1
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Johansen NJ, Kempynck N, Zemke NR, Somasundaram S, Winter SD, Hooper M, Dwivedi D, Lohia R, Wehbe F, Li B, Abaffyová D, Armand EJ, Man JD, Eksi EC, Hecker N, Hulselmans G, Konstantakos V, Mauduit D, Mich JK, Partel G, Daigle TL, Levi BP, Zhang K, Tanaka Y, Gillis J, Ting JT, Ben-Simon Y, Miller J, Ecker JR, Ren B, Aerts S, Lein ES, Tasic B, Bakken TE. Evaluating Methods for the Prediction of Cell Type-Specific Enhancers in the Mammalian Cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.21.609075. [PMID: 39229027 PMCID: PMC11370467 DOI: 10.1101/2024.08.21.609075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Identifying cell type-specific enhancers in the brain is critical to building genetic tools for investigating the mammalian brain. Computational methods for functional enhancer prediction have been proposed and validated in the fruit fly and not yet the mammalian brain. We organized the 'Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics' to assess machine learning and feature-based methods designed to nominate enhancer DNA sequences to target cell types in the mouse cortex. Methods were evaluated based on in vivo validation data from hundreds of cortical cell type-specific enhancers that were previously packaged into individual AAV vectors and retro-orbitally injected into mice. We find that open chromatin was a key predictor of functional enhancers, and sequence models improved prediction of non-functional enhancers that can be deprioritized as opposed to pursued for in vivo testing. Sequence models also identified cell type-specific transcription factor codes that can guide designs of in silico enhancers. This community challenge establishes a benchmark for enhancer prioritization algorithms and reveals computational approaches and molecular information that are crucial for the identification of functional enhancers for mammalian cortical cell types. The results of this challenge bring us closer to understanding the complex gene regulatory landscape of the mammalian brain and help us design more efficient genetic tools and potential gene therapies for human neurological diseases.
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2
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Sun K, Liu X, Xu R, Liu C, Meng A, Lan X. Mapping the chromatin accessibility landscape of zebrafish embryogenesis at single-cell resolution by SPATAC-seq. Nat Cell Biol 2024; 26:1187-1199. [PMID: 38977847 DOI: 10.1038/s41556-024-01449-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/30/2024] [Indexed: 07/10/2024]
Abstract
Currently, the dynamic accessible elements that determine regulatory programs responsible for the unique identity and function of each cell type during zebrafish embryogenesis lack detailed study. Here we present SPATAC-seq: a split-pool ligation-based assay for transposase-accessible chromatin using sequencing. Using SPATAC-seq, we profiled chromatin accessibility in more than 800,000 individual nuclei across 20 developmental stages spanning the sphere stage to the early larval protruding mouth stage. Using this chromatin accessibility map, we identified 604 cell states and inferred their developmental relationships. We also identified 959,040 candidate cis-regulatory elements (cCREs) and delineated development-specific cCREs, as well as transcription factors defining diverse cell identities. Importantly, enhancer reporter assays confirmed that the majority of tested cCREs exhibited robust enhanced green fluorescent protein expression in restricted cell types or tissues. Finally, we explored gene regulatory programs that drive pigment and notochord cell differentiation. Our work provides a valuable open resource for exploring driver regulators of cell fate decisions in zebrafish embryogenesis.
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Affiliation(s)
- Keyong Sun
- School of Medicine, Tsinghua University, Beijing, China
- Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program, Tsinghua University, Beijing, China
| | - Xin Liu
- School of Life Sciences, Tsinghua University, Beijing, China
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China
| | - Runda Xu
- School of Medicine, Tsinghua University, Beijing, China
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China
| | - Chang Liu
- School of Medicine, Tsinghua University, Beijing, China
| | - Anming Meng
- School of Life Sciences, Tsinghua University, Beijing, China.
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China.
| | - Xun Lan
- School of Medicine, Tsinghua University, Beijing, China.
- Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program, Tsinghua University, Beijing, China.
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China.
