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1. Single-cell analysis of chromatin accessibility in the adult mouse brain

Author

Zu, Songpeng, Li, Yang Eric, Wang, Kangli, Armand, Ethan J, Mamde, Sainath, Amaral, Maria Luisa, Wang, Yuelai, Chu, Andre, Xie, Yang, Miller, Michael, Xu, Jie, Wang, Zhaoning, Zhang, Kai, Jia, Bojing, Hou, Xiaomeng, Lin, Lin, Yang, Qian, Lee, Seoyeon, Li, Bin, Kuan, Samantha, Liu, Hanqing, Zhou, Jingtian, Pinto-Duarte, Antonio, Lucero, Jacinta, Osteen, Julia, Nunn, Michael, Smith, Kimberly A, Tasic, Bosiljka, Yao, Zizhen, Zeng, Hongkui, Wang, Zihan, Shang, Jingbo, Behrens, M Margarita, Ecker, Joseph R, Wang, Allen, Preissl, Sebastian, and Ren, Bing

Subjects
Biochemistry and Cell Biology, Bioinformatics and Computational Biology, Genetics, Biological Sciences, Stem Cell Research, Neurosciences, Biotechnology, Underpinning research, 1.1 Normal biological development and functioning, Neurological, Animals, Humans, Mice, Brain, Cerebral Cortex, Chromatin, Deep Learning, DNA Transposable Elements, Gene Regulatory Networks, Neurons, Single-Cell Analysis, General Science & Technology
Abstract

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.

Published
2023

2. Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain.

Author

Liu, Hanqing, Zeng, Qiurui, Zhou, Jingtian, Bartlett, Anna, Wang, Bang-An, Tian, Wei, Kenworthy, Mia, Altshul, Jordan, Nery, Joseph, Chen, Huaming, Castanon, Rosa, Zu, Songpeng, Li, Yang, Lucero, Jacinta, Osteen, Julia, Pinto-Duarte, Antonio, Lee, Jasper, Rink, Jon, Cho, Silvia, Emerson, Nora, Nunn, Michael, OConnor, Carolyn, Wu, Zhanghao, Stoica, Ion, Yao, Zizhen, Smith, Kimberly, Tasic, Bosiljka, Luo, Chongyuan, Dixon, Jesse, Zeng, Hongkui, Ren, Bing, Behrens, M, Ecker, Joseph, and Berube, Peter

Subjects
Animals, Mice, Brain, Chromatin, Cytosine, Datasets as Topic, DNA Methylation, Epigenome, Multiomics, Single-Cell Analysis, Transcription Factors, Transcription, Genetic
Abstract

Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation-methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 cross-modality-annotated subclasses. We identified 2.6 million differentially methylated regions across the genome that represent potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide spatial transcriptomics data validated the association of spatial epigenetic diversity with transcription and improved the anatomical mapping of our epigenetic datasets. Furthermore, chromatin conformation diversities occurred in important neuronal genes and were highly associated with DNA methylation and transcription changes. Brain-wide cell-type comparisons enabled the construction of regulatory networks that incorporate transcription factors, regulatory elements and their potential downstream gene targets. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a whole-brain SMART-seq2 dataset. Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellular-spatial and regulatory genome diversity of the mouse brain.

Published
2023

3. Brain-wide correspondence of neuronal epigenomics and distant projections.

Author

Zhou, Jingtian, Zhang, Zhuzhu, Wu, May, Liu, Hanqing, Pang, Yan, Bartlett, Anna, Peng, Zihao, Ding, Wubin, Rivkin, Angeline, Lagos, Will, Williams, Elora, Lee, Cheng-Ta, Miyazaki, Paula, Aldridge, Andrew, Zeng, Qiurui, Salinda, J, Claffey, Naomi, Liem, Michelle, Fitzpatrick, Conor, Boggeman, Lara, Yao, Zizhen, Smith, Kimberly, Tasic, Bosiljka, Altshul, Jordan, Kenworthy, Mia, Valadon, Cynthia, Nery, Joseph, Castanon, Rosa, Patne, Neelakshi, Vu, Minh, Rashid, Mohammad, Jacobs, Matthew, Ito, Tony, Osteen, Julia, Emerson, Nora, Lee, Jasper, Cho, Silvia, Rink, Jon, Huang, Hsiang-Hsuan, Pinto-Duartec, António, Dominguez, Bertha, Smith, Jared, OConnor, Carolyn, Zeng, Hongkui, Chen, Shengbo, Lee, Kuo-Fen, Jin, Xin, Margarita Behrens, M, Ecker, Joseph, Callaway, Edward, and Mukamel, Eran

Subjects
Animals, Mice, Amygdala, Brain, Consensus Sequence, Datasets as Topic, Epigenomics, Gene Expression Profiling, Hypothalamus, Mesencephalon, Neural Pathways, Neurons, Neurotransmitter Agents, Regulatory Sequences, Nucleic Acid, Rhombencephalon, Single-Cell Analysis, Thalamus, Transcription Factors
Abstract

Single-cell analyses parse the brains billions of neurons into thousands of cell-type clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.

