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1. Temporally distinct 3D multi-omic dynamics in the developing human brain

Author

Heffel, Matthew G, Zhou, Jingtian, Zhang, Yi, Lee, Dong-Sung, Hou, Kangcheng, Pastor-Alonso, Oier, Abuhanna, Kevin D, Galasso, Joseph, Kern, Colin, Tai, Chu-Yi, Garcia-Padilla, Carlos, Nafisi, Mahsa, Zhou, Yi, Schmitt, Anthony D, Li, Terence, Haeussler, Maximilian, Wick, Brittney, Zhang, Martin Jinye, Xie, Fangming, Ziffra, Ryan S, Mukamel, Eran A, Eskin, Eleazar, Nowakowski, Tomasz J, Dixon, Jesse R, Pasaniuc, Bogdan, Ecker, Joseph R, Zhu, Quan, Bintu, Bogdan, Paredes, Mercedes F, and Luo, Chongyuan

Subjects
Biological Sciences, Genetics, Brain Disorders, Neurosciences, Mental Illness, Mental Health, Human Genome, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Neurological, Humans, Cell Differentiation, Chromatin, Disease Susceptibility, DNA Methylation, Epigenesis, Genetic, Epigenomics, Fetus, Hippocampus, Multiomics, Neuroglia, Neurons, Prefrontal Cortex, Schizophrenia, Single Molecule Imaging, Single-Cell Analysis, Time Factors, Infant, Newborn, General Science & Technology
Abstract

The human hippocampus and prefrontal cortex play critical roles in learning and cognition1,2, yet the dynamic molecular characteristics of their development remain enigmatic. Here we investigated the epigenomic and three-dimensional chromatin conformational reorganization during the development of the hippocampus and prefrontal cortex, using more than 53,000 joint single-nucleus profiles of chromatin conformation and DNA methylation generated by single-nucleus methyl-3C sequencing (snm3C-seq3)3. The remodelling of DNA methylation is temporally separated from chromatin conformation dynamics. Using single-cell profiling and multimodal single-molecule imaging approaches, we have found that short-range chromatin interactions are enriched in neurons, whereas long-range interactions are enriched in glial cells and non-brain tissues. We reconstructed the regulatory programs of cell-type development and differentiation, finding putatively causal common variants for schizophrenia strongly overlapping with chromatin loop-connected, cell-type-specific regulatory regions. Our data provide multimodal resources for studying gene regulatory dynamics in brain development and demonstrate that single-cell three-dimensional multi-omics is a powerful approach for dissecting neuropsychiatric risk loci.

Published
2024

2. Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes

Author

Xie, Fangming, Armand, Ethan J, Yao, Zizhen, Liu, Hanqing, Bartlett, Anna, Behrens, M Margarita, Li, Yang Eric, Lucero, Jacinta D, Luo, Chongyuan, Nery, Joseph R, Pinto-Duarte, Antonio, Poirion, Olivier B, Preissl, Sebastian, Rivkin, Angeline C, Tasic, Bosiljka, Zeng, Hongkui, Ren, Bing, Ecker, Joseph R, and Mukamel, Eran A

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Epidemiology, Health Sciences, Biotechnology, Human Genome, Generic health relevance, DNA methylation, brain, chromatin accessibility, enhancer, epigenome
Abstract

Single-cell sequencing could help to solve the fundamental challenge of linking millions of cell-type-specific enhancers with their target genes. However, this task is confounded by patterns of gene co-expression in much the same way that genetic correlation due to linkage disequilibrium confounds fine-mapping in genome-wide association studies (GWAS). We developed a non-parametric permutation-based procedure to establish stringent statistical criteria to control the risk of false-positive associations in enhancer-gene association studies (EGAS). We applied our procedure to large-scale transcriptome and epigenome data from multiple tissues and species, including the mouse and human brain, to predict enhancer-gene associations genome wide. We tested the functional validity of our predictions by comparing them with chromatin conformation data and causal enhancer perturbation experiments. Our study shows how controlling for gene co-expression enables robust enhancer-gene linkage using single-cell sequencing data.

Published
2023

3. A guide to the BRAIN Initiative Cell Census Network data ecosystem

Author

Hawrylycz, Michael, Martone, Maryann E, Ascoli, Giorgio A, Bjaalie, Jan G, Dong, Hong-Wei, Ghosh, Satrajit S, Gillis, Jesse, Hertzano, Ronna, Haynor, David R, Hof, Patrick R, Kim, Yongsoo, Lein, Ed, Liu, Yufeng, Miller, Jeremy A, Mitra, Partha P, Mukamel, Eran, Ng, Lydia, Osumi-Sutherland, David, Peng, Hanchuan, Ray, Patrick L, Sanchez, Raymond, Regev, Aviv, Ropelewski, Alex, Scheuermann, Richard H, Tan, Shawn Zheng Kai, Thompson, Carol L, Tickle, Timothy, Tilgner, Hagen, Varghese, Merina, Wester, Brock, White, Owen, Zeng, Hongkui, Aevermann, Brian, Allemang, David, Ament, Seth, Athey, Thomas L, Baker, Cody, Baker, Katherine S, Baker, Pamela M, Bandrowski, Anita, Banerjee, Samik, Bishwakarma, Prajal, Carr, Ambrose, Chen, Min, Choudhury, Roni, Cool, Jonah, Creasy, Heather, D’Orazi, Florence, Degatano, Kylee, Dichter, Benjamin, Ding, Song-Lin, Dolbeare, Tim, Ecker, Joseph R, Fang, Rongxin, Fillion-Robin, Jean-Christophe, Fliss, Timothy P, Gee, James, Gillespie, Tom, Gouwens, Nathan, Zhang, Guo-Qiang, Halchenko, Yaroslav O, Harris, Nomi L, Herb, Brian R, Hintiryan, Houri, Hood, Gregory, Horvath, Sam, Huo, Bingxing, Jarecka, Dorota, Jiang, Shengdian, Khajouei, Farzaneh, Kiernan, Elizabeth A, Kir, Huseyin, Kruse, Lauren, Lee, Changkyu, Lelieveldt, Boudewijn, Li, Yang, Liu, Hanqing, Liu, Lijuan, Markuhar, Anup, Mathews, James, Mathews, Kaylee L, Mezias, Chris, Miller, Michael I, Mollenkopf, Tyler, Mufti, Shoaib, Mungall, Christopher J, Orvis, Joshua, Puchades, Maja A, Qu, Lei, Receveur, Joseph P, Ren, Bing, Sjoquist, Nathan, Staats, Brian, Tward, Daniel, van Velthoven, Cindy TJ, Wang, Quanxin, Xie, Fangming, Xu, Hua, Yao, Zizhen, and Yun, Zhixi

Subjects
Biological Sciences, Genetics, Neurosciences, Data Science, Mental Health, 1.1 Normal biological development and functioning, Neurological, Animals, Humans, Mice, Brain, Ecosystem, Neurons, Agricultural and Veterinary Sciences, Medical and Health Sciences, Developmental Biology, Agricultural, veterinary and food sciences, Biological sciences, Biomedical and clinical sciences
Abstract

