of hypomethylation at CpG sites [29]. Primates and dog show a pattern of widening hypomethylation around transcription start sites into promoter flanking regions while rodents evolve new hypomethylated regions.…”
Section: Primate Sperm Methylome Datamentioning
confidence: 99%
“…Primates and dog show a pattern of widening hypomethylation around transcription start sites into promoter flanking regions while rodents evolve new hypomethylated regions. We compared methylation levels of promoter, promoter flanking, enhancer and general genomic regions between primate chromosome 19 orthologs and whole genomes using the methylation data from Qu, et al [29]. The promoter flanking and general genomic regions showed hypomethylation of chromosome 19 relative to genome wide levels in all the examined primates consisting of human, chimpanzee, gorilla and rhesus (Table S20), with an average methylation level 0.09 lower, while promoter and enhancer methylation was similar between chromosome 19 and the genome wide levels in all the examined primates consisting of human, chimpanzee, gorilla and rhesus (Table S20).…”
Section: Primate Sperm Methylome Datamentioning
confidence: 99%
See 1 more Smart Citation
“…CpG islands (CGIs), short stretches of CpG-rich regions, are an exception to the widespread DNAme observed in spermatozoa. Indeed, the vast majority of CGIs, which encompass the promoter regions of most housekeeping genes, are hypomethylated in mature male and female germ cells, as well as in early embryonic development 18,[28][29][30][31][32][33] . In addition, CGIs retain nucleosomes in spermatozoa, foregoing the exchange for protamines [28][29][30] .…”
Section: Introductionmentioning
confidence: 99%
“…Our new method incorporates the evolutionary affinity among multiple species into the hidden Markov model (HMM) for exploiting both temporal dependencies across species in the context of evolution and spatial dependencies along the genome in a continuous-trait model. Note that our Phylo-HMGP is fundamentally different from the existing models that are restricted to discrete state space of the studied traits (Siepel and Haussler, 2005;Hobolth et al, 2007;Liu et al, 2014;Jensen and Pedersen, 2000;Lunter and Hein, 2004;Qu et al, 2018). In particular, Phylo-HMMs define a stochastic process of discrete-trait character changes (Siepel and Haussler, 2005), where different states estimated by Phylo-HMMs can reflect different patterns of substitutions or background distributions.…”
Section: Introductionmentioning
confidence: 99%