Published
2023

4. 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

5. 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

6. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

Author

Yao, Zizhen, van Velthoven, Cindy T. J., Kunst, Michael, Zhang, Meng, McMillen, Delissa, Lee, Changkyu, Jung, Won, Goldy, Jeff, Abdelhak, Aliya, Aitken, Matthew, Baker, Katherine, Baker, Pamela, Barkan, Eliza, Bertagnolli, Darren, Bhandiwad, Ashwin, Bielstein, Cameron, Bishwakarma, Prajal, Campos, Jazmin, Carey, Daniel, Casper, Tamara, Chakka, Anish Bhaswanth, Chakrabarty, Rushil, Chavan, Sakshi, Chen, Min, Clark, Michael, Close, Jennie, Crichton, Kirsten, Daniel, Scott, DiValentin, Peter, Dolbeare, Tim, Ellingwood, Lauren, Fiabane, Elysha, Fliss, Timothy, Gee, James, Gerstenberger, James, Glandon, Alexandra, Gloe, Jessica, Gould, Joshua, Gray, James, Guilford, Nathan, Guzman, Junitta, Hirschstein, Daniel, Ho, Windy, Hooper, Marcus, Huang, Mike, Hupp, Madie, Jin, Kelly, Kroll, Matthew, Lathia, Kanan, Leon, Arielle, Li, Su, Long, Brian, Madigan, Zach, Malloy, Jessica, Malone, Jocelin, Maltzer, Zoe, Martin, Naomi, McCue, Rachel, McGinty, Ryan, Mei, Nicholas, Melchor, Jose, Meyerdierks, Emma, Mollenkopf, Tyler, Moonsman, Skyler, Nguyen, Thuc Nghi, Otto, Sven, Pham, Trangthanh, Rimorin, Christine, Ruiz, Augustin, Sanchez, Raymond, Sawyer, Lane, Shapovalova, Nadiya, Shepard, Noah, Slaughterbeck, Cliff, Sulc, Josef, Tieu, Michael, Torkelson, Amy, Tung, Herman, Valera Cuevas, Nasmil, Vance, Shane, Wadhwani, Katherine, Ward, Katelyn, Levi, Boaz, Farrell, Colin, Young, Rob, Staats, Brian, Wang, Ming-Qiang Michael, Thompson, Carol L., Mufti, Shoaib, Pagan, Chelsea M., Kruse, Lauren, Dee, Nick, Sunkin, Susan M., Esposito, Luke, Hawrylycz, Michael J., Waters, Jack, Ng, Lydia, Smith, Kimberly, Tasic, Bosiljka, Zhuang, Xiaowei, and Zeng, Hongkui

Published
2023
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7. A transcriptomic taxonomy of mouse brain-wide spinal projecting neurons

Author

Winter, Carla C., Jacobi, Anne, Su, Junfeng, Chung, Leeyup, van Velthoven, Cindy T. J., Yao, Zizhen, Lee, Changkyu, Zhang, Zicong, Yu, Shuguang, Gao, Kun, Duque Salazar, Geraldine, Kegeles, Evgenii, Zhang, Yu, Tomihiro, Makenzie C., Zhang, Yiming, Yang, Zhiyun, Zhu, Junjie, Tang, Jing, Song, Xuan, Donahue, Ryan J., Wang, Qing, McMillen, Delissa, Kunst, Michael, Wang, Ning, Smith, Kimberly A., Romero, Gabriel E., Frank, Michelle M., Krol, Alexandra, Kawaguchi, Riki, Geschwind, Daniel H., Feng, Guoping, Goodrich, Lisa V., Liu, Yuanyuan, Tasic, Bosiljka, Zeng, Hongkui, and He, Zhigang

Published
2023
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9. Phenotypic variation of transcriptomic cell types in mouse motor cortex

Author

Scala, Federico, Kobak, Dmitry, Bernabucci, Matteo, Bernaerts, Yves, Cadwell, Cathryn René, Castro, Jesus Ramon, Hartmanis, Leonard, Jiang, Xiaolong, Laturnus, Sophie, Miranda, Elanine, Mulherkar, Shalaka, Tan, Zheng Huan, Yao, Zizhen, Zeng, Hongkui, Sandberg, Rickard, Berens, Philipp, and Tolias, Andreas S

Subjects
Brain Disorders, Genetics, Neurosciences, Neurological, Animals, Atlases as Topic, Female, GABAergic Neurons, Gene Expression Profiling, Glutamates, Lysine, Male, Mice, Motor Cortex, Neurons, Organ Specificity, Patch-Clamp Techniques, Phenotype, Sequence Analysis, RNA, Single-Cell Analysis, Staining and Labeling, Transcriptome, General Science & Technology
Abstract

Cortical neurons exhibit extreme diversity in gene expression as well as in morphological and electrophysiological properties1,2. Most existing neural taxonomies are based on either transcriptomic3,4 or morpho-electric5,6 criteria, as it has been technically challenging to study both aspects of neuronal diversity in the same set of cells7. Here we used Patch-seq8 to combine patch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in adult mouse primary motor cortex, providing a morpho-electric annotation of almost all transcriptomically defined neural cell types. We found that, although broad families of transcriptomic types (those expressing Vip, Pvalb, Sst and so on) had distinct and essentially non-overlapping morpho-electric phenotypes, individual transcriptomic types within the same family were not well separated in the morpho-electric space. Instead, there was a continuum of variability in morphology and electrophysiology, with neighbouring transcriptomic cell types showing similar morpho-electric features, often without clear boundaries between them. Our results suggest that neuronal types in the neocortex do not always form discrete entities. Instead, neurons form a hierarchy that consists of distinct non-overlapping branches at the level of families, but can form continuous and correlated transcriptomic and morpho-electrical landscapes within families.

Published
2021

10. 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

11. 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

12. 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

13. A coupled autoencoder approach for multi-modal analysis of cell types

Author

Gala, Rohan, Gouwens, Nathan, Yao, Zizhen, Budzillo, Agata, Penn, Osnat, Tasic, Bosiljka, Murphy, Gabe, Zeng, Hongkui, and Sümbül, Uygar

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Recent developments in high throughput profiling of individual neurons have spurred data driven exploration of the idea that there exist natural groupings of neurons referred to as cell types. The promise of this idea is that the immense complexity of brain circuits can be reduced, and effectively studied by means of interactions between cell types. While clustering of neuron populations based on a particular data modality can be used to define cell types, such definitions are often inconsistent across different characterization modalities. We pose this issue of cross-modal alignment as an optimization problem and develop an approach based on coupled training of autoencoders as a framework for such analyses. We apply this framework to a Patch-seq dataset consisting of transcriptomic and electrophysiological profiles for the same set of neurons to study consistency of representations across modalities, and evaluate cross-modal data prediction ability. We explore the problem where only a subset of neurons is characterized with more than one modality, and demonstrate that representations learned by coupled autoencoders can be used to identify types sampled only by a single modality., Comment: Main text : 10 pages, 5 figures. Supp text : 6 pages, 3 figures

