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22 results on '"Niu, Sheng-Yong"'

1. Pivotal role for S-nitrosylation of DNA methyltransferase 3B in epigenetic regulation of tumorigenesis

Author

Okuda, Kosaku, Nakahara, Kengo, Ito, Akihiro, Iijima, Yuta, Nomura, Ryosuke, Kumar, Ashutosh, Fujikawa, Kana, Adachi, Kazuya, Shimada, Yuki, Fujio, Satoshi, Yamamoto, Reina, Takasugi, Nobumasa, Onuma, Kunishige, Osaki, Mitsuhiko, Okada, Futoshi, Ukegawa, Taichi, Takeuchi, Yasuo, Yasui, Norihisa, Yamashita, Atsuko, Marusawa, Hiroyuki, Matsushita, Yosuke, Katagiri, Toyomasa, Shibata, Takahiro, Uchida, Koji, Niu, Sheng-Yong, Lang, Nhi B, Nakamura, Tomohiro, Zhang, Kam YJ, Lipton, Stuart A, and Uehara, Takashi

Subjects
Biological Sciences, Medicinal and Biomolecular Chemistry, Chemical Sciences, Genetics, Cancer, Digestive Diseases, Prevention, Aetiology, 2.1 Biological and endogenous factors, Animals, Humans, Mice, Cell Transformation, Neoplastic, DNA (Cytosine-5-)-Methyltransferase 1, DNA (Cytosine-5-)-Methyltransferases, DNA Methylation, DNA Modification Methylases, Epigenesis, Genetic
Abstract

DNA methyltransferases (DNMTs) catalyze methylation at the C5 position of cytosine with S-adenosyl-L-methionine. Methylation regulates gene expression, serving a variety of physiological and pathophysiological roles. The chemical mechanisms regulating DNMT enzymatic activity, however, are not fully elucidated. Here, we show that protein S-nitrosylation of a cysteine residue in DNMT3B attenuates DNMT3B enzymatic activity and consequent aberrant upregulation of gene expression. These genes include Cyclin D2 (Ccnd2), which is required for neoplastic cell proliferation in some tumor types. In cell-based and in vivo cancer models, only DNMT3B enzymatic activity, and not DNMT1 or DNMT3A, affects Ccnd2 expression. Using structure-based virtual screening, we discovered chemical compounds that specifically inhibit S-nitrosylation without directly affecting DNMT3B enzymatic activity. The lead compound, designated DBIC, inhibits S-nitrosylation of DNMT3B at low concentrations (IC50 ≤ 100 nM). Treatment with DBIC prevents nitric oxide (NO)-induced conversion of human colonic adenoma to adenocarcinoma in vitro. Additionally, in vivo treatment with DBIC strongly attenuates tumor development in a mouse model of carcinogenesis triggered by inflammation-induced generation of NO. Our results demonstrate that de novo DNA methylation mediated by DNMT3B is regulated by NO, and DBIC protects against tumor formation by preventing aberrant S-nitrosylation of DNMT3B.

Published
2023

2. 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

3. 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

4. Epigenomic diversity of cortical projection neurons in the mouse brain

Author

Zhang, Zhuzhu, Zhou, Jingtian, Tan, Pengcheng, Pang, Yan, Rivkin, Angeline C, Kirchgessner, Megan A, Williams, Elora, Lee, Cheng-Ta, Liu, Hanqing, Franklin, Alexis D, Miyazaki, Paula Assakura, Bartlett, Anna, Aldridge, Andrew I, Vu, Minh, Boggeman, Lara, Fitzpatrick, Conor, Nery, Joseph R, Castanon, Rosa G, Rashid, Mohammad, Jacobs, Matthew W, Ito-Cole, Tony, O’Connor, Carolyn, Pinto-Duartec, António, Dominguez, Bertha, Smith, Jared B, Niu, Sheng-Yong, Lee, Kuo-Fen, Jin, Xin, Mukamel, Eran A, Behrens, M Margarita, Ecker, Joseph R, and Callaway, Edward M

