Funded Awards

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Title Investigator Institute Fiscal Year FOA Number Status Project Number Priority Area Summary
CENTER FOR EPIGENOMICS OF THE MOUSE BRAIN ATLAS (CEMBA) Ecker, Joseph R Salk Institute For Biological Studies 2017 Active
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Dr. Ecker's group will use signatures of epigenetics, the switching on-and-off of genes in response to experience, in mouse frontal cortex to help identify different classes of cells and understand their function.

A Cellular Resolution Census of the Developing Human Brain Huang, Eric J Kriegstein, Arnold (contact) University Of California, San Francisco 2017 Active
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  • Human Neuroscience
Scientists have yet to achieve high-resolution classification of the billions of neurons and non-neuronal cells in the human brain. To attempt this feat, Arnold Kriegstein and Eric Huang will perform high-throughput, droplet-based single-cell RNA and transposase-accessible chromatin sequencing techniques to collect genetic and epigenetic information from individual cells, which will be sampled from multiple regions of post-mortem human brains that are developmentally between early gestation and adolescence. They will further classify living neurons cultured from select brain regions based on their calcium imaging responses to various chemical stimuli. Finally, they plan to use multiplexed single-molecule fluorescent in situ hybridization (smFISH) to identify the spatial distribution of these various cell types in the brain. After these data are compiled, we will have the most detailed picture to date of genetically and functionally defined cell types in the human brain throughout development.
A Community Resource for Single Cell Data in the Brain Gee, James C Hawrylycz, Michael (contact) Martone, Maryann E Ng, Lydia Lup-ming Philippakis, Anthony Allen Institute 2017 Active
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One major technical challenge for the BRAIN Initiative is the storage and dissemination of large amounts of data collected by different project teams. Hawrylycz and colleagues will support the cell census efforts of the BRAIN Initiative by hosting the BRAIN Cell Data Center (BCDC). Through the BCDC, they will store single-cell data on genetics, histology, electrophysiology, morphology, anatomical location, and synaptic connections from multiple species in a standardized manner. They will also develop and provide training for web-based tools to ease data visualization and analysis efforts. This will facilitate the integration of multiple data streams to better identify and characterize the different cell types in the brain.
A Comprehensive Center for Mouse Brain Cell Atlas Huang, Z Josh Cold Spring Harbor Laboratory 2017 Complete
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Identifying individual cell types in the brain is a monumental task that is complicated by the limitations of current molecular technologies. To measure genetic diversity in the whole mouse brain, Huang and Arlotta will lead a team using next-generation droplet-based single-cell transcriptome sequencing along with other highly sensitive single-cell techniques that allow for high-throughput data collection. They plan to map these data onto the spatial locations of forebrain neurons with the help of high-resolution microscopy and genetically driven cell markers. These efforts will provide the scientific community with unprecedented detail about neurons’ molecular and spatial characteristics that can be used to develop additional tools for cell-specific manipulations.

A comprehensive whole-brain atlas of cell types in the mouse Zeng, Hongkui Allen Institute 2017 Complete
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The large number of cells in the brain and the complexity of their molecular and functional characteristics make it difficult to define individual cell types. Zeng and colleagues plan to complement high throughput droplet-based transcriptome survey with deep sequencing technique and multiplexed error-robust fluorescence in situ hybridization (MERFISH) to comprehensively characterize gene expression information from anatomically mapped cells across the entire mouse brain. Additionally, they will use patch clamp method to measure neuronal function in specific brain regions, and combine electrophysiological with transcriptomic and morphological information to provide integrative profiles of individual cell types. These efforts will refine how we define cell types and will produce a census of individual cells in the mouse brain that can then be targeted for further study.

A Molecular and Cellular Atlas of the Marmoset Brain Feng, Guoping Massachusetts Institute Of Technology 2017 Active
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  • Human Neuroscience
Although rodents are a highly accessible model and relatively simple to use for genetic studies, it is unclear whether the cell types found in rodent brains match those of primates. To help fill the evolutionary gap in knowledge between rodents and humans, Feng will lead a team to classify cells across the marmoset brain. They will use high-throughput single-cell RNA sequencing to identify cell types in the prefrontal cortex, striatum, and thalamus and will then spatially map the cell types they find in the brain using multiplexed error-robust in situ hybridization (MERFISH). By combining MERFISH with viral expression of marker proteins in subsets of neurons, the team will also correlate cell morphology with genetic information. Altogether these efforts will produce a census of cell types in the marmoset brain, which will be valuable information for future work into the genetics and circuits of the primate brain.
A multimodal atlas of human brain cell types Lein, Ed Allen Institute 2017 Active
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  • Human Neuroscience
Because of technical limitations, most studies identifying individual cell types in the brain have focused on animal models rather than on human tissue, despite a lack of knowledge about how cell types differ between species. Ed Lein and colleagues will perform broad, high-throughput single-cell RNA sequencing techniques across the whole human brain and spinal cord, along with deep sequencing of single cells in select regions of adult post-mortem brain. They will then determine the spatial distribution of various cell types identified through these sequencing experiments by using multiplexed single-molecule fluorescent in situ hybridization (smFISH). To integrate information about neuronal function into their classifications, the team will make combined electrophysiology, morphology, and transcriptome measurements from single cells in adult human cortex obtained via live surgical resection. These efforts will lead to a much deeper understanding about the differences between cell types in the adult human brain and will facilitate future collaborations between researchers to compare cell types across species.
Anatomical characterization of neuronal cell types of the mouse brain Ascoli, Giorgio A Dong, Hong-wei (contact) Lim, Byungkook University Of Southern California 2017 Active
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Better anatomical characterization of neurons is needed if we want to identify and distinguish the different cell types in the brain. Dong and colleagues plan to classify neurons based on their spatial anatomy, connections with other neurons, and morphology using multiple neuronal retro- and anterograde tracing methods that will identify connected neurons. This team will first focus on 300 well-defined regions within the limbic system of the adult mouse, a circuit that is important for homeostasis and behavioral motivation, taking high-resolution images and creating high-throughput, three-dimensional reconstructions of these neurons. These data will provide a more complete anatomical picture of the limbic system, and this method can be applied in the future to study additional circuits throughout the brain.
Cell atlas of mouse brain-spinal cord connectome Dong, Hong-wei Tao, Huizhong Whit Zhang, Li I (contact) University Of Southern California 2018 Active
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Systematic studies on the brain-spinal cord connectome are lacking despite great efforts to characterize neuronal cell types in the brain. Zhang’s multi- laboratories project aims to systematically characterize neuronal types in the mouse spinal cord based on their anatomy, connectivity, neuronal morphologies, molecular identities, and electrophysiological properties. Via multiple newly-developed techniques, including an anterograde/retrograde trans-synaptic tagging method to label neurons, gene expression bard coding, and a fast 3D light sheet microscopy method, the team will establish a complete cell-type based brain-spinal cord connectome database, which will be made accessible to the neuroscience community.