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

Published
2023

5. Single nucleus multi-omics identifies human cortical cell regulatory genome diversity

Author

Luo, Chongyuan, Liu, Hanqing, Xie, Fangming, Armand, Ethan J, Siletti, Kimberly, Bakken, Trygve E, Fang, Rongxin, Doyle, Wayne I, Stuart, Tim, Hodge, Rebecca D, Hu, Lijuan, Wang, Bang-An, Zhang, Zhuzhu, Preissl, Sebastian, Lee, Dong-Sung, Zhou, Jingtian, Niu, Sheng-Yong, Castanon, Rosa, Bartlett, Anna, Rivkin, Angeline, Wang, Xinxin, Lucero, Jacinta, Nery, Joseph R, Davis, David A, Mash, Deborah C, Satija, Rahul, Dixon, Jesse R, Linnarsson, Sten, Lein, Ed, Behrens, M Margarita, Ren, Bing, Mukamel, Eran A, and Ecker, Joseph R

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Cancer, Precision Medicine, Human Genome, Cancer Genomics, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Good Health and Well Being
Abstract

Single-cell technologies measure unique cellular signatures but are typically limited to a single modality. Computational approaches allow the fusion of diverse single-cell data types, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells, we devised single-nucleus methylcytosine, chromatin accessibility, and transcriptome sequencing (snmCAT-seq) and applied it to postmortem human frontal cortex tissue. We developed a cross-validation approach using multi-modal information to validate fine-grained cell types and assessed the effectiveness of computational data fusion methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility, and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling the prediction of cell types that are associated with diseases.

Published
2022

6. A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex

Author

Yao, Zizhen, Liu, Hanqing, Xie, Fangming, Fischer, Stephan, Adkins, Ricky S, Aldridge, Andrew I, Ament, Seth A, Bartlett, Anna, Behrens, M Margarita, Van den Berge, Koen, Bertagnolli, Darren, de Bézieux, Hector Roux, Biancalani, Tommaso, Booeshaghi, A Sina, Bravo, Héctor Corrada, Casper, Tamara, Colantuoni, Carlo, Crabtree, Jonathan, Creasy, Heather, Crichton, Kirsten, Crow, Megan, Dee, Nick, Dougherty, Elizabeth L, Doyle, Wayne I, Dudoit, Sandrine, Fang, Rongxin, Felix, Victor, Fong, Olivia, Giglio, Michelle, Goldy, Jeff, Hawrylycz, Mike, Herb, Brian R, Hertzano, Ronna, Hou, Xiaomeng, Hu, Qiwen, Kancherla, Jayaram, Kroll, Matthew, Lathia, Kanan, Li, Yang Eric, Lucero, Jacinta D, Luo, Chongyuan, Mahurkar, Anup, McMillen, Delissa, Nadaf, Naeem M, Nery, Joseph R, Nguyen, Thuc Nghi, Niu, Sheng-Yong, Ntranos, Vasilis, Orvis, Joshua, Osteen, Julia K, Pham, Thanh, Pinto-Duarte, Antonio, Poirion, Olivier, Preissl, Sebastian, Purdom, Elizabeth, Rimorin, Christine, Risso, Davide, Rivkin, Angeline C, Smith, Kimberly, Street, Kelly, Sulc, Josef, Svensson, Valentine, Tieu, Michael, Torkelson, Amy, Tung, Herman, Vaishnav, Eeshit Dhaval, Vanderburg, Charles R, van Velthoven, Cindy, Wang, Xinxin, White, Owen R, Huang, Z Josh, Kharchenko, Peter V, Pachter, Lior, Ngai, John, Regev, Aviv, Tasic, Bosiljka, Welch, Joshua D, Gillis, Jesse, Macosko, Evan Z, Ren, Bing, Ecker, Joseph R, Zeng, Hongkui, and Mukamel, Eran A

Subjects
Human Genome, Neurosciences, Genetics, Bioengineering, Biotechnology, 1.1 Normal biological development and functioning, Underpinning research, Neurological, Animals, Atlases as Topic, Datasets as Topic, Epigenesis, Genetic, Epigenomics, Female, Gene Expression Profiling, Male, Mice, Motor Cortex, Neurons, Organ Specificity, Reproducibility of Results, Single-Cell Analysis, Transcriptome, General Science & Technology
Abstract

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.

Published
2021

7. Comparative cellular analysis of motor cortex in human, marmoset and mouse

Author

Bakken, Trygve E, Jorstad, Nikolas L, Hu, Qiwen, Lake, Blue B, Tian, Wei, Kalmbach, Brian E, Crow, Megan, Hodge, Rebecca D, Krienen, Fenna M, Sorensen, Staci A, Eggermont, Jeroen, Yao, Zizhen, Aevermann, Brian D, Aldridge, Andrew I, Bartlett, Anna, Bertagnolli, Darren, Casper, Tamara, Castanon, Rosa G, Crichton, Kirsten, Daigle, Tanya L, Dalley, Rachel, Dee, Nick, Dembrow, Nikolai, Diep, Dinh, Ding, Song-Lin, Dong, Weixiu, Fang, Rongxin, Fischer, Stephan, Goldman, Melissa, Goldy, Jeff, Graybuck, Lucas T, Herb, Brian R, Hou, Xiaomeng, Kancherla, Jayaram, Kroll, Matthew, Lathia, Kanan, van Lew, Baldur, Li, Yang Eric, Liu, Christine S, Liu, Hanqing, Lucero, Jacinta D, Mahurkar, Anup, McMillen, Delissa, Miller, Jeremy A, Moussa, Marmar, Nery, Joseph R, Nicovich, Philip R, Niu, Sheng-Yong, Orvis, Joshua, Osteen, Julia K, Owen, Scott, Palmer, Carter R, Pham, Thanh, Plongthongkum, Nongluk, Poirion, Olivier, Reed, Nora M, Rimorin, Christine, Rivkin, Angeline, Romanow, William J, Sedeño-Cortés, Adriana E, Siletti, Kimberly, Somasundaram, Saroja, Sulc, Josef, Tieu, Michael, Torkelson, Amy, Tung, Herman, Wang, Xinxin, Xie, Fangming, Yanny, Anna Marie, Zhang, Renee, Ament, Seth A, Behrens, M Margarita, Bravo, Hector Corrada, Chun, Jerold, Dobin, Alexander, Gillis, Jesse, Hertzano, Ronna, Hof, Patrick R, Höllt, Thomas, Horwitz, Gregory D, Keene, C Dirk, Kharchenko, Peter V, Ko, Andrew L, Lelieveldt, Boudewijn P, Luo, Chongyuan, Mukamel, Eran A, Pinto-Duarte, António, Preissl, Sebastian, Regev, Aviv, Ren, Bing, Scheuermann, Richard H, Smith, Kimberly, Spain, William J, White, Owen R, Koch, Christof, Hawrylycz, Michael, Tasic, Bosiljka, Macosko, Evan Z, McCarroll, Steven A, and Ting, Jonathan T

Subjects
Human Genome, Neurosciences, Genetics, Biotechnology, Underpinning research, 1.1 Normal biological development and functioning, Neurological, Animals, Atlases as Topic, Callithrix, Epigenesis, Genetic, Epigenomics, Female, GABAergic Neurons, Gene Expression Profiling, Glutamates, Humans, In Situ Hybridization, Fluorescence, Male, Mice, Middle Aged, Motor Cortex, Neurons, Organ Specificity, Phylogeny, Single-Cell Analysis, Species Specificity, Transcriptome, General Science & Technology
Abstract

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.