Subjects
Neurosciences, Human Genome, Genetics, Brain Disorders, Underpinning research, 1.1 Normal biological development and functioning, Neurological, Animals, Brain Mapping, Cerebral Cortex, Epigenome, Epigenomics, Female, Male, Mice, Neural Pathways, Neurons, General Science & Technology
Abstract

Neuronal cell types are classically defined by their molecular properties, anatomy and functions. Although recent advances in single-cell genomics have led to high-resolution molecular characterization of cell type diversity in the brain1, neuronal cell types are often studied out of the context of their anatomical properties. To improve our understanding of the relationship between molecular and anatomical features that define cortical neurons, here we combined retrograde labelling with single-nucleus DNA methylation sequencing to link neural epigenomic properties to projections. We examined 11,827 single neocortical neurons from 63 cortico-cortical and cortico-subcortical long-distance projections. Our results showed unique epigenetic signatures of projection neurons that correspond to their laminar and regional location and projection patterns. On the basis of their epigenomes, intra-telencephalic cells that project to different cortical targets could be further distinguished, and some layer 5 neurons that project to extra-telencephalic targets (L5 ET) formed separate clusters that aligned with their axonal projections. Such separation varied between cortical areas, which suggests that there are area-specific differences in L5 ET subtypes, which were further validated by anatomical studies. Notably, a population of cortico-cortical projection neurons clustered with L5 ET rather than intra-telencephalic neurons, which suggests that a population of L5 ET cortical neurons projects to both targets. We verified the existence of these neurons by dual retrograde labelling and anterograde tracing of cortico-cortical projection neurons, which revealed axon terminals in extra-telencephalic targets including the thalamus, superior colliculus and pons. These findings highlight the power of single-cell epigenomic approaches to connect the molecular properties of neurons with their anatomical and projection properties.

Published
2021

5. 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

6. Boundary-Preserved Deep Denoising of the Stochastic Resonance Enhanced Multiphoton Images

Author

Niu, Sheng-Yong, Guo, Lun-Zhang, Li, Yue, Wang, Tzung-Dau, Tsao, Yu, and Liu, Tzu-Ming

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

As the rapid growth of high-speed and deep-tissue imaging in biomedical research, it is urgent to find a robust and effective denoising method to retain morphological features for further texture analysis and segmentation. Conventional denoising filters and models can easily suppress perturbative noises in high contrast images. However, for low photon budget multi-photon images, high detector gain will not only boost signals, but also bring huge background noises. In such stochastic resonance regime of imaging, sub-threshold signals may be detectable with the help of noises. Therefore, a denoising filter that can smartly remove noises without sacrificing the important cellular features such as cell boundaries is highly desired. In this paper, we propose a convolutional neural network based autoencoder method, Fully Convolutional Deep Denoising Autoencoder (DDAE), to improve the quality of Three-Photon Fluorescence (3PF) and Third Harmonic Generation (THG) microscopy images. The average of the acquired 200 images of a given location served as the low-noise answer for DDAE training. Compared with other widely used denoising methods, our DDAE model shows better signal-to-noise ratio (26.6 and 29.9 for 3PF and THG, respectively), structure similarity (0.86 and 0.87 for 3PF and THG, respectively), and preservation of nuclear or cellular boundaries.

