Single-cell spatial transcriptomics of ACAN cKO in WT and 5xFAD mice
收藏NIAID Data Ecosystem2026-05-02 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.z612jm6pw
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资源简介:
This dataset comprises results from one single-cell spatial experiment conducted on mouse brains. This experiment was performed using the Bruker Nanostring CosMx technology on 10 µm coronal brain sections from 8-month-old female WT, WT ACAN cKO, 5xFAD, and 5x ACAN cKO mice. The dataset is provided as two separate RDS files split by flowcell which include raw and corrected counts for the RNA data, along with comprehensive metadata. Metadata includes mouse genotype, sample ID, cell type annotations, and X-Y coordinates of each cell.
Methods
Sample preparation: Isopentane fresh-frozen brain hemispheres were embedded in optimal cutting temperature (OCT) compound (Tissue-Tek, Sakura Fintek, Torrance, CA), and 10 µm thick coronal sections were prepared using a cryostat (CM1950, LeicaBiosystems, Deer Park, IL). Six hemibrains were mounted onto each VWR Superfrost Plus microscope slide (Avantor, 48311-703) and kept at -80°C until fixation. For transcriptomic analysis, n=3 mice per genotype were used for both the 5xFAD and 5xFAD ACAN cKO groups, while n=4 for WT and n=2 for WT ACAN cKO. Tissues were processed according to the Nanostring CosMx fresh-frozen slide preparation manual for RNA assay (NanoString University).
Data processing: Spatial transcriptomics datasets were filtered using the AtoMx RNA Quality Control module to flag outlier negative probes (control probes targeting non-existent sequences to quantify non-specific hybridization), lowly-expressing cells, FOVs, and target genes. Datasets were then normalized and scaled using Seurat 5.0.1 SCTransform to account for differences in library size across cell types. Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analysis were performed to reduce dimensionality and visualize clusters in space. Unsupervised clustering at 1.0 resolution yielded 38 clusters. Clusters were manually annotated based on gene expression and spatial location.
创建时间:
2025-07-01