Published
2019

14. Conserved cell types with divergent features in human versus mouse cortex.

Author

Hodge, Rebecca D, Bakken, Trygve E, Miller, Jeremy A, Smith, Kimberly A, Barkan, Eliza R, Graybuck, Lucas T, Close, Jennie L, Long, Brian, Johansen, Nelson, Penn, Osnat, Yao, Zizhen, Eggermont, Jeroen, Höllt, Thomas, Levi, Boaz P, Shehata, Soraya I, Aevermann, Brian, Beller, Allison, Bertagnolli, Darren, Brouner, Krissy, Casper, Tamara, Cobbs, Charles, Dalley, Rachel, Dee, Nick, Ding, Song-Lin, Ellenbogen, Richard G, Fong, Olivia, Garren, Emma, Goldy, Jeff, Gwinn, Ryder P, Hirschstein, Daniel, Keene, C Dirk, Keshk, Mohamed, Ko, Andrew L, Lathia, Kanan, Mahfouz, Ahmed, Maltzer, Zoe, McGraw, Medea, Nguyen, Thuc Nghi, Nyhus, Julie, Ojemann, Jeffrey G, Oldre, Aaron, Parry, Sheana, Reynolds, Shannon, Rimorin, Christine, Shapovalova, Nadiya V, Somasundaram, Saroja, Szafer, Aaron, Thomsen, Elliot R, Tieu, Michael, Quon, Gerald, Scheuermann, Richard H, Yuste, Rafael, Sunkin, Susan M, Lelieveldt, Boudewijn, Feng, David, Ng, Lydia, Bernard, Amy, Hawrylycz, Michael, Phillips, John W, Tasic, Bosiljka, Zeng, Hongkui, Jones, Allan R, Koch, Christof, and Lein, Ed S

Subjects
Cerebral Cortex, Astrocytes, Neurons, Animals, Humans, Mice, Species Specificity, Neural Inhibition, Principal Component Analysis, Adolescent, Adult, Aged, Middle Aged, Female, Male, Young Adult, Biological Evolution, Single-Cell Analysis, Transcriptome, RNA-Seq, Genetics, Neurosciences, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Aetiology, Underpinning research, Neurological, General Science & Technology
Abstract

Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.

Published
2019

17. Morphological diversity of single neurons in molecularly defined cell types

Author

Peng, Hanchuan, Xie, Peng, Liu, Lijuan, Kuang, Xiuli, Wang, Yimin, Qu, Lei, Gong, Hui, Jiang, Shengdian, Li, Anan, Ruan, Zongcai, Ding, Liya, Yao, Zizhen, Chen, Chao, Chen, Mengya, Daigle, Tanya L., Dalley, Rachel, Ding, Zhangcan, Duan, Yanjun, Feiner, Aaron, He, Ping, Hill, Chris, Hirokawa, Karla E., Hong, Guodong, Huang, Lei, Kebede, Sara, Kuo, Hsien-Chi, Larsen, Rachael, Lesnar, Phil, Li, Longfei, Li, Qi, Li, Xiangning, Li, Yaoyao, Li, Yuanyuan, Liu, An, Lu, Donghuan, Mok, Stephanie, Ng, Lydia, Nguyen, Thuc Nghi, Ouyang, Qiang, Pan, Jintao, Shen, Elise, Song, Yuanyuan, Sunkin, Susan M., Tasic, Bosiljka, Veldman, Matthew B., Wakeman, Wayne, Wan, Wan, Wang, Peng, Wang, Quanxin, Wang, Tao, Wang, Yaping, Xiong, Feng, Xiong, Wei, Xu, Wenjie, Ye, Min, Yin, Lulu, Yu, Yang, Yuan, Jia, Yuan, Jing, Yun, Zhixi, Zeng, Shaoqun, Zhang, Shichen, Zhao, Sujun, Zhao, Zijun, Zhou, Zhi, Huang, Z. Josh, Esposito, Luke, Hawrylycz, Michael J., Sorensen, Staci A., Yang, X. William, Zheng, Yefeng, Gu, Zhongze, Xie, Wei, Koch, Christof, Luo, Qingming, Harris, Julie A., Wang, Yun, and Zeng, Hongkui

Published
2021
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19. Human neocortical expansion involves glutamatergic neuron diversification

Author

Berg, Jim, Sorensen, Staci A., Ting, Jonathan T., Miller, Jeremy A., Chartrand, Thomas, Buchin, Anatoly, Bakken, Trygve E., Budzillo, Agata, Dee, Nick, Ding, Song-Lin, Gouwens, Nathan W., Hodge, Rebecca D., Kalmbach, Brian, Lee, Changkyu, Lee, Brian R., Alfiler, Lauren, Baker, Katherine, Barkan, Eliza, Beller, Allison, Berry, Kyla, Bertagnolli, Darren, Bickley, Kris, Bomben, Jasmine, Braun, Thomas, Brouner, Krissy, Casper, Tamara, Chong, Peter, Crichton, Kirsten, Dalley, Rachel, de Frates, Rebecca, Desta, Tsega, Lee, Samuel Dingman, D’Orazi, Florence, Dotson, Nadezhda, Egdorf, Tom, Enstrom, Rachel, Farrell, Colin, Feng, David, Fong, Olivia, Furdan, Szabina, Galakhova, Anna A., Gamlin, Clare, Gary, Amanda, Glandon, Alexandra, Goldy, Jeff, Gorham, Melissa, Goriounova, Natalia A., Gratiy, Sergey, Graybuck, Lucas, Gu, Hong, Hadley, Kristen, Hansen, Nathan, Heistek, Tim S., Henry, Alex M., Heyer, Djai B., Hill, DiJon, Hill, Chris, Hupp, Madie, Jarsky, Tim, Kebede, Sara, Keene, Lisa, Kim, Lisa, Kim, Mean-Hwan, Kroll, Matthew, Latimer, Caitlin, Levi, Boaz P., Link, Katherine E., Mallory, Matthew, Mann, Rusty, Marshall, Desiree, Maxwell, Michelle, McGraw, Medea, McMillen, Delissa, Melief, Erica, Mertens, Eline J., Mezei, Leona, Mihut, Norbert, Mok, Stephanie, Molnar, Gabor, Mukora, Alice, Ng, Lindsay, Ngo, Kiet, Nicovich, Philip R., Nyhus, Julie, Olah, Gaspar, Oldre, Aaron, Omstead, Victoria, Ozsvar, Attila, Park, Daniel, Peng, Hanchuan, Pham, Trangthanh, Pom, Christina A., Potekhina, Lydia, Rajanbabu, Ramkumar, Ransford, Shea, Reid, David, Rimorin, Christine, Ruiz, Augustin, Sandman, David, Sulc, Josef, Sunkin, Susan M., Szafer, Aaron, Szemenyei, Viktor, Thomsen, Elliot R., Tieu, Michael, Torkelson, Amy, Trinh, Jessica, Tung, Herman, Wakeman, Wayne, Waleboer, Femke, Ward, Katelyn, Wilbers, René, Williams, Grace, Yao, Zizhen, Yoon, Jae-Geun, Anastassiou, Costas, Arkhipov, Anton, Barzo, Pal, Bernard, Amy, Cobbs, Charles, de Witt Hamer, Philip C., Ellenbogen, Richard G., Esposito, Luke, Ferreira, Manuel, Gwinn, Ryder P., Hawrylycz, Michael J., Hof, Patrick R., Idema, Sander, Jones, Allan R., Keene, C. Dirk, Ko, Andrew L., Murphy, Gabe J., Ng, Lydia, Ojemann, Jeffrey G., Patel, Anoop P., Phillips, John W., Silbergeld, Daniel L., Smith, Kimberly, Tasic, Bosiljka, Yuste, Rafael, Segev, Idan, de Kock, Christiaan P. J., Mansvelder, Huibert D., Tamas, Gabor, Zeng, Hongkui, Koch, Christof, and Lein, Ed S.