- Ministry of Education Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China.
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3
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Chang L, Xie Y, Taylor B, Wang Z, Sun J, Tan TR, Bejar R, Chen CC, Furnari FB, Hu M, Ren B. Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590148. [PMID: 38712075 PMCID: PMC11071305 DOI: 10.1101/2024.04.18.590148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Comprehensive analysis of chromatin architecture is crucial for understanding the gene regulatory programs during development and in disease pathogenesis, yet current methods often inadequately address the unique challenges presented by analysis of heterogeneous tissue samples. Here, we introduce Droplet Hi-C, which employs a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture at single-cell resolution from the mouse cortex and analyzed gene regulatory programs in major cortical cell types. Additionally, we used this technique to detect copy number variation (CNV), structural variations (SVs) and extrachromosomal DNA (ecDNA) in cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We further refined this technique to allow for joint profiling of chromatin architecture and transcriptome in single cells, facilitating a more comprehensive exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C not only addresses critical gaps in chromatin analysis of heterogeneous tissues but also emerges as a versatile tool enhancing our understanding of gene regulation in health and disease.
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Affiliation(s)
- Lei Chang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
| | - Brett Taylor
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jiachen Sun
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
- Department of Systems Biology and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Tuyet R. Tan
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Rafael Bejar
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Clark C. Chen
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Frank B. Furnari
- Department of Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Epigenomics, Institute for Genomic Medicine, Moores Cancer Center, University of California, San Diego, School of Medicine, La Jolla, CA, USA
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4
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Bárcenas-Walls JR, Ansaloni F, Hervé B, Strandback E, Nyman T, Castelo-Branco G, Bartošovič M. Nano-CUT&Tag for multimodal chromatin profiling at single-cell resolution. Nat Protoc 2024; 19:791-830. [PMID: 38129675 DOI: 10.1038/s41596-023-00932-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 10/19/2023] [Indexed: 12/23/2023]
Abstract
The ability to comprehensively analyze the chromatin state with single-cell resolution is crucial for understanding gene regulatory principles in heterogenous tissues or during development. Recently, we developed a nanobody-based single-cell CUT&Tag (nano-CT) protocol to simultaneously profile three epigenetic modalities-two histone marks and open chromatin state-from the same single cell. Nano-CT implements a new set of secondary nanobody-Tn5 fusion proteins to direct barcoded tagmentation by Tn5 transposase to genomic targets labeled by primary antibodies raised in different species. Such nanobody-Tn5 fusion proteins are currently not commercially available, and their in-house production and purification can be completed in 3-4 d by following our detailed protocol. The single-cell indexing in nano-CT is performed on a commercially available platform, making it widely accessible to the community. In comparison to other multimodal methods, nano-CT stands out in data complexity, low sample requirements and the flexibility to choose two of the three modalities. In addition, nano-CT works efficiently with fresh brain samples, generating multimodal epigenomic profiles for thousands of brain cells at single-cell resolution. The nano-CT protocol can be completed in just 3 d by users with basic skills in standard molecular biology and bioinformatics, although previous experience with single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is beneficial for more in-depth data analysis. As a multimodal assay, nano-CT holds immense potential to reveal interactions of various chromatin modalities, to explore epigenetic heterogeneity and to increase our understanding of the role and interplay that chromatin dynamics has in cellular development.
