A DNA methylation state transition model reveals the programmed epigenetic heterogeneity in human pre-implantation embryos
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. Here, we present MethylTransition, a novel DNA methylation state transition model, for charac...
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Published in | Genome Biology Vol. 21; no. 1; p. 277 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
BioMed Central
16.11.2020
BMC |
Subjects | |
Online Access | Get full text |
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Summary: | 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.
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.
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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1474-760X 1474-7596 1474-760X |
DOI: | 10.1186/s13059-020-02189-8 |