Published
2021
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20. A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation

Author

Yao, Zizhen, van Velthoven, Cindy T.J., Nguyen, Thuc Nghi, Goldy, Jeff, Sedeno-Cortes, Adriana E., Baftizadeh, Fahimeh, Bertagnolli, Darren, Casper, Tamara, Chiang, Megan, Crichton, Kirsten, Ding, Song-Lin, Fong, Olivia, Garren, Emma, Glandon, Alexandra, Gouwens, Nathan W., Gray, James, Graybuck, Lucas T., Hawrylycz, Michael J., Hirschstein, Daniel, Kroll, Matthew, Lathia, Kanan, Lee, Changkyu, Levi, Boaz, McMillen, Delissa, Mok, Stephanie, Pham, Thanh, Ren, Qingzhong, Rimorin, Christine, Shapovalova, Nadiya, Sulc, Josef, Sunkin, Susan M., Tieu, Michael, Torkelson, Amy, Tung, Herman, Ward, Katelyn, Dee, Nick, Smith, Kimberly A., Tasic, Bosiljka, and Zeng, Hongkui

Published
2021
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21. Enhancer viruses for combinatorial cell-subclass-specific labeling

Author

Graybuck, Lucas T., Daigle, Tanya L., Sedeño-Cortés, Adriana E., Walker, Miranda, Kalmbach, Brian, Lenz, Garreck H., Morin, Elyse, Nguyen, Thuc Nghi, Garren, Emma, Bendrick, Jacqueline L., Kim, Tae Kyung, Zhou, Thomas, Mortrud, Marty, Yao, Shenqin, Siverts, La’ Akea, Larsen, Rachael, Gore, Bryan B., Szelenyi, Eric R., Trader, Cameron, Balaram, Pooja, van Velthoven, Cindy T.J., Chiang, Megan, Mich, John K., Dee, Nick, Goldy, Jeff, Cetin, Ali H., Smith, Kimberly, Way, Sharon W., Esposito, Luke, Yao, Zizhen, Gradinaru, Viviana, Sunkin, Susan M., Lein, Ed, Levi, Boaz P., Ting, Jonathan T., Zeng, Hongkui, and Tasic, Bosiljka

Published
2021
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22. Alternating sources of perisomatic inhibition during behavior

Author

Dudok, Barna, Klein, Peter M., Hwaun, Ernie, Lee, Brian R., Yao, Zizhen, Fong, Olivia, Bowler, John C., Terada, Satoshi, Sparks, Fraser T., Szabo, Gergely G., Farrell, Jordan S., Berg, Jim, Daigle, Tanya L., Tasic, Bosiljka, Dimidschstein, Jordane, Fishell, Gord, Losonczy, Attila, Zeng, Hongkui, and Soltesz, Ivan

Published
2021
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23. Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells

Author

Gouwens, Nathan W., Sorensen, Staci A., Baftizadeh, Fahimeh, Budzillo, Agata, Lee, Brian R., Jarsky, Tim, Alfiler, Lauren, Baker, Katherine, Barkan, Eliza, Berry, Kyla, Bertagnolli, Darren, Bickley, Kris, Bomben, Jasmine, Braun, Thomas, Brouner, Krissy, Casper, Tamara, Crichton, Kirsten, Daigle, Tanya L., Dalley, Rachel, de Frates, Rebecca A., Dee, Nick, Desta, Tsega, Lee, Samuel Dingman, Dotson, Nadezhda, Egdorf, Tom, Ellingwood, Lauren, Enstrom, Rachel, Esposito, Luke, Farrell, Colin, Feng, David, Fong, Olivia, Gala, Rohan, Gamlin, Clare, Gary, Amanda, Glandon, Alexandra, Goldy, Jeff, Gorham, Melissa, Graybuck, Lucas, Gu, Hong, Hadley, Kristen, Hawrylycz, Michael J., Henry, Alex M., Hill, DiJon, Hupp, Madie, Kebede, Sara, Kim, Tae Kyung, Kim, Lisa, Kroll, Matthew, Lee, Changkyu, Link, Katherine E., Mallory, Matthew, Mann, Rusty, Maxwell, Michelle, McGraw, Medea, McMillen, Delissa, Mukora, Alice, Ng, Lindsay, Ng, Lydia, Ngo, Kiet, Nicovich, Philip R., Oldre, Aaron, Park, Daniel, Peng, Hanchuan, Penn, Osnat, Pham, Thanh, Pom, Alice, Popović, Zoran, Potekhina, Lydia, Rajanbabu, Ramkumar, Ransford, Shea, Reid, David, Rimorin, Christine, Robertson, Miranda, Ronellenfitch, Kara, Ruiz, Augustin, Sandman, David, Smith, Kimberly, Sulc, Josef, Sunkin, Susan M., Szafer, Aaron, Tieu, Michael, Torkelson, Amy, Trinh, Jessica, Tung, Herman, Wakeman, Wayne, Ward, Katelyn, Williams, Grace, Zhou, Zhi, Ting, Jonathan T., Arkhipov, Anton, Sümbül, Uygar, Lein, Ed S., Koch, Christof, Yao, Zizhen, Tasic, Bosiljka, Berg, Jim, Murphy, Gabe J., and Zeng, Hongkui

Published
2020
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25. Genome engineering of isogenic human ES cells to model autism disorders