Published
2021

8. A multimodal cell census and atlas of the mammalian primary motor cortex

Author

Callaway, Edward M, Dong, Hong-Wei, Ecker, Joseph R, Hawrylycz, Michael J, Huang, Z Josh, Lein, Ed S, Ngai, John, Osten, Pavel, Ren, Bing, Tolias, Andreas Savas, White, Owen, Zeng, Hongkui, Zhuang, Xiaowei, Ascoli, Giorgio A, Behrens, M Margarita, Chun, Jerold, Feng, Guoping, Gee, James C, Ghosh, Satrajit S, Halchenko, Yaroslav O, Hertzano, Ronna, Lim, Byung Kook, Martone, Maryann E, Ng, Lydia, Pachter, Lior, Ropelewski, Alexander J, Tickle, Timothy L, Yang, X William, Zhang, Kun, Bakken, Trygve E, Berens, Philipp, Daigle, Tanya L, Harris, Julie A, Jorstad, Nikolas L, Kalmbach, Brian E, Kobak, Dmitry, Li, Yang Eric, Liu, Hanqing, Matho, Katherine S, Mukamel, Eran A, Naeemi, Maitham, Scala, Federico, Tan, Pengcheng, Ting, Jonathan T, Xie, Fangming, Zhang, Meng, Zhang, Zhuzhu, Zhou, Jingtian, Zingg, Brian, Armand, Ethan, Yao, Zizhen, Bertagnolli, Darren, Casper, Tamara, Crichton, Kirsten, Dee, Nick, Diep, Dinh, Ding, Song-Lin, Dong, Weixiu, Dougherty, Elizabeth L, Fong, Olivia, Goldman, Melissa, Goldy, Jeff, Hodge, Rebecca D, Hu, Lijuan, Keene, C Dirk, Krienen, Fenna M, Kroll, Matthew, Lake, Blue B, Lathia, Kanan, Linnarsson, Sten, Liu, Christine S, Macosko, Evan Z, McCarroll, Steven A, McMillen, Delissa, Nadaf, Naeem M, Nguyen, Thuc Nghi, Palmer, Carter R, Pham, Thanh, Plongthongkum, Nongluk, Reed, Nora M, Regev, Aviv, Rimorin, Christine, Romanow, William J, Savoia, Steven, Siletti, Kimberly, Smith, Kimberly, Sulc, Josef, Tasic, Bosiljka, Tieu, Michael, Torkelson, Amy, Tung, Herman, van Velthoven, Cindy TJ, Vanderburg, Charles R, Yanny, Anna Marie, Fang, Rongxin, Hou, Xiaomeng, Lucero, Jacinta D, Osteen, Julia K, Pinto-Duarte, Antonio, and Poirion, Olivier

Subjects
Genetics, Neurosciences, Human Genome, Biotechnology, Underpinning research, 1.1 Normal biological development and functioning, Neurological, Animals, Atlases as Topic, Callithrix, Epigenomics, Female, Gene Expression Profiling, Glutamates, Humans, In Situ Hybridization, Fluorescence, Male, Mice, Motor Cortex, Neurons, Organ Specificity, Phylogeny, Single-Cell Analysis, Species Specificity, Transcriptome, BRAIN Initiative Cell Census Network, General Science & Technology
Abstract

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.

Published
2021

9. Comprehensive analysis of single cell ATAC-seq data with SnapATAC.

Author

Fang, Rongxin, Preissl, Sebastian, Li, Yang, Hou, Xiaomeng, Lucero, Jacinta, Wang, Xinxin, Motamedi, Amir, Shiau, Andrew K, Zhou, Xinzhu, Xie, Fangming, Mukamel, Eran A, Zhang, Kai, Zhang, Yanxiao, Behrens, M Margarita, Ecker, Joseph R, and Ren, Bing

Subjects
Motor Cortex, Chromatin, Animals, Mice, Inbred C57BL, Mice, Sequence Analysis, DNA, Computational Biology, Male, Epigenomics, Single-Cell Analysis, Chromatin Immunoprecipitation Sequencing, Human Genome, Genetics, Biotechnology, 1.1 Normal biological development and functioning
Abstract

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.

Published
2021

10. Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes

Author

Armand, Ethan J, Li, Junhao, Xie, Fangming, Luo, Chongyuan, and Mukamel, Eran A

Subjects
Genetics, Biotechnology, Neurosciences, Human Genome, Bioengineering, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Neurological, Brain, DNA Methylation, Epigenome, Epigenomics, Humans, Sequence Analysis, DNA, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome, ATAC-seq, DNA methylation, cell state, cell type, epigenome, multi-omics, open chromatin, single-cell sequencing, spatial transcriptomics, transcriptome, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Single-cell sequencing technologies, including transcriptomic and epigenomic assays, are transforming our understanding of the cellular building blocks of neural circuits. By directly measuring multiple molecular signatures in thousands to millions of individual cells, single-cell sequencing methods can comprehensively characterize the diversity of brain cell types. These measurements uncover gene regulatory mechanisms that shape cellular identity and provide insight into developmental and evolutionary relationships between brain cell populations. Single-cell sequencing data can aid the design of tools for targeted functional studies of brain circuit components, linking molecular signatures with anatomy, connectivity, morphology, and physiology. Here, we discuss the fundamental principles of single-cell transcriptome and epigenome sequencing, integrative computational analysis of the data, and key applications in neuroscience.

Published
2021

13. Orientational Phase Transitions and the Assembly of Viral Capsids

Author

Dharmavaram, Sanjay, Xie, Fangming, Klug, William, Rudnick, Joseph, and Bruinsma, Robijn

Subjects
Physics - Biological Physics, Condensed Matter - Soft Condensed Matter, Quantitative Biology - Subcellular Processes
Abstract

We present a generalized Landau-Brazovskii free energy for the solidification of chiral molecules on a spherical surface in the context of the assembly of viral shells. We encounter two types of icosahedral solidification transitions. The first type is a conventional first-order phase transition from the uniform to the icosahedral state. It can be described by a single icosahedral spherical harmonic of even $l$. The chiral pseudo-scalar term in the free energy creates secondary terms with chiral character but it does not affect the thermodynamics of the transition. The second type, associated with icosahedral spherical harmonics with odd $l$, is anomalous. Pure odd $l$ icosahedral states are unstable but stability is recovered if admixture with the neighboring $l+1$ icosahedral spherical harmonic is included, generated by the non-linear terms. This is in conflict with the principle of Landau theory that symmetry-breaking transitions are characterized by only a \textit{single} irreducible representation of the symmetry group of the uniform phase and we argue that this principle should be removed from Landau theory. The chiral term now directly affects the transition because it lifts the degeneracy between two isomeric mixed-$l$ icosahedral states. A direct transition is possible only over a limited range of parameters. Outside this range, non-icosahedral states intervene. For the important case of capsid assembly dominated by $l=15$, the intervening states are found to be based on octahedral symmetry.

Published
2017
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15. Landau Theory and the Emergence of Chirality in Viral Capsids

Author

Dharmavaram, Sanjay, Xie, Fangming, Klug, William, Rudnick, Joseph, and Bruinsma, Robijn

Subjects
Physics - Biological Physics, Condensed Matter - Soft Condensed Matter, Quantitative Biology - Subcellular Processes
Abstract

We present a generalized Landau-Brazovskii theory for the solidification of chiral molecules on a spherical surface. With increasing sphere radius one encounters first intervals where robust achiral density modulations appear with icosahedral symmetry via first-order transitions. Next, one en- counters intervals where fragile but stable icosahedral structures still can be constructed but only by superposition of multiple irreducible representations. Chiral icoshedral structures appear via continuous or very weakly first-order transitions. Outside these parameter intervals, icosahedral symmetry is broken along a three-fold axis or a five-fold axis. The predictions of the theory are compared with recent numerical simulations.