Collaboratory for atlasing cell type anatomy in the female and male mouse brain Osten, Pavel Cold Spring Harbor Laboratory 2017 Active
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Although neuronal properties have been studied for over a century, we still have an incomplete idea of how different cell types are distributed throughout the brain. Osten and colleagues will use the automated Cell Counting and Distribution Mapping (CCDM) pipeline that they developed to express specific neuronal markers in the brains of adult mice, take high-resolution images of the neurons, and then spatially map their location. They plan to identify the distribution patterns and somato-dendritic morphology of more than 80 molecularly defined cell types. These data will provide detailed anatomical information about cell circuits that can then be integrated with molecular data to better define cell types in the brain.
Dendritome mapping of genetically-defined and sparsely-labeled cortical and striatal projection neurons Dong, Hong-wei Yang, Xiangdong William (contact) University Of California Los Angeles 2018 Active
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The precise number of neuronal cell types of about one hundred million highly-interconnected neurons in the mouse brain is unknown. Ultimately, the classification of neuronal cell types in the mammalian brain will require integrating molecular, morphological, and connectomic properties. Yang and colleagues propose to classify neuronal cell types via brain-wide comprehensive profiling of the dendritic morphology of neurons with subsequent digital reconstruction. Their transgenic mouse lines, MORF, enable sparse labeling of genetically-defined neurons in mice, which allow for the resolution and reconstruction of individual cells’ dendritic morphologies within densely populated neuronal networks. This project will help contribute to the BICCN effort to generate a reference mouse brain cell atlas, and data will be shared publicly through the BRAIN Cell Data Center.

Imaging and Analysis Techniques to Construct a Cell Census Atlas of the Human Brain Boas, David A Fischl, Bruce (contact) Massachusetts General Hospital 2018 Active
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  • Human Neuroscience

Three-dimensional human brain atlases are increasingly important for integrating complex datasets into useful community resources. Fischl’s team proposes to create a multi-scale atlas—akin to Google Earth™ for the human brain—to map hemisphere-wide networks and also zoom in to see individual, labeled cells at micron resolution. This advance will be made possible through multiple imaging technologies, including light-sheet microscopy, tissue clearing, immunohistochemistry, magnetic resonance imaging, and newly-developed techniques in Optical Coherence Tomography. The ability to probe the cellular properties and multi-scale networks of specific areas in the human brain could evolve to an automated system for visualizing across the entire human brain in health and disease.

Toward a human adult brain cell atlas with single-cell technologies Chun, Jerold Zhang, Kun (contact) University Of California, San Diego 2018 Active
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  • Human Neuroscience

Defining a complete cell atlas of the human brain, including a full molecular catalog of all its cell types and their spatial distribution, is a critical step toward understanding the human cognitive machine. Zhang’s team will expand on their previous efforts toward building a complete cell atlas of the whole human adult brain. They will systematically apply novel technologies for scalable, single-nucleus transcriptome sequencing, single-cell DNA accessibility assay, and in situ RNA imaging to MRI-scanned human brains, incorporating innovative computational approaches. If successful, the derived data will facilitate the study of molecular mechanisms underlying brain function and disorders, empowering the scientific community with a massive, readily accessible database of unprecedented scope.

Towards integrated 3D reconstruction of whole human brains at subcellular resolution Chung, Kwanghun Massachusetts Institute Of Technology 2018 Active
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  • Human Neuroscience

Dr. Chung’s team aims to build a three-dimensional proteomic atlas of cells and neural circuits of human brains. To do this, his team plans to develop indestructible and transparent hydrogel-tissue hybrids for multi-rounds of protein labeling and imaging at subcellular resolution. They will stain the tissue via a variety of cellular and molecular labeling techniques and then use automated imaging to visualize different brain cell types, nerve fibers and synapses. The team will also create a supercomputing cloud- based framework and algorithms to analyze petabytes of high-resolution image data. This three- dimensional human brain atlas could give researchers a rapid, low cost way to discover brain cell types and the circuit problems behind neurological and neuropsychiatric disorders.