Author

Martinez, Refugio A, Stein, Jason L, Krostag, Anne-Rachel F, Nelson, Angelique M, Marken, John S, Menon, Vilas, May, Ryan C, Yao, Zizhen, Kaykas, Ajamete, Geschwind, Daniel H, and Grimley, Joshua S

Subjects
Stem Cell Research - Nonembryonic - Human, Stem Cell Research - Embryonic - Human, Autism, Biotechnology, Genetics, Mental Health, Regenerative Medicine, Brain Disorders, Pediatric, Intellectual and Developmental Disabilities (IDD), Human Genome, Stem Cell Research, 5.2 Cellular and gene therapies, 1.1 Normal biological development and functioning, Underpinning research, Development of treatments and therapeutic interventions, Generic health relevance, Autistic Disorder, Binding Sites, Cell Engineering, Cell Line, Child Development Disorders, Pervasive, Deoxyribonucleases, Embryonic Stem Cells, Gene Targeting, Genome, Human, Humans, Long QT Syndrome, Models, Genetic, Recombinational DNA Repair, Software, Syndactyly, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Developmental Biology
Abstract

Isogenic pluripotent stem cells are critical tools for studying human neurological diseases by allowing one to study the effects of a mutation in a fixed genetic background. Of particular interest are the spectrum of autism disorders, some of which are monogenic such as Timothy syndrome (TS); others are multigenic such as the microdeletion and microduplication syndromes of the 16p11.2 chromosomal locus. Here, we report engineered human embryonic stem cell (hESC) lines for modeling these two disorders using locus-specific endonucleases to increase the efficiency of homology-directed repair (HDR). We developed a system to: (1) computationally identify unique transcription activator-like effector nuclease (TALEN) binding sites in the genome using a new software program, TALENSeek, (2) assemble the TALEN genes by combining golden gate cloning with modified constructs from the FLASH protocol, and (3) test the TALEN pairs in an amplification-based HDR assay that is more sensitive than the typical non-homologous end joining assay. We applied these methods to identify, construct, and test TALENs that were used with HDR donors in hESCs to generate an isogenic TS cell line in a scarless manner and to model the 16p11.2 copy number disorder without modifying genomic loci with high sequence similarity.

Published
2015

28. A Suite of Transgenic Driver and Reporter Mouse Lines with Enhanced Brain-Cell-Type Targeting and Functionality

Author

Daigle, Tanya L., Madisen, Linda, Hage, Travis A., Valley, Matthew T., Knoblich, Ulf, Larsen, Rylan S., Takeno, Marc M., Huang, Lawrence, Gu, Hong, Larsen, Rachael, Mills, Maya, Bosma-Moody, Alice, Siverts, La’ Akea, Walker, Miranda, Graybuck, Lucas T., Yao, Zizhen, Fong, Olivia, Nguyen, Thuc Nghi, Garren, Emma, Lenz, Garreck H., Chavarha, Mariya, Pendergraft, Julie, Harrington, James, Hirokawa, Karla E., Harris, Julie A., Nicovich, Philip R., McGraw, Medea J., Ollerenshaw, Douglas R., Smith, Kimberly A., Baker, Christopher A., Ting, Jonathan T., Sunkin, Susan M., Lecoq, Jérôme, Lin, Michael Z., Boyden, Edward S., Murphy, Gabe J., da Costa, Nuno M., Waters, Jack, Li, Lu, Tasic, Bosiljka, and Zeng, Hongkui

Published
2018
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29. 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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30. Fundamental differences in promoter CpG island DNA hypermethylation between human cancer and genetically engineered mouse models of cancer

Author

Diede, Scott J, Yao, Zizhen, Keyes, C Chip, Tyler, Ashlee E, Dey, Joyoti, Hackett, Christopher S, Elsaesser, Katrina, Kemp, Christopher J, Neiman, Paul E, Weiss, William A, Olson, James M, and Tapscott, Stephen J

Subjects
Cancer, Human Genome, Pediatric, Brain Cancer, Rare Diseases, Breast Cancer, Brain Disorders, Genetics, Hematology, 2.1 Biological and endogenous factors, Aetiology, Animals, Breast Neoplasms, Burkitt Lymphoma, Cerebellar Neoplasms, CpG Islands, DNA Methylation, Female, Humans, Medulloblastoma, Mice, Mice, Transgenic, Neoplasms, Neoplasms, Experimental, Promoter Regions, Genetic, cancer, DNA methylation, epigenomics, genetically engineered mouse models, medulloblastoma, Biochemistry and Cell Biology, Medical Biochemistry and Metabolomics, Developmental Biology
Abstract

Genetic and epigenetic alterations are essential for the initiation and progression of human cancer. We previously reported that primary human medulloblastomas showed extensive cancer-specific CpG island DNA hypermethylation in critical developmental pathways. To determine whether genetically engineered mouse models (GEMMs) of medulloblastoma have comparable epigenetic changes, we assessed genome-wide DNA methylation in three mouse models of medulloblastoma. In contrast to human samples, very few loci with cancer-specific DNA hypermethylation were detected, and in almost all cases the degree of methylation was relatively modest compared with the dense hypermethylation in the human cancers. To determine if this finding was common to other GEMMs, we examined a Burkitt lymphoma and breast cancer model and did not detect promoter CpG island DNA hypermethylation, suggesting that human cancers and at least some GEMMs are fundamentally different with respect to this epigenetic modification. These findings provide an opportunity to both better understand the mechanism of aberrant DNA methylation in human cancer and construct better GEMMs to serve as preclinical platforms for therapy development.

