Single cell epigenomic atlas of the developing human brain and organoids

Dynamic changes in chromatin accessibility coincide with important aspects of neuronal differentiation, such as fate specification and arealization and confer cell type-specific associations to neurodevelopmental disorders. However, studies of the epigenomic landscape of the developing human brain have yet to be performed at single-cell resolution. Here, we profiled chromatin accessibility of >75,000 cells from eight distinct areas of developing human forebrain using single cell ATAC-seq (scATACseq). We identified thousands of loci that undergo extensive cell type-specific changes in accessibility during corticogenesis. Chromatin state profiling also reveals novel distinctions between neural progenitor cells from different cortical areas not seen in transcriptomic profiles and suggests a role for retinoic acid signaling in cortical arealization. Comparison of the cell type-specific chromatin landscape of cerebral organoids to primary developing cortex found that organoids establish broad cell type-specific enhancer accessibility patterns similar to the developing cortex, but lack many putative regulatory elements identified in homologous primary cell types. Together, our results reveal the important contribution of chromatin state to the emerging patterns of cell type diversity and cell fate specification and provide a blueprint for evaluating the fidelity and robustness of cerebral organoids as a model for cortical development.

[1]  Matthew W. Mosconi,et al.  Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism , 2019, Cell.

[2]  Trygve E Bakken,et al.  Sex-Based Analysis of De Novo Variants in Neurodevelopmental Disorders. , 2019, American journal of human genetics.

[3]  A. West,et al.  Neurobiological functions of transcriptional enhancers , 2019, Nature Neuroscience.

[4]  Nir Yosef,et al.  Identification and Massively Parallel Characterization of Regulatory Elements Driving Neural Induction. , 2019, Cell stem cell.

[5]  B. Ren,et al.  An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome , 2019, Nature Structural & Molecular Biology.

[6]  S. Pääbo,et al.  Organoid single-cell genomic atlas uncovers human-specific features of brain development , 2019, Nature.

[7]  Allan R. Jones,et al.  Conserved cell types with divergent features in human versus mouse cortex , 2019, Nature.

[8]  David Kulp,et al.  Innovations in Primate Interneuron Repertoire , 2019, bioRxiv.

[9]  Neva C. Durand,et al.  Activity-by-Contact model of enhancer-promoter regulation from thousands of CRISPR perturbations , 2019, Nature Genetics.

[10]  Jakob Grove,et al.  Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder , 2017, bioRxiv.

[11]  B. Ren,et al.  Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types , 2019 .

[12]  Andrew C. Adey,et al.  The accessible chromatin landscape of the murine hippocampus at single-cell resolution , 2019, Genome research.

[13]  Allon M Klein,et al.  Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data. , 2019, Cell systems.

[14]  R. Satija,et al.  Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression , 2019, Genome Biology.

[15]  Christopher P. Tzeng,et al.  A scalable platform for the development of cell-type-specific viral drivers , 2019, bioRxiv.

[16]  Alicia R. Martin,et al.  Identification of common genetic risk variants for autism spectrum disorder , 2019, Nature Genetics.

[17]  Andrew J. Hill,et al.  The single cell transcriptional landscape of mammalian organogenesis , 2019, Nature.

[18]  Trygve E Bakken,et al.  Epigenetic landscape and AAV targeting of human neocortical cell classes , 2019 .

[19]  Garreck H. Lenz,et al.  Prospective, brain-wide labeling of neuronal subclasses with enhancer-driven AAVs , 2019, bioRxiv.

[20]  Gerald Quon,et al.  scAlign: a tool for alignment, integration, and rare cell identification from scRNA-seq data , 2018, Genome Biology.

[21]  Ian T. Fiddes,et al.  Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution , 2018, Cell.

[22]  R. Marioni,et al.  Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions , 2018, Nature Neuroscience.

[23]  Patrick J. Short,et al.  Integrating healthcare and research genetic data empowers the discovery of 49 novel developmental disorders , 2019, bioRxiv.

[24]  Gerome Breen,et al.  Genetic identification of brain cell types underlying schizophrenia , 2017, Nature Genetics.

[25]  Stephan J Sanders,et al.  Integrative functional genomic analysis of human brain development and neuropsychiatric risks , 2018, Science.

[26]  M. Gerstein,et al.  Transcriptome and epigenome landscape of human cortical development modeled in organoids , 2018, Science.

[27]  Matthew W. Mosconi,et al.  Novel genes for autism implicate both excitatory and inhibitory cell lineages in risk , 2018, bioRxiv.

[28]  Trygve E Bakken,et al.  Neurodevelopmental disease genes implicated by de novo mutation and copy number variation morbidity , 2018, Nature Genetics.

[29]  Allan R. Jones,et al.  Shared and distinct transcriptomic cell types across neocortical areas , 2018, Nature.

[30]  Andrew C. Adey,et al.  Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data. , 2018, Molecular cell.

[31]  Kevin R. Moon,et al.  Recovering Gene Interactions from Single-Cell Data Using Data Diffusion , 2018, Cell.

[32]  A. Regev,et al.  Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis , 2018, Science.

[33]  Ryan L. Collins,et al.  An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder , 2018, Nature Genetics.

[34]  Paul Hoffman,et al.  Integrating single-cell transcriptomic data across different conditions, technologies, and species , 2018, Nature Biotechnology.

[35]  Jakob Grove,et al.  Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection , 2018, Nature Genetics.

[36]  D. Dickel,et al.  Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation , 2018, Nature Neuroscience.

[37]  D. Geschwind,et al.  The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis , 2018, Cell.

[38]  P. Kharchenko,et al.  Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain , 2017, Nature Biotechnology.

[39]  Alex A. Pollen,et al.  Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex , 2017, Science.