Published
2016
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18. Author Correction: Comparative cellular analysis of motor cortex in human, marmoset and mouse

Author

Bakken, Trygve E., Jorstad, Nikolas L., Hu, Qiwen, Lake, Blue B., Tian, Wei, Kalmbach, Brian E., Crow, Megan, Hodge, Rebecca D., Krienen, Fenna M., Sorensen, Staci A., Eggermont, Jeroen, Yao, Zizhen, Aevermann, Brian D., Aldridge, Andrew I., Bartlett, Anna, Bertagnolli, Darren, Casper, Tamara, Castanon, Rosa G., Crichton, Kirsten, Daigle, Tanya L., Dalley, Rachel, Dee, Nick, Dembrow, Nikolai, Diep, Dinh, Ding, Song-Lin, Dong, Weixiu, Fang, Rongxin, Fischer, Stephan, Goldman, Melissa, Goldy, Jeff, Graybuck, Lucas T., Herb, Brian R., Hou, Xiaomeng, Kancherla, Jayaram, Kroll, Matthew, Lathia, Kanan, van Lew, Baldur, Li, Yang Eric, Liu, Christine S., Liu, Hanqing, Lucero, Jacinta D., Mahurkar, Anup, McMillen, Delissa, Miller, Jeremy A., Moussa, Marmar, Nery, Joseph R., Nicovich, Philip R., Niu, Sheng-Yong, Orvis, Joshua, Osteen, Julia K., Owen, Scott, Palmer, Carter R., Pham, Thanh, Plongthongkum, Nongluk, Poirion, Olivier, Reed, Nora M., Rimorin, Christine, Rivkin, Angeline, Romanow, William J., Sedeño-Cortés, Adriana E., Siletti, Kimberly, Somasundaram, Saroja, Sulc, Josef, Tieu, Michael, Torkelson, Amy, Tung, Herman, Wang, Xinxin, Xie, Fangming, Yanny, Anna Marie, Zhang, Renee, Ament, Seth A., Behrens, M. Margarita, Bravo, Hector Corrada, Chun, Jerold, Dobin, Alexander, Gillis, Jesse, Hertzano, Ronna, Hof, Patrick R., Höllt, Thomas, Horwitz, Gregory D., Keene, C. Dirk, Kharchenko, Peter V., Ko, Andrew L., Lelieveldt, Boudewijn P., Luo, Chongyuan, Mukamel, Eran A., Pinto-Duarte, António, Preiss, Sebastian, Regev, Aviv, Ren, Bing, Scheuermann, Richard H., Smith, Kimberly, Spain, William J., White, Owen R., Koch, Christof, Hawrylycz, Michael, Tasic, Bosiljka, Macosko, Evan Z., McCarroll, Steven A., Ting, Jonathan T., Zeng, Hongkui, Zhang, Kun, Feng, Guoping, Ecker, Joseph R., Linnarsson, Sten, and Lein, Ed S.

Published
2022
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19. Integrated computational analysis of brain cell transcriptomes and epigenomes

Author

Xie, Fangming

Subjects
Neurosciences, Biophysics, Genetics
Abstract

The mammalian brain consists of a vast network of neurons and non-neuronal cells with diverse morphology, anatomy, physiology and behavioral roles. These cellular phenotypes are enacted and maintained by a complex molecular program, including the abundance of gene transcripts, i.e. the transcriptome, and epigenetic modifications of DNA, i.e., the epigenome. Single cell sequencing assays, capable of measuring the entire transcriptome or epigenome for hundreds of thousands of single cells, have enabled the systematic characterization of brain cell types at unprecedented scale and with fine granularity. However, it is challenging to integrate diverse datasets, which differ in sample and library preparation, sequencing platforms, and assay modalities, for a consistent biological understanding of cell type organization. This thesis presents novel computational algorithms to integrate brain cell transcriptomes and epigenomes. We developed SingleCellFusion, which integrates disparate datasets into a common feature space based on a constrained k-nearest-neighbor graph algorithm. Using SingleCellFusion, we integrated 8 datasets with >400,000 cells from the mouse primary motor cortex (MOp). This analysis identified 56 neuronal cell types with consistent cell type specific patterns of gene expression, chromatin accessibility and DNA methylation. To validate the accuracy of SingleCellFusion, we helped to develop a novel multimodal sequencing assay, snmCAT-seq, that simultaneously measures methylCytosine (mC), chromatin Accessibility (A), and Transcriptome (T) from the same cells. Applying snmCAT-seq to 3,898 human frontal cortex cells, we identified fine grained neuronal cell types. SingleCellFusion integrated single-cell transcriptomes and DNA methylomes from the same cell types with 62.6~87.3% accuracy, recapitulating snmCAT-seq results at the cell type level. Cell type specific gene expression is in part regulated by epigenetic modifications of DNA at cis-regulatory elements (CREs), which are typically located thousands of base pairs away from the gene they regulate. We took advantage of co-variations in gene expression and epigenetic activity at candidate CREs across cell types to identify brain cell-type-specific gene-CRE associations. We developed a method that identified more than 10,000 robust gene-CRE associations from mouse MOp, using an empirical data shuffling procedure to control for false positives due to gene co-expression. Our results highlight the power of integrating transcriptomes and epigenomes to uncover the complex molecular regulation of brain cell types, and will directly enable design of reagents to target specific cell types for functional analysis. It also demonstrates that robust and efficient computational analysis methods are imperative to distill biological understandings from disparate large-scale single cell sequencing data.

Published
2021

26. Epigenomic and chromosomal architectural reconfiguration in developing human frontal cortex and hippocampus

Author

Heffel, Matthew G., primary, Zhou, Jingtian, additional, Zhang, Yi, additional, Lee, Dong-Sung, additional, Hou, Kangcheng, additional, Alonso, Oier Pastor, additional, Abuhanna, Kevin, additional, Schmitt, Anthony D., additional, Li, Terence, additional, Haeussler, Maximilian, additional, Wick, Brittney, additional, Zhang, Martin Jinye, additional, Xie, Fangming, additional, Ziffra, Ryan S., additional, Mukamel, Eran A., additional, Eskin, Eleazar, additional, Pasaniuc, Bogdan, additional, Ecker, Joseph R., additional, Dixon, Jesse, additional, Nowakowski, Tomasz J, additional, Paredes, Mercedes F., additional, and Luo, Chongyuan, additional

Published
2022
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27. Spatial spillover effect of environmental regulation on regional economic growth.

Author

Xie, Fangming, Liu, Yali, and Yang, Mengman

Subjects
ENVIRONMENTAL regulations, ECONOMIC expansion, REGULATION of growth, ENVIRONMENTAL policy, ECONOMIC development
Abstract

China's rapid economic development has attracted worldwide attention, but the resulting environmental problems also cannot be ignored. Whether environmental regulations can achieve a win–win situation between "green" and "economic growth" has become the focus of academic circles. While related studies have examined environmental regulation through the "Cost-following theory" and "Porter hypothesis", they have mostly focused on a particular region or province, thus neglecting the spatial effects. The spatial effects of environmental regulation are important to study because of the overall environmental correlation across regions and especially adjacent provinces. This paper extends the "cost-following theory" and the "Porter hypothesis" to the spatial perspective and proposes two hypotheses, respectively. Through the spatial expansion of environmental regulation theory, this paper not only analyses the direct effect of local environmental regulation on local economic growth, but also the spatial spillover effect of adjacent provinces' environmental regulation on local economic growth. The empirical results show that the relationship between environmental regulation and economic growth in China is consistent with the spatial perspective of "Cost-following theory", but not with the spatial perspective of "Porter hypothesis". Through the above analysis, this paper is able to address the issues of how to make environmental regulation policies in adjacent provinces or regions as a whole, and how to coordinate environmental regulation with economic growth in adjacent regions. The findings of this paper also suggest that spatial effects need to be sufficiently considered in future studies on environment-related issues. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Comparative cellular analysis of motor cortex in human, marmoset and mouse

