A multimodal atlas of human brain cell types
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PROVIDER: PRJNA525917 | ENA |
REPOSITORIES: ENA
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Project description:A multimodal atlas of human brain cell types
| PRJNA525918 | ENA
Project description:<p>"A multimodal atlas of human brain cell types" includes sample data targeting two cell types that show species differences between mouse and human. First, it includes a detailed transcriptomic, morphological, and electrophysiological characterization of cell types in layer 1 of human middle temporal gyrus, focusing primarily on different inhibitory cell types. This project also includes gene expression data collected from nuclei in layer 5 of human fronto-insula, with a goal of identifying transcriptomic signatures of Von Economo neurons. Control samples collected as part of the same experiment are also included in the data set.</p> <p>This study was conducted as part of a collaboration between the Allen Institute for Brain Science, the University of Szeged, and the J. Craig Venter Institute. Collaborators request that publications resulting from these data cite their original publication: Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type (PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30150662" target="_blank">30150662</a>).</p>
| phs001791 | dbGaP
Project description:A multimodal atlas of human brain cell types_2021 data
| PRJNA781341 | ENA
Project description:A multimodal atlas of human brain cell types_2021 data
| PRJNA816970 | ENA
Project description:The mammalian brain consists of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled (~4.0 million cells passing quality control), and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into four nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters. We present a newly developed online platform, Allen Brain Cell (ABC) Atlas, to visualize the mouse whole brain cell type taxonomy and atlas along with the scRNA-seq and MERFISH data and metadata sets. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate myriad modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cellular and circuit function, development, and evolution of the mammalian brain.
2023-11-14 | GSE246717 | GEO
Project description:BrainSpan Atlas of the Human Brain
| PRJNA251912 | ENA
Project description:Melanoma Brain Metastasis Atlas
| PRJNA768859 | ENA
Project description:The diversity of cell types and regulatory states in the brain, and how these change during ageing, remains largely unknown. We present a single-cell transcriptome atlas of the entire adult Drosophila melanogaster brain sampled across its lifespan. Cell clustering identified 87 initial cell clusters that are further subclustered and validated by targeted cell-sorting. Our data shows high granularity and identifies a wide range of cell types. Gene network analyses using SCENIC revealed regulatory heterogeneity linked to energy consumption. During ageing, RNA content declines exponentially without affecting neuronal identity in old brains. This single-cell brain atlas covers nearly all cells in the normal brain and provides the tools to study cellular diversity alongside other Drosophila and mammalian single-cell datasets in our unique single-cell analysis platform. These results allow comprehensive exploration of all transcriptional states of an entire ageing brain.
2018-06-13 | GSE107451 | GEO
Project description:The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity.
2021-01-15 | GSE164378 | GEO
Project description:A comparative atlas of single-cell chromatin accessibility in the human brainRecent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (ATAC-seq), we explored open chromatin landscapes across 1.1 million cells in 42 brain regions from three adults. Integrating this data unveiled 107 distinct cell types and their specific utilization of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly a third of the cCREs demonstrated conservation and chromatin accessibility in the mouse brain cells. We reveal strong links between specific brain cell types and neuropsychiatric disorders including schizophrenia, bipolar disorder, Alzheimer’s disease (AD), and major depression, and have developed deep learning models to predict the regulatory roles of noncoding risk variants in these disorders.
2023-10-04 | GSE244618 | GEO