Published
2013

31. Author Correction: Human neocortical expansion involves glutamatergic neuron diversification

Author

Berg, Jim, Sorensen, Staci A., Ting, Jonathan T., Miller, Jeremy A., Chartrand, Thomas, Buchin, Anatoly, Bakken, Trygve E., Budzillo, Agata, Dee, Nick, Ding, Song-Lin, Gouwens, Nathan W., Hodge, Rebecca D., Kalmbach, Brian, Lee, Changkyu, Lee, Brian R., Alfiler, Lauren, Baker, Katherine, Barkan, Eliza, Beller, Allison, Berry, Kyla, Bertagnolli, Darren, Bickley, Kris, Bomben, Jasmine, Braun, Thomas, Brouner, Krissy, Casper, Tamara, Chong, Peter, Crichton, Kirsten, Dalley, Rachel, de Frates, Rebecca, Desta, Tsega, Lee, Samuel Dingman, D’Orazi, Florence, Dotson, Nadezhda, Egdorf, Tom, Enstrom, Rachel, Farrell, Colin, Feng, David, Fong, Olivia, Furdan, Szabina, Galakhova, Anna A., Gamlin, Clare, Gary, Amanda, Glandon, Alexandra, Goldy, Jeff, Gorham, Melissa, Goriounova, Natalia A., Gratiy, Sergey, Graybuck, Lucas, Gu, Hong, Hadley, Kristen, Hansen, Nathan, Heistek, Tim S., Henry, Alex M., Heyer, Djai B., Hill, DiJon, Hill, Chris, Hupp, Madie, Jarsky, Tim, Kebede, Sara, Keene, Lisa, Kim, Lisa, Kim, Mean-Hwan, Kroll, Matthew, Latimer, Caitlin, Levi, Boaz P., Link, Katherine E., Mallory, Matthew, Mann, Rusty, Marshall, Desiree, Maxwell, Michelle, McGraw, Medea, McMillen, Delissa, Melief, Erica, Mertens, Eline J., Mezei, Leona, Mihut, Norbert, Mok, Stephanie, Molnar, Gabor, Mukora, Alice, Ng, Lindsay, Ngo, Kiet, Nicovich, Philip R., Nyhus, Julie, Olah, Gaspar, Oldre, Aaron, Omstead, Victoria, Ozsvar, Attila, Park, Daniel, Peng, Hanchuan, Pham, Trangthanh, Pom, Christina A., Potekhina, Lydia, Rajanbabu, Ramkumar, Ransford, Shea, Reid, David, Rimorin, Christine, Ruiz, Augustin, Sandman, David, Sulc, Josef, Sunkin, Susan M., Szafer, Aaron, Szemenyei, Viktor, Thomsen, Elliot R., Tieu, Michael, Torkelson, Amy, Trinh, Jessica, Tung, Herman, Wakeman, Wayne, Waleboer, Femke, Ward, Katelyn, Wilbers, René, Williams, Grace, Yao, Zizhen, Yoon, Jae-Geun, Anastassiou, Costas, Arkhipov, Anton, Barzo, Pal, Bernard, Amy, Cobbs, Charles, de Witt Hamer, Philip C., Ellenbogen, Richard G., Esposito, Luke, Ferreira, Manuel, Gwinn, Ryder P., Hawrylycz, Michael J., Hof, Patrick R., Idema, Sander, Jones, Allan R., Keene, C. Dirk, Ko, Andrew L., Murphy, Gabe J., Ng, Lydia, Ojemann, Jeffrey G., Patel, Anoop P., Phillips, John W., Silbergeld, Daniel L., Smith, Kimberly, Tasic, Bosiljka, Yuste, Rafael, Segev, Idan, de Kock, Christiaan P. J., Mansvelder, Huibert D., Tamas, Gabor, Zeng, Hongkui, Koch, Christof, and Lein, Ed S.

Published
2022
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32. Single-Cell Profiling of an In Vitro Model of Human Interneuron Development Reveals Temporal Dynamics of Cell Type Production and Maturation

Author

Close, Jennie L., Yao, Zizhen, Levi, Boaz P., Miller, Jeremy A., Bakken, Trygve E., Menon, Vilas, Ting, Jonathan T., Wall, Abigail, Krostag, Anne-Rachel, Thomsen, Elliot R., Nelson, Angel M., Mich, John K., Hodge, Rebecca D., Shehata, Soraya I., Glass, Ian A., Bort, Susan, Shapovalova, Nadiya V., Ngo, N. Kiet, Grimley, Joshua S., Phillips, John W., Thompson, Carol L., Ramanathan, Sharad, and Lein, Ed

Published
2017
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33. A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development

Author

Yao, Zizhen, Mich, John K., Ku, Sherman, Menon, Vilas, Krostag, Anne-Rachel, Martinez, Refugio A., Furchtgott, Leon, Mulholland, Heather, Bort, Susan, Fuqua, Margaret A., Gregor, Ben W., Hodge, Rebecca D., Jayabalu, Anu, May, Ryan C., Melton, Samuel, Nelson, Angelique M., Ngo, N. Kiet, Shapovalova, Nadiya V., Shehata, Soraya I., Smith, Michael W., Tait, Leah J., Thompson, Carol L., Thomsen, Elliot R., Ye, Chaoyang, Glass, Ian A., Kaykas, Ajamete, Yao, Shuyuan, Phillips, John W., Grimley, Joshua S., Levi, Boaz P., Wang, Yanling, and Ramanathan, Sharad

Published
2017
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34. Shared and distinct transcriptomic cell types across neocortical areas

Author

Tasic, Bosiljka, Yao, Zizhen, Graybuck, Lucas T., Smith, Kimberly A., Nguyen, Thuc Nghi, Bertagnolli, Darren, and Goldy, Jeff

Subjects
Brain cells -- Research, Neocortex -- Research, RNA sequencing -- Usage, Neurophysiology, GABA, Brain, Neurons, RNA, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA ([gamma]-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex. Single-cell transcriptomics of more than 20,000 cells from two functionally distinct areas of the mouse neocortex identifies 133 transcriptomic types, and provides a foundation for understanding the diversity of cortical cell types., Author(s): Bosiljka Tasic [sup.1] , Zizhen Yao [sup.1] , Lucas T. Graybuck [sup.1] , Kimberly A. Smith [sup.1] , Thuc Nghi Nguyen [sup.1] , Darren Bertagnolli [sup.1] , Jeff Goldy [...]

