Whole-genome bisulphite sequencing data from diverse human cell and tissue types shows that only about 22% of CpGs change their methylation state across these cell types; most of these CpGs are located at gene regulatory elements, particularly enhancers and transcription-factor-binding sites, and these selected regions with dynamic DNA methylation patterns could help to define putative regulatory elements further. The methylation of cytosine, usually at CpGs, is a common feature of epigenetic regulation of gene expression. Most cell types have relatively stable CpG dinucleotide methylation patterns and our understanding of which CpGs participate in genomic regulation is limited. Here, Meissner and colleagues analyse whole-genome bisulphite sequencing data sets across diverse human cell and tissue types and find that only about 22% of CpGs change their methylation state across these. Most of these CpGs are located at putative gene regulatory elements, particularly enhancers and transcription-factor-binding sites. In addition to further clarifying the distribution of DNA methylation, these selected regions with dynamic DNA methylation patterns could help guide more efficient genomic approaches to focus on informative regions, as well as help define regulatory elements. DNA methylation is a defining feature of mammalian cellular identity and is essential for normal development1,2. Most cell types, except germ cells and pre-implantation embryos3,4,5, display relatively stable DNA methylation patterns, with 70–80% of all CpGs being methylated6. Despite recent advances, we still have a limited understanding of when, where and how many CpGs participate in genomic regulation. Here we report the in-depth analysis of 42 whole-genome bisulphite sequencing data sets across 30 diverse human cell and tissue types. We observe dynamic regulation for only 21.8% of autosomal CpGs within a normal developmental context, most of which are distal to transcription start sites. These dynamic CpGs co-localize with gene regulatory elements, particularly enhancers and transcription-factor-binding sites, which allow identification of key lineage-specific regulators. In addition, differentially methylated regions (DMRs) often contain single nucleotide polymorphisms associated with cell-type-related diseases as determined by genome-wide association studies. The results also highlight the general inefficiency of whole-genome bisulphite sequencing, as 70–80% of the sequencing reads across these data sets provided little or no relevant information about CpG methylation. To demonstrate further the utility of our DMR set, we use it to classify unknown samples and identify representative signature regions that recapitulate major DNA methylation dynamics. In summary, although in theory every CpG can change its methylation state, our results suggest that only a fraction does so as part of coordinated regulatory programs. Therefore, our selected DMRs can serve as a starting point to guide new, more effective reduced representation approaches to capture the most informative fraction of CpGs, as well as further pinpoint putative regulatory elements.

The hypothalamic arcuate–median eminence (Arc-ME) complex is rich with functionally distinct cell types, a fraction of which have been characterized. The authors profile 20,921 individual cells by single-cell RNA-seq, identifying 50 Arc-ME cell types and their markers, determining each's response to energy status and implicating two neuron populations in the genetic control of obesity. The hypothalamic arcuate–median eminence complex (Arc-ME) controls energy balance, fertility and growth through molecularly distinct cell types, many of which remain unknown. To catalog cell types in an unbiased way, we profiled gene expression in 20,921 individual cells in and around the adult mouse Arc-ME using Drop-seq. We identify 50 transcriptionally distinct Arc-ME cell populations, including a rare tanycyte population at the Arc-ME diffusion barrier, a new leptin-sensing neuron population, multiple agouti-related peptide (AgRP) and pro-opiomelanocortin (POMC) subtypes, and an orexigenic somatostatin neuron population. We extended Drop-seq to detect dynamic expression changes across relevant physiological perturbations, revealing cell type–specific responses to energy status, including distinct responses in AgRP and POMC neuron subtypes. Finally, integrating our data with human genome-wide association study data implicates two previously unknown neuron populations in the genetic control of obesity. This resource will accelerate biological discovery by providing insights into molecular and cell type diversity from which function can be inferred.