Author

Bakken, Trygve E., Jorstad, Nikolas L., Hu, Qiwen, Lake, Blue B., Tian, Wei, Kalmbach, Brian E., Crow, Megan, Hodge, Rebecca D., Krienen, Fenna M., Sorensen, Staci A., Eggermont, Jeroen, Yao, Zizhen, Aevermann, Brian D., Aldridge, Andrew I., Bartlett, Anna, Bertagnolli, Darren, Casper, Tamara, Castanon, Rosa G., Crichton, Kirsten, Daigle, Tanya L., Dalley, Rachel, Dee, Nick, Dembrow, Nikolai, Diep, Dinh, Ding, Song-Lin, Dong, Weixiu, Fang, Rongxin, Fischer, Stephan, Goldman, Melissa, Goldy, Jeff, Graybuck, Lucas T., Herb, Brian R., Hou, Xiaomeng, Kancherla, Jayaram, Kroll, Matthew, Lathia, Kanan, van Lew, Baldur, Li, Yang Eric, Liu, Christine S., Liu, Hanqing, Lucero, Jacinta D., Mahurkar, Anup, McMillen, Delissa, Miller, Jeremy A., Moussa, Marmar, Nery, Joseph R., Nicovich, Philip R., Niu, Sheng-Yong, Orvis, Joshua, Osteen, Julia K., Owen, Scott, Palmer, Carter R., Pham, Thanh, Plongthongkum, Nongluk, Poirion, Olivier, Reed, Nora M., Rimorin, Christine, Rivkin, Angeline, Romanow, William J., Sedeño-Cortés, Adriana E., Siletti, Kimberly, Somasundaram, Saroja, Sulc, Josef, Tieu, Michael, Torkelson, Amy, Tung, Herman, Wang, Xinxin, Xie, Fangming, Yanny, Anna Marie, Zhang, Renee, Ament, Seth A., Behrens, M. Margarita, Bravo, Hector Corrada, Chun, Jerold, Dobin, Alexander, Gillis, Jesse, Hertzano, Ronna, Hof, Patrick R., Höllt, Thomas, Horwitz, Gregory D., Keene, C. Dirk, Kharchenko, Peter V., Ko, Andrew L., Lelieveldt, Boudewijn P., Luo, Chongyuan, Mukamel, Eran A., Pinto-Duarte, António, Preissl, Sebastian, Regev, Aviv, Ren, Bing, Scheuermann, Richard H., Smith, Kimberly, Spain, William J., White, Owen R., Koch, Christof, Hawrylycz, Michael, Tasic, Bosiljka, Macosko, Evan Z., McCarroll, Steven A., Ting, Jonathan T., Zeng, Hongkui, Zhang, Kun, Feng, Guoping, Ecker, Joseph R., Linnarsson, Sten, Lein, Ed S., Bakken, Trygve E., Jorstad, Nikolas L., Hu, Qiwen, Lake, Blue B., Tian, Wei, Kalmbach, Brian E., Crow, Megan, Hodge, Rebecca D., Krienen, Fenna M., Sorensen, Staci A., Eggermont, Jeroen, Yao, Zizhen, Aevermann, Brian D., Aldridge, Andrew I., Bartlett, Anna, Bertagnolli, Darren, Casper, Tamara, Castanon, Rosa G., Crichton, Kirsten, Daigle, Tanya L., Dalley, Rachel, Dee, Nick, Dembrow, Nikolai, Diep, Dinh, Ding, Song-Lin, Dong, Weixiu, Fang, Rongxin, Fischer, Stephan, Goldman, Melissa, Goldy, Jeff, Graybuck, Lucas T., Herb, Brian R., Hou, Xiaomeng, Kancherla, Jayaram, Kroll, Matthew, Lathia, Kanan, van Lew, Baldur, Li, Yang Eric, Liu, Christine S., Liu, Hanqing, Lucero, Jacinta D., Mahurkar, Anup, McMillen, Delissa, Miller, Jeremy A., Moussa, Marmar, Nery, Joseph R., Nicovich, Philip R., Niu, Sheng-Yong, Orvis, Joshua, Osteen, Julia K., Owen, Scott, Palmer, Carter R., Pham, Thanh, Plongthongkum, Nongluk, Poirion, Olivier, Reed, Nora M., Rimorin, Christine, Rivkin, Angeline, Romanow, William J., Sedeño-Cortés, Adriana E., Siletti, Kimberly, Somasundaram, Saroja, Sulc, Josef, Tieu, Michael, Torkelson, Amy, Tung, Herman, Wang, Xinxin, Xie, Fangming, Yanny, Anna Marie, Zhang, Renee, Ament, Seth A., Behrens, M. Margarita, Bravo, Hector Corrada, Chun, Jerold, Dobin, Alexander, Gillis, Jesse, Hertzano, Ronna, Hof, Patrick R., Höllt, Thomas, Horwitz, Gregory D., Keene, C. Dirk, Kharchenko, Peter V., Ko, Andrew L., Lelieveldt, Boudewijn P., Luo, Chongyuan, Mukamel, Eran A., Pinto-Duarte, António, Preissl, Sebastian, Regev, Aviv, Ren, Bing, Scheuermann, Richard H., Smith, Kimberly, Spain, William J., White, Owen R., Koch, Christof, Hawrylycz, Michael, Tasic, Bosiljka, Macosko, Evan Z., McCarroll, Steven A., Ting, Jonathan T., Zeng, Hongkui, Zhang, Kun, Feng, Guoping, Ecker, Joseph R., Linnarsson, Sten, and Lein, Ed S.

Abstract

AbstractThe 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.

