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Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.In this Review, Preissl, Gaulton and Ren discuss single-cell epigenomic methods and data analysis tools, their readiness for profiling cis-regulatory elements in human tissues and the insight they can provide into dynamic, context-specific gene regulation.

Pdgfra-expressing (Pdgfra+) cells have been implicated as progenitors in many mesenchymal tissues. To determine lineage potential, we generated PdgfrartTA knockin mice using CRISPR/Cas9. During lung maturation, counter to a prior study reporting that Pdgfra+ cells give rise equally to myofibroblasts and lipofibroblasts, lineage tracing using PdgfrartTA;tetO-cre mice indicated that ~95% of the lineaged cells are myofibroblasts. Genetic ablation of Pdgfra+ cells using PdgfrartTA-driven diphtheria toxin (DTA) led to alveolar simplification, demonstrating that these cells are essential for building the gas exchange surface area. In the adult bleomycin model of lung fibrosis, lineaged cells increased to contribute to pathological myofibroblasts. In contrast, in a neonatal hyperoxia model of bronchopulmonary dysplasia (BPD), lineaged cells decreased and do not substantially contribute to pathological myofibroblasts. Our findings revealed complexity in the behavior of the Pdgfra-lineaged cells as exemplified by their distinct contributions to myofibroblasts in normal maturation, BPD and adult fibrosis.

Genome-wide association studies (GWAS) have linked hundreds of thousands of sequence variants in the human genome to common traits and diseases. However, translating this knowledge into a mechanistic understanding of disease-relevant biology remains challenging, largely because such variants are predominantly in non-protein-coding sequences that still lack functional annotation at cell-type resolution. Recent advances in single-cell epigenomics assays have enabled the generation of cell type-, subtype- and state-resolved maps of the epigenome in heterogeneous human tissues. These maps have facilitated cell type-specific annotation of candidate cis-regulatory elements and their gene targets in the human genome, enhancing our ability to interpret the genetic basis of common traits and diseases.In this Review, Gaulton et al. discuss how single-cell epigenomic methods generate cell type-, subtype- and state-resolved maps of candidate cis-regulatory elements in heterogeneous human tissues that can help to interpret the genetic basis of common traits and diseases.

Integrating large single-cell gene expression, chromatin accessibility and DNA methylation datasets requires general and scalable computational approaches. Here we describe online integrative non-negative matrix factorization (iNMF), an algorithm for integrating large, diverse and continually arriving single-cell datasets. Our approach scales to arbitrarily large numbers of cells using fixed memory, iteratively incorporates new datasets as they are generated and allows many users to simultaneously analyze a single copy of a large dataset by streaming it over the internet. Iterative data addition can also be used to map new data to a reference dataset. Comparisons with previous methods indicate that the improvements in efficiency do not sacrifice dataset alignment and cluster preservation performance. We demonstrate the effectiveness of online iNMF by integrating more than 1 million cells on a standard laptop, integrating large single-cell RNA sequencing and spatial transcriptomic datasets, and iteratively constructing a single-cell multi-omic atlas of the mouse motor cortex. A new algorithm enables scalable and iterative integration of single-cell datasets.

Long-range chromatin interactions between enhancers and promoters are essential for transcription of many developmentally controlled genes in mammals and other metazoans. Currently, the exact mechanisms that connect distal enhancers to their specific target promoters remain to be fully elucidated. Here, we show that the enhancer-specific histone H3 lysine 4 monomethylation （H3K4mel） and the histone methyltransferases MLL3 and MLL4 （MLL3/4） play an active role in this process. We demonstrate that in differentiating mouse embryonic stem cells, MLL3/4-dependent deposition of H3K4mel at enhancers correlates with increased levels of chromatin interactions, whereas loss of this histone modification leads to reduced levels of chromatin interactions and defects in gene activation during differentiation. H3K4mel facilitates recruitment of the Cohesin complex, a known regulator of chromatin organization, to chromatin in vitro and in vivo, providing a potential mechanism for MLL3/4 to promote chromatin interactions between enhancers and promoters. Taken together, our results support a role for MLL3/4-dependent H3K4mel in orchestrating long-range ehromatin interactions at enhancers in mammalian cells.

Identification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators. Single cell analysis of transposase-accessible chromatin is deepening our understanding on the origins of cellular diversity, yet methods are limited by data sparsity. Here, the authors introduce SnapATAC, a pipeline to resolve cellular heterogeneity and reveal candidate regulatory elements across different cell populations.

Analysis of chromatin accessibility can reveal transcriptional regulatory sequences, but heterogeneity of primary tissues poses a significant challenge in mapping the precise chromatin landscape in specific cell types. Here we report single-nucleus ATAC-seq, a combinatorial barcoding-assisted single-cell assay for transposase-accessible chromatin that is optimized for use on flash-frozen primary tissue samples. We apply this technique to the mouse forebrain through eight developmental stages. Through analysis of more than 15,000 nuclei, we identify 20 distinct cell populations corresponding to major neuronal and non-neuronal cell types. We further define cell-type-specific transcriptional regulatory sequences, infer potential master transcriptional regulators and delineate developmental changes in forebrain cellular composition. Our results provide insight into the molecular and cellular dynamics that underlie forebrain development in the mouse and establish technical and analytical frameworks that are broadly applicable to other heterogeneous tissues.

