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.

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 (PSC) differentiation, we discover a role for the primate-specific endogenous retrotransposon HERV-H in creating topologically associating domains (TAD) in human PSCs. Deleting these HERV-H elements eliminates their corresponding TAD boundaries and reduces transcription of upstream genes, while de novo insertion of HERV-Hs can introduce new TAD boundaries. HERV-H’s ability to create these TAD boundaries depends on high transcription, as transcriptional repression of HERV-H elements prevents formation of these boundaries. This ability is not limited to human PSCs, as these actively transcribed HERV-Hs and their corresponding TAD boundaries also appear in PSCs from other hominids but not in more distantly related species lacking HERV-Hs. Overall, our results provide direct evidence for retrotransposons in actively shaping cell-type- and species-specific chromatin architecture.

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.

The mammalian cerebrum performs high-level sensory perception, motor control and cognitive functions through highly specialized cortical and subcortical structures1. Recent surveys of mouse and human brains with single-cell transcriptomics2–6 and high-throughput imaging technologies7,8 have uncovered hundreds of neural cell types distributed in different brain regions, but the transcriptional regulatory programs that are responsible for the unique identity and function of each cell type remain unknown. Here we probe the accessible chromatin in more than 800,000 individual nuclei from 45 regions that span the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to map the state of 491,818 candidate cis-regulatory DNA elements in 160 distinct cell types. We find high specificity of spatial distribution for not only excitatory neurons, but also most classes of inhibitory neurons and a subset of glial cell types. We characterize the gene regulatory sequences associated with the regional specificity within these cell types. We further link a considerable fraction of the cis-regulatory elements to putative target genes expressed in diverse cerebral cell types and predict transcriptional regulators that are involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of noncoding risk variants associated with various neurological diseases and traits in humans.

23The primary motor cortex (M1) is essential for voluntary fine motor control and is functionally conserved 24 across mammals. Using high-throughput transcriptomic and epigenomic profiling of over 450,000 single 25 nuclei in human, marmoset monkey, and mouse, we demonstrate a broadly conserved cellular makeup 26 of this region, whose similarity mirrors evolutionary distance and is consistent between the 27 transcriptome and epigenome. The core conserved molecular identity of neuronal and non-neuronal 28 types allowed the generation of a cross-species consensus cell type classification and inference of 29 conserved cell type properties across species. Despite overall conservation, many species 30 specializations were apparent, including differences in cell type proportions, gene expression, DNA 31 methylation, and chromatin state. Few cell type marker genes were conserved across species, 32 providing a short list of candidate genes and regulatory mechanisms responsible for conserved features 33 of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic 34 classification allowed the Patch-seq identification of layer 5 (L5) corticospinal Betz cells in non-human 35 primate and human and characterization of their highly specialized physiology and anatomy. These 36 findings highlight the robust molecular underpinnings of cell type diversity in M1 across mammals and 37 point to the genes and regulatory pathways responsible for the functional identity of cell types and their 38 species-specific adaptations. 39 40 distinguished on the basis of regions of open chromatin or DNA methylation 5,9,10 . Furthermore, several 48 recent studies have shown that transcriptomically-defined cell types can be aligned across species 2,11-49 13 , indicating that these methods provide a path to quantitatively study evolutionary conservation and 50 divergence at the level of cell types. However, application of these methods has been highly 51 fragmented to date. Human and mouse comparisons have been performed in different cortical regions, 52 using single-cell (with biases in cell proportions) versus single-nucleus (with biases in transcript 53 makeup) analysis, and most single-cell transcriptomic and epigenomic studies have been performed 54 independently. 55 56The primary motor cortex (MOp in mouse, M1 in human and non-human primates, all referred to as M1 57 herein) provides an ideal cortical region to address questions about cellular evolution in rodents and 58 primates by integrating these approaches. Unlike the primary visual cortex (V1), which is highly 59 specialized in primates, or frontal and temporal association areas, whose homologues in rodents 60 remain poorly defined, M1 is essential for fine motor control and is functionally conserved across 61 placental mammals. M1 is an agranular cortex, lacking a defined L4, although neurons with L4-like 62properties have been described 14 . L5 of carnivore and primate M1 contains exceptionally large 63 "giganto-cellular" corticospinal neurons (Betz c...

During mouse embryonic development, pluripotent cells rapidly divide and diversify, yet the regulatory programs that define the cell repertoire for each organ remain ill-defined. To delineate comprehensive chromatin landscapes during early organogenesis, we mapped chromatin accessibility in 19,453 single nuclei from mouse embryos at 8.25 days post-fertilisation. Identification of cell type-specific regions of open chromatin pinpointed two TAL1-bound endothelial enhancers, which we validated using transgenic mouse assays. Integrated gene expression and transcription factor motif enrichment analyses highlighted cell type-specific transcriptional regulators. Subsequent in vivo experiments in zebrafish revealed a role for the ETS factor FEV in endothelial identity downstream of ETV2 (Etsrp in zebrafish). Concerted in vivo validation experiments in mouse and zebrafish thus illustrate how single-cell open chromatin maps, representative of a mammalian embryo, provide access to the regulatory blueprint for mammalian organogenesis.

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Integrating large single-cell gene expression, chromatin accessibility and DNA methylation datasets requires general and scalable computational approaches. Here we describe online integrative nonnegative 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 a million cells on a standard laptop, integrating large single-cell RNA-seq and spatial transcriptomic datasets, and iteratively constructing a single-cell multi-omic atlas of the mouse motor cortex.