Dataset Information

Spatial transcriptomic profiling of the aging mouse brain [spatial scRNA-seq]

ABSTRACT: The mammalian brain can be divided into distinct structural and functional regions to perform a variety of diverse functions, but during normal aging, exactly how each region is affected, and the information interaction changes between different regions, remains largely unknown. To gain a better insight into these processes, here we generate a single-cell spatial transcriptomic (ST) atlas of young and old mice brains involving cerebrum, brain stem and fiber tracts regions. Based on the unbiased classification of spatial molecular atlas, 27 distinguished brain spatial domains were obtained, which are similar to known anatomical regions, but slightly different. Through differential expression analysis and gene set enrichment analysis (GSEA), we identified aging-related genes and pathways that vary in a coordinated or opposite manner across regions. Combined with single-cell transcriptomic data, we characterized the spatial distribution of cell types, identified an up-regulated gene Ifi27 across regions and cell types in VIS region. Through ligand-receptor interaction analysis, we identified all possible information interaction changes between regions with aging. In summary, we establish a brain spatial molecular atlas (accessible online at https:) to provide a rich resource of spatially differentially expressed genes and information interaction, which may help to understand aging and provide novel insights into the molecular mechanism of brain aging.

ORGANISM(S): Mus musculus

PROVIDER: GSE193107 | GEO | 2024/02/20

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

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.

Dataset Information

Spatial transcriptomic profiling of the aging mouse brain [spatial scRNA-seq]

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure