DNA methylation reprogramming of functional elements during mammalian embryonic development.
Congru LiYong FanGuoqiang LiXiaocui XuJialei DuanRong LiXiangjin KangXin MaXuepeng ChenYuwen KeJie YanYing LianPing LiuYue ZhaoHongcui ZhaoYaoyong ChenYang YuJiang LiuPublished in: Cell discovery (2018)
DNA methylation plays important roles during development. However, the DNA methylation reprogramming of functional elements has not been fully investigated during mammalian embryonic development. Herein, using our modified MethylC-Seq library generation method and published post-bisulphite adapter-tagging (PBAT) method, we generated genome-wide DNA methylomes of human gametes and early embryos at single-base resolution and compared them with mouse methylomes. We showed that the dynamics of DNA methylation in functional elements are conserved between humans and mice during early embryogenesis, except for satellite repeats. We further found that oocyte-specific hypomethylated promoters usually exhibit low CpG densities. Genes with oocyte-specific hypomethylated promoters generally show oocyte-specific hypomethylated genic and intergenic regions, and these hypomethylated regions contribute to the hypomethylation pattern of mammalian oocytes. Furthermore, hypomethylated genic regions with low CG densities correlate with gene silencing in oocytes, whereas hypomethylated genic regions with high CG densities correspond to high gene expression. We further show that methylation reprogramming of enhancers during early embryogenesis is highly associated with the development of almost all human organs. Our data support the hypothesis that DNA methylation plays important roles during mammalian development.
Keyphrases
- single cell
- dna methylation
- genome wide
- gene expression
- endothelial cells
- copy number
- single molecule
- induced pluripotent stem cells
- pluripotent stem cells
- electronic health record
- big data
- transcription factor
- type diabetes
- metabolic syndrome
- genome wide identification
- atomic force microscopy
- deep learning
- genome wide analysis
- wild type