Description

This spatially resolved cell atlas of the whole mouse brain provides a systematic characterization of the spatial organization of transcriptomically defined cell types across the entire adult mouses brain using in situ, single-cell transcriptomic profiling with multiplexed error-robust fluorescence in situ hybridization (MERFISH). Zhuang imaged ~9 million cells with a ~1,100-gene panel using MERFISH and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating our MERFISH data with the whole-brain single-cell RNA-sequencing (scRNA-seq) dataset generated by the Allen Institute. This allowed them to generate a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to ∼300 major cell types (subclasses), in the whole mouse brain with high molecular and spatial resolution. The cell atlas was further registered to the Allen Mouse Brain Common Coordinate Framework (CCF v3), which allows systematic quantifications of the cell composition and organization in individual brain regions as anatomically delineated in the CCF v3. This cell atlas also reveals molecularly defined brain regions characterized by distinct cell-type compositions, spatial gradients featuring gradual changes in the gene-expression profiles of cells, as well as cell-type-specific cell-cell interactions and the molecular basis and functional implications of these cell-cell interactions. Learn more...

This data accompanies the January 2025 paper Brain-wide cell-type-specific transcriptomic signatures of healthy ageing in mice published in Nature.

The Cellular and Molecular Characterization of the Aged Mouse Brain project seeks to create a foundational reference for the transcriptional and epigenomic changes that occur in the brain with normal aging. Single cell gene expression and chromatin accessibility measurements survey neuronal and non-neuronal cell classes/types across the entire mouse brain to reveal areas and cell types that are more susceptible to aging than others. This is a comprehensive single-cell RNA-sequencing (scRNA-seq) dataset containing 1.2 million high-quality single-cell transcriptomes of brain cells from aged (18mo) and young adult (2mo) mice of both sexes, from regions spanning the forebrain, midbrain, and hindbrain. Learn more...

The Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) is a consortium focused on gaining a deep molecular and cellular understanding of the early pathogenesis of Alzheimer’s Disease. SEA-AD is a collaboration of the Allen Institute for Brain Science, the University of Washington Alzheimer’s Disease Research Center, and Kaiser Permanente Washington Research Institute.

Using the ABC Atlas, users can explore the largest cell-resolution spatial transcriptomics (MERFISH) data set in human brain to date, which provides accurate spatial annotation and colocalization of cell types in the middle temporal gyrus (MTG) of 24 donors from the SEA-AD cohort. This can be viewed in parallel with the 2.78 million cells collected from MTG and dorsolateral prefrontal cortex (DFC) using single nucleus transcriptomics and multiomics (from 84 donors), and organized into a joint taxonomy to allow exploration of gene expression in the context of cell types and donor metrics. Learn more...

This dataset includes more than three million cells sampled from the adult human brain. Samples were isolated from ~100 dissections from three donors and assayed using single-nucleus RNA sequencing. The resulting cells were clustered into hierarchical groups of 31 superclusters, 461 clusters, and 3313 subclusters. Additionally, categorical neurotransmitter type annotations were assigned to clusters based on expression (or lack thereof) of one or more neurotransmitter-associated marker genes. Included in this dataset includes two tSNE plots - one plot contains approximately 900k non-neuronal cells and the other contains approximately 2.5m neuronal cells... Learn more...

The Aligning Science Across Parkinson’s (ASAP) initiative, Allen Institute, and the Michael J. Fox Foundation are teaming up to help researchers unlock deeper insights into how cell types, brain anatomy, and diseases like Parkinson’s are connected.

This initial collaboration focuses on the Human Postmortem-derived Brain Sequencing Collection (PMDBS), a harmonized repository comprised of single nucleus and PolyA RNA-seq data contributed by five ASAP CRN teams (Hafler, Lee, Jakobsson, Scherzer, Hardy). Sequencing data were uniformly aligned to the GRCh38.p13 reference genome (Gencode V32), quality control was performed and low-quality cells were filtered out. A set of highly variable genes were identified and the scVI workflow resulted in an integrated latent variable representation, 2D UMAP coordinates and a set of 30 clusters. Currently, the repository spans roughly 3 millions cells obtained from 9 brain regions and 211 donors with various pathologies (including healthy control). For more details on this dataset and to access the raw data used in its preparation, please visit the collection description on the ASAP CRN Cloud webpage. Learn more...

The Mouse Whole Brain Atlas is a high-resolution transcriptomic and spatial cell-type atlas across the entire mouse brain, integrating several whole-brain single-cell RNA-sequencing (scRNA-seq) datasets. The datasets contain a total of ~4 million cells passing rigorous quality-control (QC) criteria. The integrated transcriptomic taxonomy contains 5,322 clusters that are organized in a hierarchical manner with nested groupings of 34 classes, 338 subclasses, 1,201 supertypes and 5,322 types/clusters. The scRNA-seq data reveal transcriptome-wide gene expression and co-expression patterns for each cell type. The anatomical location of each cell type has been annotated using a comprehensive brain-wide MERFISH dataset with a total of ~4 million segmented and QC-passed cells, probed with a 500-gene panel and registered to the Allen Mouse Brain Common Coordinate Framework (CCF v3). The MERFISH data not only provide accurate spatial annotation of cell types at subclass, supertype and cluster levels, but also reveal fine-resolution spatial distinctions or gradients for cell types.

The combination of scRNA-seq and MERFISH data reveals a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type, as well as unique features of cell type organization in different brain regions.

A detailed cell type annotation table is also provided along with data downloads (GitHub), detailing information about the hierarchical membership, anatomical annotation, neurotransmitter type, cell type marker genes, transcription factor and neuropeptide markers, and other metadata types for each cluster. Learn more...