Published
2022

33. A multimodal cell census and atlas of the mammalian primary motor cortex

Author

Callaway, Edward M., Dong, Hong-Wei, Ecker, Joseph R., Hawrylycz, Michael J., Huang, Z. Josh, Lein, Ed S., Ngai, John, Osten, Pavel, Ren, Bing, Tolias, Andreas Savas, White, Owen, Zeng, Hongkui, Zhuang, Xiaowei, Ascoli, Giorgio A., Behrens, M. Margarita, Chun, Jerold, Feng, Guoping, Gee, James C., Ghosh, Satrajit S., Halchenko, Yaroslav O., Hertzano, Ronna, Lim, Byung Kook, Martone, Maryann E., Ng, Lydia, Pachter, Lior, Ropelewski, Alexander J., Tickle, Timothy L., Yang, X. William, Zhang, Kun, Bakken, Trygve E., Berens, Philipp, Daigle, Tanya L., Harris, Julie A., Jorstad, Nikolas L., Kalmbach, Brian E., Kobak, Dmitry, Li, Yang Eric, Liu, Hanqing, Matho, Katherine S., Mukamel, Eran A., Naeemi, Maitham, Scala, Federico, Tan, Pengcheng, Ting, Jonathan T., Xie, Fangming, Zhang, Meng, Zhang, Zhuzhu, Zhou, Jingtian, Zingg, Brian, Armand, Ethan, Yao, Zizhen, Bertagnolli, Darren, Casper, Tamara, Crichton, Kirsten, Dee, Nick, Diep, Dinh, Ding, Song-Lin, Dong, Weixiu, Dougherty, Elizabeth L., Fong, Olivia, Goldman, Melissa, Goldy, Jeff, Hodge, Rebecca D., Hu, Lijuan, Keene, C. Dirk, Krienen, Fenna M., Kroll, Matthew, Lake, Blue B., Lathia, Kanan, Linnarsson, Sten, Liu, Christine S., Macosko, Evan Z., McCarroll, Steven A., McMillen, Delissa, Nadaf, Naeem M., Nguyen, Thuc Nghi, Palmer, Carter R., Pham, Thanh, Plongthongkum, Nongluk, Reed, Nora M., Regev, Aviv, Rimorin, Christine, Romanow, William J., Savoia, Steven, Siletti, Kimberly, Smith, Kimberly, Sulc, Josef, Tasic, Bosiljka, Tieu, Michael, Torkelson, Amy, Tung, Herman, van Velthoven, Cindy T. J., Vanderburg, Charles R., Yanny, Anna Marie, Fang, Rongxin, Hou, Xiaomeng, Lucero, Jacinta D., Osteen, Julia K., Pinto-Duarte, Antonio, Poirion, Olivier, Preissl, Sebastian, Wang, Xinxin, Aldridge, Andrew I., Bartlett, Anna, Boggeman, Lara, O’Connor, Carolyn, Castanon, Rosa G., Chen, Huaming, Fitzpatrick, Conor, Luo, Chongyuan, Nery, Joseph R., Nunn, Michael, Rivkin, Angeline C., Tian, Wei, Dominguez, Bertha, Ito-Cole, Tony, Jacobs, Matthew, Jin, Xin, Lee, Cheng-Ta, Lee, Kuo-Fen, Miyazaki, Paula Assakura, Pang, Yan, Rashid, Mohammad, Smith, Jared B., Vu, Minh, Williams, Elora, Biancalani, Tommaso, Booeshaghi, A. Sina, Crow, Megan, Dudoit, Sandrine, Fischer, Stephan, Gillis, Jesse, Hu, Qiwen, Kharchenko, Peter V., Niu, Sheng-Yong, Ntranos, Vasilis, Purdom, Elizabeth, Risso, Davide, de Bézieux, Hector Roux, Somasundaram, Saroja, Street, Kelly, Svensson, Valentine, Vaishnav, Eeshit Dhaval, Van den Berge, Koen, Welch, Joshua D., An, Xu, Bateup, Helen S., Bowman, Ian, Chance, Rebecca K., Foster, Nicholas N., Galbavy, William, Gong, Hui, Gou, Lin, Hatfield, Joshua T., Hintiryan, Houri, Hirokawa, Karla E., Kim, Gukhan, Kramer, Daniel J., Li, Anan, Li, Xiangning, Luo, Qingming, Muñoz-Castañeda, Rodrigo, Stafford, David A., Feng, Zhao, Jia, Xueyan, Jiang, Shengdian, Jiang, Tao, Kuang, Xiuli, Larsen, Rachael, Lesnar, Phil, Li, Yaoyao, Li, Yuanyuan, Liu, Lijuan, Peng, Hanchuan, Qu, Lei, Ren, Miao, Ruan, Zongcai, Shen, Elise, Song, Yuanyuan, Wakeman, Wayne, Wang, Peng, Wang, Yimin, Wang, Yun, Yin, Lulu, Yuan, Jing, Zhao, Sujun, Zhao, Xuan, Narasimhan, Arun, Palaniswamy, Ramesh, Banerjee, Samik, Ding, Liya, Huilgol, Dhananjay, Huo, Bingxing, Kuo, Hsien-Chi, Laturnus, Sophie, Li, Xu, Mitra, Partha P., Mizrachi, Judith, Wang, Quanxin, Xie, Peng, Xiong, Feng, Yu, Yang, Eichhorn, Stephen W., Berg, Jim, Bernabucci, Matteo, Bernaerts, Yves, Cadwell, Cathryn René, Castro, Jesus Ramon, Dalley, Rachel, Hartmanis, Leonard, Horwitz, Gregory D., Jiang, Xiaolong, Ko, Andrew L., Miranda, Elanine, Mulherkar, Shalaka, Nicovich, Philip R., Owen, Scott F., Sandberg, Rickard, Sorensen, Staci A., Tan, Zheng Huan, Allen, Shona, Hockemeyer, Dirk, Lee, Angus Y., Veldman, Matthew B., Adkins, Ricky S., Ament, Seth A., Bravo, Héctor Corrada, Carter, Robert, Chatterjee, Apaala, Colantuoni, Carlo, Crabtree, Jonathan, Creasy, Heather, Felix, Victor, Giglio, Michelle, Herb, Brian R., Kancherla, Jayaram, Mahurkar, Anup, McCracken, Carrie, Nickel, Lance, Olley, Dustin, Orvis, Joshua, Schor, Michael, Hood, Greg, Dichter, Benjamin, Grauer, Michael, Helba, Brian, Bandrowski, Anita, Barkas, Nikolaos, Carlin, Benjamin, D’Orazi, Florence D., Degatano, Kylee, Gillespie, Thomas H., Khajouei, Farzaneh, Konwar, Kishori, Thompson, Carol, Kelly, Kathleen, Mok, Stephanie, Sunkin, Susan, BRAIN Initiative Cell Census Network (BICCN) Corresponding authors, [missing], BICCN contributing principal investigators, [missing], Principal manuscript editors, [missing], Manuscript writing and figure generation, [missing], Analysis coordination, [missing], Integrated data analysis, [missing], scRNA-seq and snRNA-seq data generation and processing, [missing], ATAC-seq data generation and processing, [missing], Methylcytosine data production and analysis, [missing], Epi-retro-seq data generation and processing, [missing], ‘Omics data analysis, [missing], Tracing and connectivity data generation, [missing], Morphology data generation and reconstruction, [missing], OLST/STPT and other data generation, [missing], Morphology, connectivity and imaging analysis, [missing], Spatially resolved single-cell transcriptomics (MERFISH), [missing], Multimodal profiling (Patch-seq), [missing], Transgenic tools, [missing], NeMO archive and analytics, [missing], Brain Image Library (BIL) archive, [missing], DANDI archive, [missing], Brain Cell Data Center (BCDC), [missing], Project management, [missing], and BRAIN Initiative Cell Census Network (BICCN), [missing]

Subjects
Epigenomics, Male, INTERNEURONS, ORGANIZATION, MOUSE, Molecular neuroscience, Neural circuits, CLASSIFICATION, Article, Mice, Atlases as Topic, Glutamates, Species Specificity, Animals, Humans, TRANSCRIPTOMICS, SPECIFICATION, NEURONS, In Situ Hybridization, Fluorescence, Phylogeny, Neurons, Multidisciplinary, Gene Expression Profiling, Biology and Life Sciences, PATHWAYS, Brain, Callithrix, Censuses, Cellular neuroscience, Mathematics and Statistics, SINGLE, Organ Specificity, MORPHOLOGY, Motor cortex, Female, Single-Cell Analysis, Transcriptome
Abstract

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., The BRAIN Initiative Cell Census Network has constructed a multimodal cell census and atlas of the mammalian primary motor cortex in a landmark effort towards understanding brain cell-type diversity, neural circuit organization and brain function.