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Affiliation(s)
| | - Federico Ansaloni
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Bastien Hervé
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Emilia Strandback
- Protein Science Facility, Department of Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Tomas Nyman
- Protein Science Facility, Department of Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Gonçalo Castelo-Branco
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- Ming Wai Lau Centre for Reparative Medicine, Stockholm node, Karolinska Institutet, Stockholm, Sweden
| | - Marek Bartošovič
- Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
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5
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Bai D, Zhang X, Xiang H, Guo Z, Zhu C, Yi C. Simultaneous single-cell analysis of 5mC and 5hmC with SIMPLE-seq. Nat Biotechnol 2024:10.1038/s41587-024-02148-9. [PMID: 38336903 DOI: 10.1038/s41587-024-02148-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 01/18/2024] [Indexed: 02/12/2024]
Abstract
Dynamic 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications to DNA regulate gene expression in a cell-type-specific manner and are associated with various biological processes, but the two modalities have not yet been measured simultaneously from the same genome at the single-cell level. Here we present SIMPLE-seq, a scalable, base resolution method for joint analysis of 5mC and 5hmC from thousands of single cells. Based on orthogonal labeling and recording of 'C-to-T' mutational signals from 5mC and 5hmC sites, SIMPLE-seq detects these two modifications from the same molecules in single cells and enables unbiased DNA methylation dynamics analysis of heterogeneous biological samples. We applied this method to mouse embryonic stem cells, human peripheral blood mononuclear cells and mouse brain to give joint epigenome maps at single-cell and single-molecule resolution. Integrated analysis of these two cytosine modifications reveals distinct epigenetic patterns associated with divergent regulatory programs in different cell types as well as cell states.
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Affiliation(s)
- Dongsheng Bai
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China
| | - Xiaoting Zhang
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China
| | - Huifen Xiang
- Department of Obstetrics and Gynecology, First Affiliated Hospital of Anhui Medical University, Anhui, China
- NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Anhui, China
| | - Zijian Guo
- State Key Laboratory of Coordination Chemistry, Coordination Chemistry Institute, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, China
| | - Chenxu Zhu
- New York Genome Center, New York, NY, USA.
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
| | - Chengqi Yi
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
- Department of Chemical Biology and Synthetic and Functional Biomolecules Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
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6
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Wang Z, Ren B. Role of H3K4 monomethylation in gene regulation. Curr Opin Genet Dev 2024; 84:102153. [PMID: 38278054 PMCID: PMC11065453 DOI: 10.1016/j.gde.2024.102153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 01/02/2024] [Accepted: 01/02/2024] [Indexed: 01/28/2024]
Abstract
Methylation of histone H3 on the lysine-4 residue (H3K4me) is found throughout the eukaryotic domain, and its initial discovery as a conserved epigenetic mark of active transcription from yeast to mammalian cells has contributed to the histone code hypothesis. However, recent studies have raised questions on whether the different forms of H3K4me play a direct role in gene regulation or are simply by-products of the transcription process. Here, we review the often-conflicting experimental evidence, focusing on the monomethylation of lysine 4 on histone H3 that has been linked to the transcriptional state of enhancers in metazoans. We suggest that this epigenetic mark acts in a context-dependent manner to directly facilitate the transcriptional output of the genome and the establishment of cellular identity.
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Affiliation(s)
- Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA. https://twitter.com/@ZhaoningWang
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA; Institute of Genomic Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA.
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7
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Zhang K, Zemke NR, Armand EJ, Ren B. A fast, scalable and versatile tool for analysis of single-cell omics data. Nat Methods 2024; 21:217-227. [PMID: 38191932 PMCID: PMC10864184 DOI: 10.1038/s41592-023-02139-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 11/23/2023] [Indexed: 01/10/2024]
Abstract
Single-cell omics technologies have revolutionized the study of gene regulation in complex tissues. A major computational challenge in analyzing these datasets is to project the large-scale and high-dimensional data into low-dimensional space while retaining the relative relationships between cells. This low dimension embedding is necessary to decompose cellular heterogeneity and reconstruct cell-type-specific gene regulatory programs. Traditional dimensionality reduction techniques, however, face challenges in computational efficiency and in comprehensively addressing cellular diversity across varied molecular modalities. Here we introduce a nonlinear dimensionality reduction algorithm, embodied in the Python package SnapATAC2, which not only achieves a more precise capture of single-cell omics data heterogeneities but also ensures efficient runtime and memory usage, scaling linearly with the number of cells. Our algorithm demonstrates exceptional performance, scalability and versatility across diverse single-cell omics datasets, including single-cell assay for transposase-accessible chromatin using sequencing, single-cell RNA sequencing, single-cell Hi-C and single-cell multi-omics datasets, underscoring its utility in advancing single-cell analysis.
