Induced pluripotent stem (iPS) cells are derived by epigenetic reprogramming, but their DNA methylation patterns have not yet been analyzed on a genome-wide scale. Here, we find substantial hypermethylation and hypomethylation of cytosine-phosphate-guanine (CpG) island shores in nine human iPS cell lines as compared to their parental fibroblasts. The differentially methylated regions (DMRs) in the reprogrammed cells (denoted R-DMRs) were significantly enriched in tissue-specific (T-DMRs; 2.6-fold, P < 10 −4 ) and cancer-specific DMRs (C-DMRs; 3.6-fold, P < 10 −4 ). Notably, even though the iPS cells are derived from fibroblasts, their R-DMRs can distinguish between normal brain, liver and spleen cells and between colon cancer and normal colon cells. Thus, many DMRs are broadly involved in tissue differentiation, epigenetic reprogramming and cancer. We observed colocalization of hypomethylated R-DMRs with hypermethylated C-DMRs and bivalent chromatin marks, and colocalization of hypermethylated R-DMRs with hypomethylated C-DMRs and the absence of bivalent marks, suggesting two mechanisms for epigenetic reprogramming in iPS cells and cancer.Correspondence should be addressed to G.Q.D. (George.Daley@childrens.harvard.edu) and A.P.F. (afeinberg@jhu.edu). 5 These authors contributed equally to this work. 6 These authors jointly supervised this work.Accession codes. NCBI GEO: Gene expression microarray data and CHARM microarray data have been submitted under accession number GSE18111.Note: Supplementary information is available on the Nature Genetics website. Here we used a similar approach to the question of iPS cell reprogramming, first comparing six human iPS cell lines to the fibroblasts from which they were derived using comprehensive high-throughput array-based relative methylation (CHARM) analysis 9 . This approach allows the interrogation of ~4.6 million CpG sites genome-wide using a custom designed NimbleGen HD2 microarray, including almost all CpG islands and shores in the human genome. Genomic DNA from iPS cells 3,5 , their parental fibroblasts and human embryonic stem (hES) cells (Online Methods) was digested with the enzyme McrBC, fractionated, labeled and hybridized to a CHARM array. AUTHOR CONTRIBUTIONSA total of 4,401 regions (including 96,404 CpG sites) were found to differ in iPS cell lines from the fibroblasts of origin (Table 1, Supplementary Table 1) at a false discovery rate (FDR) of 5%; we term these regions R-DMRs. Of these R-DMRs, DMRs that were hypermethylated in iPS cells compared to fibroblasts predominated over hypomethylated DMRs (60%:40%). Of the 4,401 DMRs, 1,969 were within 2 kb of the transcriptional start site of a gene.The genes that were associated with these R-DMRs showed functionally important features based on bioinformatic analyses. First, gene ontology (GO) annotation analysis of these genes revealed significant enrichment for genes involved in developmental and regulatory processes (Supplementary Table 2). For example, 38% of the genes that were hypomethylated in iPS ...

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

In honeybee societies, distinct caste phenotypes are created from the same genotype, suggesting a role for epigenetics in deriving these behaviorally different phenotypes. We found no differences in DNA methylation between irreversible worker/queen castes, but substantial differences between nurses and forager subcastes. Reverting foragers back to nurses reestablished methylation levels for a majority of genes and provided the first evidence in any organism of reversible epigenetic changes associated with behavior.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1–3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas—containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities—is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp.Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis. IntroductionNeural circuits are characterized by extraordinary diversity of their cellular components 1,2 . Single-cell molecular assays, especially transcriptomic measurements by RNA-Seq, have accelerated the discovery and characterization of cell types across brain regions and in diverse species. Recent advances include single-cell transcriptome datasets with >10 5 individual cells, identifying hundreds of neuronal and non-neuronal cell types across the mouse nervous system 3-5 . As the number of profiled cells grows into the millions, a key question is whether these data will converge toward a comprehensive and coherent taxonomy of cell types with broad utility for organizing knowledge of brain cells and their function. Data from different modalities, including transcriptomic and epigenomic data, must be cross-referenced and integrated to establish robust and consistent cell type classifications.Although a comprehensive atlas should incorporate anatomical and physiological information, the high throughput of single cell sequencing assays makes integration of molecular data a particularly urgent challenge. A rigorous and reproducible consensus molecular atlas of brain cell types would drive progress across modalities, including obtaining functional information.Single cell sequencing technologies can measure multiple molecular signatures of cell identity. The core molecular identity of a cell is largely established during development and maintained by a combination of gene regulatory proteins...

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...

The gEAR portal (gene Expression Analysis Resource, umgear.org) is an open access community-driven tool for multi-omic and multi-species data visualization, analysis and sharing. The gEAR supports visualization of multiple RNA-seq data types (bulk, sorted, single cell/nucleus) and epigenomics data, from multiple species, time points and tissues in a single-page, user-friendly browsable format. An integrated scRNA-seq workbench provides access to raw data of scRNA-seq datasets for de novo analysis, as well as marker-gene and cluster comparisons of pre-assigned clusters. Users can upload, view, analyze and privately share their own data in the context of previously published datasets. Short, permanent URLs can be generated for dissemination of individual or collections of datasets in published manuscripts. While the gEAR is currently curated for auditory research with over 90 high-value datasets organized in thematic profiles, the gEAR also supports the BRAIN initiative (via nemoanalytics.org) and is easily adaptable for other research domains.