A guide to the BRAIN Initiative Cell Census Network data ecosystem

Author:

Hawrylycz MichaelORCID,Martone Maryann E.ORCID,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 T. J.,Wang Quanxin,Xie Fangming,Xu Hua,Yao Zizhen,Yun Zhixi,Zhang Yun Renee,Zheng W. Jim,Zingg Brian

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.

Funder

National Institute of Mental Health and Neurosciences

National Institute of Mental Health

U.S. Department of Energy

European Union’s Horizon 2020 Framework Programme

National Institute of Health

Publisher

Public Library of Science (PLoS)

Subject

General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Neuroscience

Reference70 articles.

1. The NIH BRAIN Initiative;TR Insel;Science,2013

2. The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas;JR Ecker;Neuron,2017

3. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain;Z Yao;bioRxiv,2023

4. A molecularly defined and spatially resolved cell atlas of the whole mouse brain;M Zhang;bioRxivorg,2023

5. RFA-MH-21-235: BRAIN Initiative Cell Atlas Network (BICAN): Comprehensive Center on Human and Non-human Primate Brain Cell Atlases (UM1 Clinical Trial Not Allowed) [Internet]. [cited 2022 Aug 18]. Available from: https://grants.nih.gov/grants/guide/rfa-files/RFA-MH-21-235.html.

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