Published
2018
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37. Morphoelectric and transcriptomic divergence of the layer 1 interneuron repertoire in human versus mouse neocortex

Author

Chartrand, Thomas, Dalley, Rachel, Close, Jennie, Goriounova, Natalia A., Lee, Brian R., Mann, Rusty, Miller, Jeremy A., Molnar, Gabor, Mukora, Alice, Alfiler, Lauren, Baker, Katherine, Bakken, Trygve E., Berg, Jim, Bertagnolli, Darren, Braun, Thomas, Brouner, Krissy, Casper, Tamara, Csajbok, Eva Adrienn, Dee, Nick, Egdorf, Tom, Enstrom, Rachel, Galakhova, Anna A., Gary, Amanda, Gelfand, Emily, Goldy, Jeff, Hadley, Kristen, Heistek, Tim S., Hill, Di Jon, Jorstad, Nik, Kim, Lisa, Kocsis, Agnes Katalin, Kruse, Lauren, Kunst, Michael, Leon, Gabriela, Long, Brian, Mallory, Matthew, McGraw, Medea, McMillen, Delissa, Melief, Erica J., Mihut, Norbert, Ng, Lindsay, Nyhus, Julie, Oláh, Gáspár, Ozsvár, Attila, Omstead, Victoria, Peterfi, Zoltan, Pom, Alice, Potekhina, Lydia, Rajanbabu, Ramkumar, Rozsa, Marton, Ruiz, Augustin, Sandle, Joanna, Sunkin, Susan M., Szots, Ildiko, Tieu, Michael, Toth, Martin, Trinh, Jessica, Vargas, Sara, Vumbaco, David, Williams, Grace, Wilson, Julia, Yao, Zizhen, Barzo, Pal, Cobbs, Charles, Ellenbogen, Richard G., Esposito, Luke, Ferreira, Manuel, Gouwens, Nathan W., Grannan, Benjamin, Gwinn, Ryder P., Hauptman, Jason S., Jarsky, Tim, Keene, C. Dirk, Ko, Andrew L., Koch, Christof, Ojemann, Jeffrey G., Patel, Anoop, Ruzevick, Jacob, Silbergeld, Daniel L., Smith, Kimberly, Sorensen, Staci A., Tasic, Bosiljka, Ting, Jonathan T., Waters, Jack, de Kock, Christiaan P.J., Mansvelder, Huib D., Tamas, Gabor, Zeng, Hongkui, Kalmbach, Brian, Lein, Ed S., Chartrand, Thomas, Dalley, Rachel, Close, Jennie, Goriounova, Natalia A., Lee, Brian R., Mann, Rusty, Miller, Jeremy A., Molnar, Gabor, Mukora, Alice, Alfiler, Lauren, Baker, Katherine, Bakken, Trygve E., Berg, Jim, Bertagnolli, Darren, Braun, Thomas, Brouner, Krissy, Casper, Tamara, Csajbok, Eva Adrienn, Dee, Nick, Egdorf, Tom, Enstrom, Rachel, Galakhova, Anna A., Gary, Amanda, Gelfand, Emily, Goldy, Jeff, Hadley, Kristen, Heistek, Tim S., Hill, Di Jon, Jorstad, Nik, Kim, Lisa, Kocsis, Agnes Katalin, Kruse, Lauren, Kunst, Michael, Leon, Gabriela, Long, Brian, Mallory, Matthew, McGraw, Medea, McMillen, Delissa, Melief, Erica J., Mihut, Norbert, Ng, Lindsay, Nyhus, Julie, Oláh, Gáspár, Ozsvár, Attila, Omstead, Victoria, Peterfi, Zoltan, Pom, Alice, Potekhina, Lydia, Rajanbabu, Ramkumar, Rozsa, Marton, Ruiz, Augustin, Sandle, Joanna, Sunkin, Susan M., Szots, Ildiko, Tieu, Michael, Toth, Martin, Trinh, Jessica, Vargas, Sara, Vumbaco, David, Williams, Grace, Wilson, Julia, Yao, Zizhen, Barzo, Pal, Cobbs, Charles, Ellenbogen, Richard G., Esposito, Luke, Ferreira, Manuel, Gouwens, Nathan W., Grannan, Benjamin, Gwinn, Ryder P., Hauptman, Jason S., Jarsky, Tim, Keene, C. Dirk, Ko, Andrew L., Koch, Christof, Ojemann, Jeffrey G., Patel, Anoop, Ruzevick, Jacob, Silbergeld, Daniel L., Smith, Kimberly, Sorensen, Staci A., Tasic, Bosiljka, Ting, Jonathan T., Waters, Jack, de Kock, Christiaan P.J., Mansvelder, Huib D., Tamas, Gabor, Zeng, Hongkui, Kalmbach, Brian, and Lein, Ed S.

Abstract

Neocortical layer 1 (L1) is a site of convergence between pyramidal-neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neurons with extensive L1 branching, but whether L1 interneurons are similarly diverse is underexplored. Using Patch-seq recordings from human neurosurgical tissue, we identified four transcriptomic subclasses with mouse L1 homologs, along with distinct subtypes and types unmatched in mouse L1. Subclass and subtype comparisons showed stronger transcriptomic differences in human L1 and were correlated with strong morphoelectric variability along dimensions distinct from mouse L1 variability. Accompanied by greater layer thickness and other cytoarchitecture changes, these findings suggest that L1 has diverged in evolution, reflecting the demands of regulating the expanded human neocortical circuit.

Published
2023
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39. A Suite of Transgenic Driver and Reporter Mouse Lines with Enhanced Brain-Cell-Type Targeting and Functionality

Author

Daigle, Tanya L., Madisen, Linda, Hage, Travis A., Valley, Matthew T., Knoblich, Ulf, Larsen, Rylan S., Takeno, Marc M., Huang, Lawrence, Gu, Hong, Larsen, Rachael, Mills, Maya, Bosma-Moody, Alice, Siverts, La’ Akea, Walker, Miranda, Graybuck, Lucas T., Yao, Zizhen, Fong, Olivia, Nguyen, Thuc Nghi, Garren, Emma, Lenz, Garreck H., Chavarha, Mariya, Pendergraft, Julie, Harrington, James, Hirokawa, Karla E., Harris, Julie A., Nicovich, Philip R., McGraw, Medea J., Ollerenshaw, Douglas R., Smith, Kimberly A., Baker, Christopher A., Ting, Jonathan T., Sunkin, Susan M., Lecoq, Jérôme, Lin, Michael Z., Boyden, Edward S., Murphy, Gabe J., da Costa, Nuno M., Waters, Jack, Li, Lu, Tasic, Bosiljka, Zeng, Hongkui, Daigle, Tanya L., Madisen, Linda, Hage, Travis A., Valley, Matthew T., Knoblich, Ulf, Larsen, Rylan S., Takeno, Marc M., Huang, Lawrence, Gu, Hong, Larsen, Rachael, Mills, Maya, Bosma-Moody, Alice, Siverts, La’ Akea, Walker, Miranda, Graybuck, Lucas T., Yao, Zizhen, Fong, Olivia, Nguyen, Thuc Nghi, Garren, Emma, Lenz, Garreck H., Chavarha, Mariya, Pendergraft, Julie, Harrington, James, Hirokawa, Karla E., Harris, Julie A., Nicovich, Philip R., McGraw, Medea J., Ollerenshaw, Douglas R., Smith, Kimberly A., Baker, Christopher A., Ting, Jonathan T., Sunkin, Susan M., Lecoq, Jérôme, Lin, Michael Z., Boyden, Edward S., Murphy, Gabe J., da Costa, Nuno M., Waters, Jack, Li, Lu, Tasic, Bosiljka, and Zeng, Hongkui

Abstract

An expanded toolkit of transgenic mouse lines for exploring the organization, function, and development of mammalian neural circuits.

