A Guide to the Brain Initiative Cell Census Network Data Ecosystem

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

Cellular anatomy of the mouse primary motor cortex.

An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input-output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture

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

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) 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. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

Derivation of the Spatial Distribution of Free Water Storage Capacity Based on Topographic Index

Free water storage capacity, an important characteristic of land surface related to runoff process, has a significant influence on runoff generation and separation. It is thus necessary to derive reasonable spatial distribution of free water storage capacity for rainfall-runoff simulation, especially in distributed modeling. In this paper, a topographic index based approach is proposed for the derivation of free water storage capacity spatial distribution. The topographic index, which can be obtained from digital elevation model (DEM), are used to establish a functional relationship with free water storage capacity in the proposed approach. In this case, the spatial variability of free water storage capacity can be directly estimated from the characteristics of watershed topography. This approach was tested at two medium sized watersheds, including Changhua and Chenhe, with the drainage areas of 905 km2 and 1395 km2, respectively. The results show that locations with larger values of free water storage capacity generally correspond to locations with higher topographic index values, such as riparian region. The estimated spatial distribution of free water storage capacity is also used in a distributed, grid-based Xinanjiang model to simulate 10 flood events for Chenhe Watershed and 17 flood events for Changhua Watershed. Our analysis indicates that the proposed approach based on topographic index can produce reasonable spatial variability of free water storage capacity and is more suitable for flood simulation

Evaluation of Reference Genes Suitable for Gene Expression during Root Enlargement in Cherry Radish Based on Transcriptomic Data

Reliable reference genes (RGs) are of great significance for the normalization of quantitative data. RGs are often used as a reference to ensure the accuracy of experimental results to detect gene expression levels by reverse transcription–quantitative real-time PCR (RT-qPCR). To evaluate the normalized RGs that are suitable for studying the expression of genes during the process of radish stele enlargement, based on the functional annotations and fragment per kilobase of transcript per million mapped reads (FPKM) values in the transcriptome data, three traditional RGs (GAPDH, 18SrRNA, and ACTIN7) and seven commonly used RGs (UBQ11, TUA6, TUB6, EF-1b1, EF-1a2, PP2A11, and SAND) were obtained. In the study, the results of geNorm, NormFinder, and BestKeeper from RefFinder comprehensively analyzed the stability ranking of candidate RGs. The results showed that compared with the traditional RGs, the common RGs show higher and more stable expression. Among the seven commonly used RGs, PP2A11 is recommended as the optimal RG for studying cherry radish stele enlargement. This research provides a useful and reliable RG resource for the accurate study of gene expression during root enlargement in cherry radishes and facilitates the functional genomics research on root enlargement

Extracellular biosynthesis of monodispersed gold nanoparticles by a SAM capping route

Monodispersed gold nanoparticles capped with a self-assembled monolayer of dodecanethiol were biosynthesized extracellularly by an efficient, simple, and environmental friendly procedure, which involved the use of Bacillus megatherium D01 as the reducing agent and the use of dodecanethiol as the capping ligand at 26 A degrees C. The kinetics of gold nanoparticle formation was followed by transmission electron microscope (TEM) and UV-vis spectroscopy. It was shown that reaction time was an important parameter in controlling the morphology of gold nanoparticles. The effect of thiol on the shape, size, and dispersity of gold nanoparticles was also studied. The results showed that the presence of thiol during the biosynthesis could induce the formation of small size gold nanoparticles (< 2.5 nm), hold the shape of spherical nanoparticles, and promote the monodispersity of nanoparticles. Through the modulation of reaction time and the use of thiol, monodispersed spherical gold nanoparticles capped with thiol of 1.9 +/- A 0.8 nm size were formed by using Bacillus megatherium D01.National Natural Science Foundation of China [20433040, 20423002]; State Key Laboratory for Physical Chemistry of the Solid Surface, Xiamen University of China [200408

A guide to the BRAIN Initiative Cell Census Network data ecosystem

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

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

none258Here 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.openCallaway, 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, SusanCallaway, 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, Susa