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Affiliation(s)
- Kai Zhang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Westlake Laboratory of Life Sciences and Biomedicine, School of Life Sciences, Westlake University, Hangzhou, China
| | - Nathan R Zemke
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA.
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8
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Coda DM, Gräff J. From cellular to fear memory: An epigenetic toolbox to remember. Curr Opin Neurobiol 2024; 84:102829. [PMID: 38128422 DOI: 10.1016/j.conb.2023.102829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 11/28/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023]
Abstract
Throughout development, the neuronal epigenome is highly sensitive to external stimuli, yet capable of safeguarding cellular memory for a lifetime. In the adult brain, memories of fearful experiences are rapidly instantiated, yet can last for decades, but the mechanisms underlying such longevity remain unknown. Here, we showcase how fear memory formation and storage - traditionally thought to exclusively affect synapse-based events - elicit profound and enduring changes to the chromatin, proposing epigenetic regulation as a plausible molecular template for mnemonic processes. By comparing these to mechanisms occurring in development and differentiation, we notice that an epigenetic machinery similar to that preserving cellular memories might be employed by brain cells so as to form, store, and retrieve behavioral memories.
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Affiliation(s)
- Davide Martino Coda
- Laboratory of Neuroepigenetics, Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Federale Lausanne (EPFL), 1015, Lausanne, Switzerland.
| | - Johannes Gräff
- Laboratory of Neuroepigenetics, Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Federale Lausanne (EPFL), 1015, Lausanne, Switzerland.
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9
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Zemke NR, Armand EJ, Wang W, Lee S, Zhou J, Li YE, Liu H, Tian W, Nery JR, Castanon RG, Bartlett A, Osteen JK, Li D, Zhuo X, Xu V, Chang L, Dong K, Indralingam HS, Rink JA, Xie Y, Miller M, Krienen FM, Zhang Q, Taskin N, Ting J, Feng G, McCarroll SA, Callaway EM, Wang T, Lein ES, Behrens MM, Ecker JR, Ren B. Conserved and divergent gene regulatory programs of the mammalian neocortex. Nature 2023; 624:390-402. [PMID: 38092918 PMCID: PMC10719095 DOI: 10.1038/s41586-023-06819-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Divergence of cis-regulatory elements drives species-specific traits1, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains unclear. Here we investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset and mouse using single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome and chromosomal conformation profiles from a total of over 200,000 cells. From these data, we show evidence that divergence of transcription factor expression corresponds to species-specific epigenome landscapes. We find that conserved and divergent gene regulatory features are reflected in the evolution of the three-dimensional genome. Transposable elements contribute to nearly 80% of the human-specific candidate cis-regulatory elements in cortical cells. Through machine learning, we develop sequence-based predictors of candidate cis-regulatory elements in different species and demonstrate that the genomic regulatory syntax is highly preserved from rodents to primates. Finally, we show that epigenetic conservation combined with sequence similarity helps to uncover functional cis-regulatory elements and enhances our ability to interpret genetic variants contributing to neurological disease and traits.
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Affiliation(s)
- Nathan R Zemke
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
| | - Wenliang Wang
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Jingtian Zhou
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yang Eric Li
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Wei Tian
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rosa G Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia K Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Daofeng Li
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Xiaoyu Zhuo
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Vincent Xu
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Lei Chang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Keyi Dong
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Hannah S Indralingam
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Jonathan A Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Michael Miller
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Fenna M Krienen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Genetics, Harvard Medical School, Boston, USA
| | - Qiangge Zhang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Naz Taskin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Guoping Feng
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven A McCarroll
- Department of Genetics, Harvard Medical School, Boston, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Edward M Callaway
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Ting Wang
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - M Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Institute of Genomic Medicine, Moores Cancer Center, School of Medicine, University of California San Diego, La Jolla, CA, USA.
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