Published
2019

7. 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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8. Inferring gene regulation from stochastic transcriptional variation across single cells at steady state

Author

Gupta, Anika, primary, Martin-Rufino, Jorge D., additional, Jones, Thouis R., additional, Subramanian, Vidya, additional, Qiu, Xiaojie, additional, Grody, Emanuelle I., additional, Bloemendal, Alex, additional, Weng, Chen, additional, Niu, Sheng-Yong, additional, Min, Kyung Hoi, additional, Mehta, Arnav, additional, Zhang, Kaite, additional, Siraj, Layla, additional, Al' Khafaji, Aziz, additional, Sankaran, Vijay G., additional, Raychaudhuri, Soumya, additional, Cleary, Brian, additional, Grossman, Sharon, additional, and Lander, Eric S., additional

Published
2022
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9. Inferring gene regulation from stochastic transcriptional variation across single cells at steady state

Author

Massachusetts Institute of Technology. Department of Biology, Gupta, Anika, Martin-Rufino, Jorge D, Jones, Thouis R, Subramanian, Vidya, Qiu, Xiaojie, Grody, Emanuelle I, Bloemendal, Alex, Weng, Chen, Niu, Sheng-Yong, Min, Kyung Hoi, Mehta, Arnav, Zhang, Kaite, Siraj, Layla, Al' Khafaji, Aziz, Sankaran, Vijay G, Raychaudhuri, Soumya, Cleary, Brian, Grossman, Sharon, Lander, Eric S, Massachusetts Institute of Technology. Department of Biology, Gupta, Anika, Martin-Rufino, Jorge D, Jones, Thouis R, Subramanian, Vidya, Qiu, Xiaojie, Grody, Emanuelle I, Bloemendal, Alex, Weng, Chen, Niu, Sheng-Yong, Min, Kyung Hoi, Mehta, Arnav, Zhang, Kaite, Siraj, Layla, Al' Khafaji, Aziz, Sankaran, Vijay G, Raychaudhuri, Soumya, Cleary, Brian, Grossman, Sharon, and Lander, Eric S

Abstract

Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.

Published
2022

10. 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

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 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

13. FOXR1 regulates stress response pathways and is necessary for proper brain development

Author

Mota, Andressa, primary, Waxman, Hannah K., additional, Hong, Rui, additional, Lagani, Gavin D., additional, Niu, Sheng-Yong, additional, Bertherat, Féodora L., additional, Wolfe, Lynne, additional, Malicdan, Christine May, additional, Markello, Thomas C., additional, Adams, David R., additional, Gahl, William A., additional, Cheng, Christine S., additional, Beffert, Uwe, additional, and Ho, Angela, additional

Published
2021
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14. 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

15. Forkhead box R1-mediated stress response linked to a case of human microcephaly and brain atrophy

Author

Mota, Andressa, primary, Hong, Rui, additional, Niu, Sheng-Yong, additional, Bertherat, Féodora L., additional, Wolfe, Lynne, additional, Malicdan, Christine May, additional, Markello, Thomas C., additional, Adams, David R., additional, Gahl, William A., additional, Cheng, Christine, additional, Beffert, Uwe, additional, and Ho, Angela, additional

Published
2020
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16. Epigenomic Diversity of Cortical Projection Neurons in the Mouse Brain

Author

Zhang, Zhuzhu, primary, Zhou, Jingtian, additional, Tan, Pengcheng, additional, Pang, Yan, additional, Rivkin, Angeline, additional, Kirchgessner, Megan A., additional, Williams, Elora, additional, Lee, Cheng-Ta, additional, Liu, Hanqing, additional, Franklin, Alexis D., additional, Miyazaki, Paula Assakura, additional, Bartlett, Anna, additional, Aldridge, Andrew, additional, Vu, Minh, additional, Boggeman, Lara, additional, Fitzpatrick, Conor, additional, Nery, Joseph R., additional, Castanon, Rosa G., additional, Rashid, Mohammad, additional, Jacobs, Matthew, additional, Ito, Tony, additional, Dominguez, Bertha, additional, Niu, Sheng-Yong, additional, Smith, Jared B., additional, O’Connor, Carolyn, additional, Lee, Kuo-Fen, additional, Jin, Xin, additional, Mukamel, Eran A., additional, Behrens, M. Margarita, additional, Ecker, Joseph R., additional, and Callaway, Edward M., additional

Published
2020
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17. 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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18. 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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