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A DNA methylation state transition model reveals the programmed epigenetic heterogeneity in human pre-implantation embryos

BACKGROUND: During mammalian early embryogenesis, expression and epigenetic heterogeneity emerge before the first cell fate determination, but the programs causing such determinate heterogeneity are largely unexplored. RESULTS: Here, we present MethylTransition, a novel DNA methylation state transit...

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Detalles Bibliográficos
Autores principales: Zhao, Chengchen, Zhang, Naiqian, Zhang, Yalin, Tuersunjiang, Nuermaimaiti, Gao, Shaorong, Liu, Wenqiang, Zhang, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7667739/
https://www.ncbi.nlm.nih.gov/pubmed/33198783
http://dx.doi.org/10.1186/s13059-020-02189-8
Descripción
Sumario:BACKGROUND: During mammalian early embryogenesis, expression and epigenetic heterogeneity emerge before the first cell fate determination, but the programs causing such determinate heterogeneity are largely unexplored. RESULTS: Here, we present MethylTransition, a novel DNA methylation state transition model, for characterizing methylation changes during one or a few cell cycles at single-cell resolution. MethylTransition involves the creation of a transition matrix comprising three parameters that represent the probabilities of DNA methylation-modifying activities in order to link the methylation states before and after a cell cycle. We apply MethylTransition to single-cell DNA methylome data from human pre-implantation embryogenesis and elucidate that the DNA methylation heterogeneity that emerges at promoters during this process is largely an intrinsic output of a program with unique probabilities of DNA methylation-modifying activities. Moreover, we experimentally validate the effect of the initial DNA methylation on expression heterogeneity in pre-implantation mouse embryos. CONCLUSIONS: Our study reveals the programmed DNA methylation heterogeneity during human pre-implantation embryogenesis through a novel mathematical model and provides valuable clues for identifying the driving factors of the first cell fate determination during this process. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s13059-020-02189-8.