Epigenetic modifications are cell fate building blocks, which play fundamental roles for establishing and maintaining cell identities and fates. With the accumulation of high-throughput biological data, it is demanding to develop computational frameworks to study the epigenetic heterogeneities and their roles in cell fate determinations. I will present three studies on epigenetic heterogeneity. First, we developed MethylTransition, a novel DNA methylation state transition model, for characterizing methylation changes during one or a few cell cycles at single-cell resolution. We applied MethylTransition to single-cell DNA methylome data from human embryogenesis, and elucidated 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. Second, we developed PCAR, a computational framework for call allele-specific H3K9me3 and DNA methylation co-marked regions and scoring allele-specific regulatory potential. We applied PCAR to allele-specific epigenetic map in gynogenetic and androgenetic mouse embryos, and predicted 22 ICR-like regions, of which five were validated to be critical for mouse embryo development. Third, we developed ncHMR detector, the first computational framework to predict non-classical functions and cofactors of a given histone modification regulator, based on ChIP-seq data mining. We applied ncHMR detector in ChIP-seq data-rich cell types, and revealed several regulators’ functional heterogeneities.
 

bioinformatics; epigenetic heterogeneity