Published
2022

40. 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

43. Author Correction:Human neocortical expansion involves glutamatergic neuron diversification (Nature, (2021), 598, 7879, (151-158), 10.1038/s41586-021-03813-8)

Author

Berg, Jim, Sorensen, Staci A., Ting, Jonathan T., Miller, Jeremy A., Chartrand, Thomas, Buchin, Anatoly, Bakken, Trygve E., Budzillo, Agata, Dee, Nick, Ding, Song-Lin, Gouwens, Nathan W., Hodge, Rebecca D., Kalmbach, Brian, Lee, Changkyu, Lee, Brian R., Alfiler, Lauren, Baker, Katherine, Barkan, Eliza, Beller, Allison, Berry, Kyla, Bertagnolli, Darren, Bickley, Kris, Bomben, Jasmine, Braun, Thomas, Brouner, Krissy, Casper, Tamara, Chong, Peter, Crichton, Kirsten, Dalley, Rachel, de Frates, Rebecca, Desta, Tsega, Lee, Samuel Dingman, D’Orazi, Florence, Dotson, Nadezhda, Egdorf, Tom, Enstrom, Rachel, Farrell, Colin, Feng, David, Fong, Olivia, Furdan, Szabina, Galakhova, Anna A., Gamlin, Clare, Gary, Amanda, Glandon, Alexandra, Goldy, Jeff, Gorham, Melissa, Goriounova, Natalia A., Gratiy, Sergey, Graybuck, Lucas, Gu, Hong, Hadley, Kristen, Hansen, Nathan, Heistek, Tim S., Henry, Alex M., Heyer, Djai B., Hill, DiJon, Hill, Chris, Hupp, Madie, Jarsky, Tim, Kebede, Sara, Keene, Lisa, Kim, Lisa, Kim, Mean-Hwan, Kroll, Matthew, Latimer, Caitlin, Levi, Boaz P., Link, Katherine E., Mallory, Matthew, Mann, Rusty, Marshall, Desiree, Maxwell, Michelle, McGraw, Medea, McMillen, Delissa, Melief, Erica, Mertens, Eline J., Mezei, Leona, Mihut, Norbert, Mok, Stephanie, Molnar, Gabor, Mukora, Alice, Ng, Lindsay, Ngo, Kiet, Nicovich, Philip R., Nyhus, Julie, Olah, Gaspar, Oldre, Aaron, Omstead, Victoria, Ozsvar, Attila, Park, Daniel, Peng, Hanchuan, Pham, Trangthanh, Pom, Christina A., Potekhina, Lydia, Rajanbabu, Ramkumar, Ransford, Shea, Reid, David, Rimorin, Christine, Ruiz, Augustin, Sandman, David, Sulc, Josef, Sunkin, Susan M., Szafer, Aaron, Szemenyei, Viktor, Thomsen, Elliot R., Tieu, Michael, Torkelson, Amy, Trinh, Jessica, Tung, Herman, Wakeman, Wayne, Waleboer, Femke, Ward, Katelyn, Wilbers, René, Williams, Grace, Yao, Zizhen, Yoon, Jae-Geun, Anastassiou, Costas, Arkhipov, Anton, Barzo, Pal, Bernard, Amy, Cobbs, Charles, de Witt Hamer, Philip C., Ellenbogen, Richard G., Esposito, Luke, Ferreira, Manuel, Gwinn, Ryder P., Hawrylycz, Michael J., Hof, Patrick R., Idema, Sander, Jones, Allan R., Keene, C. Dirk, Ko, Andrew L., Murphy, Gabe J., Ng, Lydia, Ojemann, Jeffrey G., Patel, Anoop P., Phillips, John W., Silbergeld, Daniel L., Smith, Kimberly, Tasic, Bosiljka, Yuste, Rafael, Segev, Idan, de Kock, Christiaan P. J., Mansvelder, Huibert D., Tamas, Gabor, Zeng, Hongkui, Koch, Christof, and Lein, Ed S.

Abstract

In the version of this Article initially published, the Acknowledgements statement contained an error. Originally appearing with thanks for support given in part as follows, “R01EY023173 from The National Eye Institute, U01MH105982 from the National Institute of Mental Health and Eunice Kennedy Shriver National Institute of Child Health and Human Development, and R011EY023173 from The National Institute of Allergy and Infectious Disease,” the last number (R011EY023173) was mistakenly added and is not in fact a grant or one provided by the NIAID. The mention has been removed. The changes have been made to the online version of the Article.

Published
2022
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45. 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

48. Single-cell and single-nucleus RNA-seq uncovers shared and distinct axes of variation in dorsal LGN neurons in mice, non-human primates, and humans

Author

Bakken, Trygve E, primary, van Velthoven, Cindy TJ, additional, Menon, Vilas, additional, Hodge, Rebecca D, additional, Yao, Zizhen, additional, Nguyen, Thuc Nghi, additional, Graybuck, Lucas T, additional, Horwitz, Gregory D, additional, Bertagnolli, Darren, additional, Goldy, Jeff, additional, Yanny, Anna Marie, additional, Garren, Emma, additional, Parry, Sheana, additional, Casper, Tamara, additional, Shehata, Soraya I, additional, Barkan, Eliza R, additional, Szafer, Aaron, additional, Levi, Boaz P, additional, Dee, Nick, additional, Smith, Kimberly A, additional, Sunkin, Susan M, additional, Bernard, Amy, additional, Phillips, John, additional, Hawrylycz, Michael J, additional, Koch, Christof, additional, Murphy, Gabe J, additional, Lein, Ed, additional, Zeng, Hongkui, additional, and Tasic, Bosiljka, additional

Published
2021
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