Integrative single-cell omics analyses reveal epigenetic heterogeneity in mouse embryonic stem cells

Embryonic stem cells (ESCs) consist of a population of self-renewing cells displaying extensive phenotypic and functional heterogeneity. Research towards the understanding of the epigenetic mechanisms underlying the heterogeneity among ESCs is still in its initial stage. Key issues, such as how to identify cell-subset specifically methylated loci and how to interpret the biological meanings of methylation variations remain largely unexplored. To fill in the research gap, we implemented a computational pipeline to analyze single-cell methylome and to perform an integrative analysis with single-cell transcriptome data. According to the origins of variation in DNA methylation, we determined the genomic loci associated with allelic-specific methylation or asymmetric DNA methylation, and explored a beta mixture model to infer the genomic loci exhibiting cell-subset specific methylation (CSM). We observed that the putative CSM loci in ESCs are significantly enriched in CpG island (CGI) shelves and regions with histone marks for promoter and enhancer, and the genes hosting putative CSM loci show wide-ranging expression among ESCs. More interestingly, the putative CSM loci may be clustered into co-methylated modules enriching the binding motifs of distinct sets of transcription factors. Taken together, our study provided a novel tool to explore single-cell methylome and transcriptome to reveal the underlying transcriptional regulatory networks associated with epigenetic heterogeneity of ESCs.Author summary: DNA methylation is an epigenetic mark with covalent modification that occurs directly on genetic material. In vertebrates, the most common form of DNA methylation is 5-methylcytosine (5-mC) at which a methyl group (CH3) is attached to the cytosine nucleotide, especially in the context of CpG dinucleotide. DNA methylation has important regulatory roles in a broad range of biological processes and diseases, such as embryonic stem cells (ESCs) differentiation and development. ESC populations can be strikingly heterogeneous in DNA methylation. Emerging single-cell methods for capturing DNA methylation are being developed with the exciting potential to investigate the DNA methylation feature within complex and heterogeneous tissues. In this study, we implemented a computational pipeline to infer cell-subset specific methylation of ESCs from single-cell methylome. Through integrative analyses with transcription factor binding and single-cell transcriptome, we explored the underlying regulatory mechanisms associated with methylation heterogeneity in ESCs to interpret the biological functional relevance of methylation variations.