Published
2021

35. Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes

Author

Xie, Fangming, primary, Armand, Ethan J., additional, Yao, Zizhen, additional, Liu, Hanqing, additional, Bartlett, Anna, additional, Behrens, M. Margarita, additional, Li, Yang Eric, additional, Lucero, Jacinta D., additional, Luo, Chongyuan, additional, Nery, Joseph R., additional, Pinto-Duarte, Antonio, additional, Poirion, Olivier, additional, Preissl, Sebastian, additional, Rivkin, Angeline C., additional, Tasic, Bosiljka, additional, Zeng, Hongkui, additional, Ren, Bing, additional, Ecker, Joseph R., additional, and Mukamel, Eran A., additional

Published
2021
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36. Study on Liquid Phase Hydrogenation Technology of White Oil

Author

Yungang Jia, Wang Fucun, Sun Famin, Zijin Yan, Zhang Tiezhen, Xie Fangming, Jiang Wei, and Haiyan Li

Subjects
Pharmacology, White oil, Materials science, Chemical engineering, Liquid phase
Abstract

Using Aspen Plus simulation software to simulate the hydrogen solubility of white oil raw materials, and calculate the de-aromatic hydrogen consumption. The liquid hydrogenation technology of white oil was studied by using 100mL uplink liquid hydrogenation evaluation device. The research results show that the ultraviolet absorbance of the liquid phase hydrogenation product is no more than 0.1, and saybolt color, copper plate corrosion, readily carbonizable substance can meet the quality requirements under the conditions of 230℃, 17 Mpa and LHSV 0.5 h-1. 2000 hours liquid phase hydrogenation test shows the stability of product quality which meets the food grade standard, and the liquid phase hydrogenation technology is feasible.

Published
2021
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37. An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

Author

Yao, Zizhen, Liu, Hanqing, Xie, Fangming, Fischer, Stephan, Adkins, Ricky S., Aldrige, Andrew I., Ament, Seth A., Bartlett, Ann, Behrens, M. Margarita, Van den Berge, Koen, Bertagnolli, Darren, Biancalani, Tommaso, Booeshaghi, A. Sina, Corrada Bravo, Hector, Casper, Tamara, Colantuoni, Carlo, Crabtree, Jonathan, Creasy, Heather, Crichton, Kirsten, Crow, Megan, Dee, Nick, Dougherty, Elizabeth L., Doyle, Wayne I., Dudoit, Sandrine, Fang, Rongxin, Felix, Victor, Fong, Olivia, Giglio, Michelle, Goldy, Jeff, Hawrylycz, Michael, Roux de Bezieux, Hector, Herb, Brian R., Hertzano, Ronna, Hou, Xiaomeng, Hu, Qiwen, Huang, Z. Josh, Kancherla, Jayaram, Kroll, Matthew, Lathia, Kanan, Li, Yang Eric, Lucero, Jacinta D., Luo, Chongyuan, Mahurkar, Anup, McMillen, Delissa, Nadaf, Naeem M., Nery, Joseph R., Nguyen, Thuc Nghi, Niu, Sheng-Yong, Ntranos, Vasilis, Orvis, Joshua, Osteen, Julia K., Pham, Thanh, Pinto-Duarte, Antonio, Poirion, Olivier, Preissl, Sebastian, Purdom, Elizabeth, Rimorin, Christine, Risso, Davide, Rivkin, Angeline C., Smith, Kimberly, Street, Kelly, Sulc, Josef, Svensson, Valentine, Tieu, Michael, Torkelson, Amy, Tung, Herman, Vaishnav, Eeshit Dhaval, Vanderburg, Charles R., van Velthoven, Cindy, Wang, Xinxin, White, Owen, Gillis, Jesse, Kharchenko, Peter V., Ngai, John, Pachter, Lior, Regev, Aviv, Tasic, Bosiljka, Welch, Joshua D., Ecker, Joseph R., Macosko, Evan, Ren, Bing, Zeng, Hongkui, Mukamel, Eran A., Yao, Zizhen, Liu, Hanqing, Xie, Fangming, Fischer, Stephan, Adkins, Ricky S., Aldrige, Andrew I., Ament, Seth A., Bartlett, Ann, Behrens, M. Margarita, Van den Berge, Koen, Bertagnolli, Darren, Biancalani, Tommaso, Booeshaghi, A. Sina, Corrada Bravo, Hector, Casper, Tamara, Colantuoni, Carlo, Crabtree, Jonathan, Creasy, Heather, Crichton, Kirsten, Crow, Megan, Dee, Nick, Dougherty, Elizabeth L., Doyle, Wayne I., Dudoit, Sandrine, Fang, Rongxin, Felix, Victor, Fong, Olivia, Giglio, Michelle, Goldy, Jeff, Hawrylycz, Michael, Roux de Bezieux, Hector, Herb, Brian R., Hertzano, Ronna, Hou, Xiaomeng, Hu, Qiwen, Huang, Z. Josh, Kancherla, Jayaram, Kroll, Matthew, Lathia, Kanan, Li, Yang Eric, Lucero, Jacinta D., Luo, Chongyuan, Mahurkar, Anup, McMillen, Delissa, Nadaf, Naeem M., Nery, Joseph R., Nguyen, Thuc Nghi, Niu, Sheng-Yong, Ntranos, Vasilis, Orvis, Joshua, Osteen, Julia K., Pham, Thanh, Pinto-Duarte, Antonio, Poirion, Olivier, Preissl, Sebastian, Purdom, Elizabeth, Rimorin, Christine, Risso, Davide, Rivkin, Angeline C., Smith, Kimberly, Street, Kelly, Sulc, Josef, Svensson, Valentine, Tieu, Michael, Torkelson, Amy, Tung, Herman, Vaishnav, Eeshit Dhaval, Vanderburg, Charles R., van Velthoven, Cindy, Wang, Xinxin, White, Owen, Gillis, Jesse, Kharchenko, Peter V., Ngai, John, Pachter, Lior, Regev, Aviv, Tasic, Bosiljka, Welch, Joshua D., Ecker, Joseph R., Macosko, Evan, Ren, Bing, Zeng, Hongkui, and Mukamel, Eran A.

Abstract

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.