Three papers in this issue of Nature use highly sensitive ChIP–seq assays to describe the dynamic patterns of histone modifications during early mouse embryogenesis, showing that oocytes have a distinctive epigenome and providing insights into how the maternal gene expression program transitions to the zygotic program. Chromatin states in embryogenesis Genomic analysis of chromatin states in early embryos has been technically difficult, owing to the limited number of cells available for analysis. Three papers in this issue of Nature use highly sensitive ChIP–seq assays to describe the dynamic patterns of histone modifications during early mouse embryogenesis. Arne Klungland and colleagues find that the oocyte genome is associated with broad non-canonical domains of histone H3K4me3 which seem to function in preventing deposition of DNA methylation. Wei Xie and colleagues find that the oocyte genome is associated with broad non-canonical domains of histone H3K4me3 which overlap with domains of low DNA methylation and seem to contribute to gene silencing. Shaorong Gao and colleagues map histone H3K4me3 and H3K27me3 modifications in pre-implantation embryos and focus on the re-establishment of histone modifications during zygotic genome activation. They find that the breadth of H3K4me3 domains is highly dynamic and that H3K4me3 re-establishes rapidly on promoter regions whereas H3K27me3 is mostly absent from these regions. Taken together—and with previously published work—these studies show that the oocyte has a distinctive epigenome and provide insights into how the maternal gene expression program transitions to the zygotic program. Maternal-to-zygotic transition (MZT) is essential for the formation of a new individual, but is still poorly understood despite recent progress in analysis of gene expression and DNA methylation in early embryogenesis 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 . Dynamic histone modifications may have important roles in MZT 10 , 11 , 12 , 13 , but direct measurements of chromatin states have been hindered by technical difficulties in profiling histone modifications from small quantities of cells. Recent improvements allow for 500 cell-equivalents of chromatin per reaction, but require 10,000 cells for initial steps 14 or require a highly specialized microfluidics device that is not readily available 15 . We developed a micro-scale chromatin immunoprecipitation and sequencing (μChIP–seq) method, which we used to profile genome-wide histone H3 lysine methylation (H3K4me3) and acetylation (H3K27ac) in mouse immature and metaphase II oocytes and in 2-cell and 8-cell embryos. Notably, we show that ~ 22% of the oocyte genome is associated with broad H3K4me3 domains that are anti-correlated with DNA methylation. The H3K4me3 signal becomes confined to transcriptional-start-site regions in 2-cell embryos, concomitant with the onset of major zygotic genome activation. Active removal of broad H3K4me3 domains by the lysine demethylases KDM5A and KDM5B is required for normal zygotic genome activation and is essential for early embryo development. Our results provide insight into the onset of the developmental program in mouse embryos and demonstrate a role for broad H3K4me3 domains in MZT.

Chromatin architecture has been implicated in cell type-specific gene regulatory programs, yet how chromatin remodels during development remains to be fully elucidated. Here, by interrogating chromatin reorganization during human pluripotent stem cell (hPSC) differentiation, we discover a role for the primate-specific endogenous retrotransposon human endogenous retrovirus subfamily H (HERV-H) in creating topologically associating domains (TADs) in hPSCs. Deleting these HERV-H elements eliminates their corresponding TAD boundaries and reduces the transcription of upstream genes, while de novo insertion of HERV-H elements can introduce new TAD boundaries. The ability of HERV-H to create TAD boundaries depends on high transcription, as transcriptional repression of HERV-H elements prevents the formation of boundaries. This ability is not limited to hPSCs, as these actively transcribed HERV-H elements and their corresponding TAD boundaries also appear in pluripotent stem cells from other hominids but not in more distantly related species lacking HERV-H elements. Overall, our results provide direct evidence for retrotransposons in actively shaping cell type- and species-specific chromatin architecture. Genetic deletion or transcriptional silencing of HERV-H elements in human pluripotent stem cells (hPSCs) eliminates nearby topologically associating domain boundaries, while de novo insertion of HERV-H elements can introduce new ones. Mutations of specific HERV-H elements can impact hPSC differentiation.

Single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) creates new opportunities to dissect cell type–specific mechanisms of complex diseases. Since pancreatic islets are central to type 2 diabetes (T2D), we profiled 15,298 islet cells by using combinatorial barcoding snATAC-seq and identified 12 clusters, including multiple alpha, beta and delta cell states. We cataloged 228,873 accessible chromatin sites and identified transcription factors underlying lineage- and state-specific regulation. We observed state-specific enrichment of fasting glucose and T2D genome-wide association studies for beta cells and enrichment for other endocrine cell types. At T2D signals localized to islet-accessible chromatin, we prioritized variants with predicted regulatory function and co-accessibility with target genes. A causal T2D variant rs231361 at the KCNQ1 locus had predicted effects on a beta cell enhancer co-accessible with INS and genome editing in embryonic stem cell–derived beta cells affected INS levels. Together our findings demonstrate the power of single-cell epigenomics for interpreting complex disease genetics. Single-cell ATAC-seq analysis of human pancreatic islet cells identifies different cell clusters and transcription factors that underlie lineage- and state-specific regulation and helps prioritize type 2 diabetes risk variants.