[40]  M. Gerstein,et al.  Molecular and cellular reorganization of neural circuits in the human lineage , 2017, Science.

[41]  A. Tanay,et al.  Multiscale 3D Genome Rewiring during Mouse Neural Development , 2017, Cell.

[42]  Nicholas A. Sinnott-Armstrong,et al.  An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues , 2017, Nature Methods.

[43]  William J. Greenleaf,et al.  chromVAR: Inferring transcription factor-associated accessibility from single-cell epigenomic data , 2017, Nature Methods.

[44]  Bradley P. Coe,et al.  Targeted sequencing identifies 91 neurodevelopmental disorder risk genes with autism and developmental disability biases , 2017, Nature Genetics.

[45]  Evan Z. Macosko,et al.  Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types , 2017, Nature Genetics.

[46]  Joseph R Ecker,et al.  Cerebral Organoids Recapitulate Epigenomic Signatures of the Human Fetal Brain. , 2016, Cell reports.

[47]  Soher Balkhy,et al.  Mutations in Human Accelerated Regions Disrupt Cognition and Social Behavior , 2016, Cell.

[48]  Tomasz J. Nowakowski,et al.  Transformation of the Radial Glia Scaffold Demarcates Two Stages of Human Cerebral Cortex Development , 2016, Neuron.

[49]  Fidel Ramírez,et al.  deepTools2: a next generation web server for deep-sequencing data analysis , 2016, Nucleic Acids Res..

[50]  Adele M Doyle,et al.  Fixed single-cell transcriptomic characterization of human radial glial diversity , 2015, Nature Methods.

[51]  Bernat Gel,et al.  regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests , 2015, Bioinform..

[52]  Madeline A. Lancaster,et al.  Human cerebral organoids recapitulate gene expression programs of fetal neocortex development , 2015, Proceedings of the National Academy of Sciences.

[53]  Alex A. Pollen,et al.  Molecular Identity of Human Outer Radial Glia during Cortical Development , 2015, Cell.

[54]  Yakir A Reshef,et al.  Partitioning heritability by functional annotation using genome-wide association summary statistics , 2015, Nature Genetics.

[55]  Qing-Yu He,et al.  ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization , 2015, Bioinform..

[56]  Howard Y. Chang,et al.  Single-cell chromatin accessibility reveals principles of regulatory variation , 2015, Nature.

[57]  Terrence J. Sejnowski,et al.  Epigenomic Signatures of Neuronal Diversity in the Mammalian Brain , 2015, Neuron.

[58]  Andrew C. Adey,et al.  Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing , 2015, Science.

[59]  Jing Leng,et al.  Evolutionary changes in promoter and enhancer activity during human corticogenesis , 2015, Science.

[60]  Kali T. Witherspoon,et al.  Refining analyses of copy number variation identifies specific genes associated with developmental delay , 2014, Nature Genetics.

[61]  L. Gudas,et al.  Retinoic Acid Suppresses the Canonical Wnt Signaling Pathway in Embryonic Stem Cells and Activates the Noncanonical Wnt Signaling Pathway , 2014, Stem cells.

[62]  C. Spencer,et al.  Biological Insights From 108 Schizophrenia-Associated Genetic Loci , 2014, Nature.

[63]  Hongkui Zeng,et al.  Transcriptional Regulation of Enhancers Active in Protodomains of the Developing Cerebral Cortex , 2014, Neuron.

[64]  Allan R. Jones,et al.  Transcriptional Landscape of the Prenatal Human Brain , 2014, Nature.

[65]  A. Visel,et al.  Rapid and Pervasive Changes in Genome-wide Enhancer Usage during Mammalian Development , 2013, Cell.

[66]  Katherine S. Pollard,et al.  Many human accelerated regions are developmental enhancers , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.

[67]  M. Eiraku,et al.  Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell–derived neocortex , 2013, Proceedings of the National Academy of Sciences.

[68]  Jan H Lui,et al.  Non-epithelial stem cells and cortical interneuron production in the human ganglionic eminences , 2013, Nature Neuroscience.

[69]  J. Rubenstein,et al.  Subcortical origins of human and monkey neocortical interneurons , 2013, Nature Neuroscience.

[70]  Howard Y. Chang,et al.  Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position , 2013, Nature Methods.

[71]  J. Rubenstein,et al.  CoupTFI Interacts with Retinoic Acid Signaling during Cortical Development , 2013, PloS one.

[72]  Hani Z. Girgis,et al.  A High-Resolution Enhancer Atlas of the Developing Telencephalon , 2013, Cell.

[73]  C. Glass,et al.  Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. , 2010, Molecular cell.

[74]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[75]  Clifford A. Meyer,et al.  Model-based Analysis of ChIP-Seq (MACS) , 2008, Genome Biology.

[76]  A. Mortazavi,et al.  Genome-Wide Mapping of in Vivo Protein-DNA Interactions , 2007, Science.

[77]  Inna Dubchak,et al.  VISTA Enhancer Browser—a database of tissue-specific human enhancers , 2006, Nucleic Acids Res..

[78]  David Haussler,et al.  Forces Shaping the Fastest Evolving Regions in the Human Genome , 2006, PLoS genetics.

[79]  D. Wotton,et al.  TGIF Inhibits Retinoid Signaling , 2006, Molecular and Cellular Biology.

[80]  Morriss Gm Morphogenesis of the malformations induced in rat embryos by maternal hypervitaminosis A. , 1972 .

[81]  G. Morriss Morphogenesis of the malformations induced in rat embryos by maternal hypervitaminosis A. , 1972, Journal of anatomy.

[82]  S. Counce The Strategy of the Genes , 1958, The Yale Journal of Biology and Medicine.