Published
2020

39. Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse

Author

Bakken, Trygve E., primary, Jorstad, Nikolas L., additional, Hu, Qiwen, additional, Lake, Blue B., additional, Tian, Wei, additional, Kalmbach, Brian E., additional, Crow, Megan, additional, Hodge, Rebecca D., additional, Krienen, Fenna M., additional, Sorensen, Staci A., additional, Eggermont, Jeroen, additional, Yao, Zizhen, additional, Aevermann, Brian D., additional, Aldridge, Andrew I., additional, Bartlett, Anna, additional, Bertagnolli, Darren, additional, Casper, Tamara, additional, Castanon, Rosa G., additional, Crichton, Kirsten, additional, Daigle, Tanya L., additional, Dalley, Rachel, additional, Dee, Nick, additional, Dembrow, Nikolai, additional, Diep, Dinh, additional, Ding, Song-Lin, additional, Dong, Weixiu, additional, Fang, Rongxin, additional, Fischer, Stephan, additional, Goldman, Melissa, additional, Goldy, Jeff, additional, Graybuck, Lucas T., additional, Herb, Brian R., additional, Hou, Xiaomeng, additional, Kancherla, Jayaram, additional, Kroll, Matthew, additional, Lathia, Kanan, additional, van Lew, Baldur, additional, Li, Yang Eric, additional, Liu, Christine S., additional, Liu, Hanqing, additional, Lucero, Jacinta D., additional, Mahurkar, Anup, additional, McMillen, Delissa, additional, Miller, Jeremy A., additional, Moussa, Marmar, additional, Nery, Joseph R., additional, Nicovich, Philip R., additional, Orvis, Joshua, additional, Osteen, Julia K., additional, Owen, Scott, additional, Palmer, Carter R., additional, Pham, Thanh, additional, Plongthongkum, Nongluk, additional, Poirion, Olivier, additional, Reed, Nora M., additional, Rimorin, Christine, additional, Rivkin, Angeline, additional, Romanow, William J., additional, Sedeño-Cortés, Adriana E., additional, Siletti, Kimberly, additional, Somasundaram, Saroja, additional, Sulc, Josef, additional, Tieu, Michael, additional, Torkelson, Amy, additional, Tung, Herman, additional, Wang, Xinxin, additional, Xie, Fangming, additional, Yanny, Anna Marie, additional, Zhang, Renee, additional, Ament, Seth A., additional, Behrens, M. Margarita, additional, Bravo, Hector Corrada, additional, Chun, Jerold, additional, Dobin, Alexander, additional, Gillis, Jesse, additional, Hertzano, Ronna, additional, Hof, Patrick R., additional, Höllt, Thomas, additional, Horwitz, Gregory D., additional, Keene, C. Dirk, additional, Kharchenko, Peter V., additional, Ko, Andrew L., additional, Lelieveldt, Boudewijn P., additional, Luo, Chongyuan, additional, Mukamel, Eran A., additional, Preissl, Sebastian, additional, Regev, Aviv, additional, Ren, Bing, additional, Scheuermann, Richard H., additional, Smith, Kimberly, additional, Spain, William J., additional, White, Owen R., additional, Koch, Christof, additional, Hawrylycz, Michael, additional, Tasic, Bosiljka, additional, Macosko, Evan Z., additional, McCarroll, Steven A., additional, Ting, Jonathan T., additional, Zeng, Hongkui, additional, Zhang, Kun, additional, Feng, Guoping, additional, Ecker, Joseph R., additional, Linnarsson, Sten, additional, and Lein, Ed S., additional

Published
2020
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40. An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

Author

Yao, Zizhen, primary, Liu, Hanqing, additional, Xie, Fangming, additional, Fischer, Stephan, additional, Booeshaghi, A. Sina, additional, Adkins, Ricky S, additional, Aldridge, Andrew I., additional, Ament, Seth A., additional, Pinto-Duarte, Antonio, additional, Bartlett, Anna, additional, Behrens, M. Margarita, additional, Van den Berge, Koen, additional, Bertagnolli, Darren, additional, Biancalani, Tommaso, additional, Bravo, Héctor Corrada, additional, Casper, Tamara, additional, Colantuoni, Carlo, additional, Creasy, Heather, additional, Crichton, Kirsten, additional, Crow, Megan, additional, Dee, Nick, additional, Dougherty, Elizabeth L, additional, Doyle, Wayne I., additional, Dudoit, Sandrine, additional, Fang, Rongxin, additional, Felix, Victor, additional, Fong, Olivia, additional, Giglio, Michelle, additional, Goldy, Jeff, additional, Hawrylycz, Mike, additional, de Bézieux, Hector Roux, additional, Herb, Brian R., additional, Hertzano, Ronna, additional, Hou, Xiaomeng, additional, Hu, Qiwen, additional, Crabtree, Jonathan, additional, Kancherla, Jayaram, additional, Kroll, Matthew, additional, Lathia, Kanan, additional, Li, Yang Eric, additional, Lucero, Jacinta D., additional, Luo, Chongyuan, additional, Mahurkar, Anup, additional, McMillen, Delissa, additional, Nadaf, Naeem, additional, Nery, Joseph R., additional, Niu, Sheng-Yong, additional, Orvis, Joshua, additional, Osteen, Julia K., additional, Pham, Thanh, additional, Poirion, Olivier, additional, Preissl, Sebastian, additional, Purdom, Elizabeth, additional, Rimorin, Christine, additional, Risso, Davide, additional, Rivkin, Angeline C., additional, Smith, Kimberly, additional, Street, Kelly, additional, Sulc, Josef, additional, Nguyen, Thuc Nghi, additional, Tieu, Michael, additional, Torkelson, Amy, additional, Tung, Herman, additional, Vaishnav, Eeshit Dhaval, additional, Svensson, Valentine, additional, Vanderburg, Charles R., additional, Ntranos, Vasilis, additional, van Velthoven, Cindy, additional, Wang, Xinxin, additional, White, Owen R., additional, Huang, Z. Josh, additional, Kharchenko, Peter V., additional, Pachter, Lior, additional, Ngai, John, additional, Regev, Aviv, additional, Tasic, Bosiljka, additional, Welch, Joshua D., additional, Gillis, Jesse, additional, Macosko, Evan Z., additional, Ren, Bing, additional, Ecker, Joseph R., additional, Zeng, Hongkui, additional, and Mukamel, Eran A., additional

Published
2020
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43. Green Credit and Company R&amp

Author

Chen, Huiying, Liu, Chuanzhe, Xie, Fangming, Zhang, Tong, and Guan, Fangyuan

Subjects
R&amp, Hardware_GENERAL, green credit, environmental production companies, threshold effect, D level
Abstract

Commercial banks follow sustainable development strategies to provide green credit for companies. As the main target for banks to issue green credit, environmental protection companies carry out research and development (R&amp, D) activities for the purposes of protecting the environment and sustainable development. Therefore, the R&amp, D level of environmental protection companies is a measure of whether the green credit policy meets its purpose. Therefore, it is particularly important to study green credit from a company perspective. This paper used panel data from 24 environmental protection companies listed on the Shanghai and Shenzhen Stock Exchange from 2012 to 2017 and adopted a threshold model to examine the relationship between green credit and company R&amp, D level. The results indicate that there is a positive but nonlinear relationship between green credit and company R&amp, D levels. The empirical analysis through the threshold model shows that a threshold effect remains on the relationship and this threshold effect is caused by the levels of firm size, bank lending, and government subsidies.

Published
2019
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44. Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

Author

Luo, Chongyuan, primary, Liu, Hanqing, additional, Xie, Fangming, additional, Armand, Ethan J., additional, Siletti, Kimberly, additional, Bakken, Trygve E., additional, Fang, Rongxin, additional, Doyle, Wayne I., additional, Hodge, Rebecca D., additional, Hu, Lijuan, additional, Wang, Bang-An, additional, Zhang, Zhuzhu, additional, Preissl, Sebastian, additional, Lee, Dong-Sung, additional, Zhou, Jingtian, additional, Niu, Sheng-Yong, additional, Castanon, Rosa, additional, Bartlett, Anna, additional, Rivkin, Angeline, additional, Wang, Xinxin, additional, Lucero, Jacinta, additional, Nery, Joseph R., additional, Davis, David A., additional, Mash, Deborah C., additional, Dixon, Jesse R., additional, Linnarsson, Sten, additional, Lein, Ed, additional, Behrens, M. Margarita, additional, Ren, Bing, additional, Mukamel, Eran A., additional, and Ecker, Joseph R., additional

Published
2019
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46. SnapATAC: A Comprehensive Analysis Package for Single Cell ATAC-seq

Author

Fang, Rongxin, primary, Preissl, Sebastian, additional, Li, Yang, additional, Hou, Xiaomeng, additional, Lucero, Jacinta, additional, Wang, Xinxin, additional, Motamedi, Amir, additional, Shiau, Andrew K., additional, Zhou, Xinzhu, additional, Xie, Fangming, additional, Mukamel, Eran A., additional, Zhang, Kai, additional, Zhang, Yanxiao, additional, Behrens, M. Margarita, additional, Ecker, Joseph R., additional, and Ren, Bing, additional

Published
2019
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