Published March 25, 2026 | Version v1
Dataset Open

Novel transcriptomic microglia taxonomy across mouse and human pathologies

  • 1. ROR icon University Medical Center Freiburg
  • 1. Universitätsklinikum Freiburg
  • 2. Albert-Ludwigs-Universität Freiburg Medizinische Fakultät

Description

This archive contains the processed Seurat objects and associated R scripts used to generate all main and extended figures from the manuscript: Chhatbar et al.

The data includes single-cell transcriptomic or spatial transcriptomics profiles of human brain immune cells, focusing on microglia across multiple brain regions and neurological conditions across two species, human and mouse. Each .rds file corresponds to a specific figure (or panel group), and accompanying R scripts reproduce the individual plots used to build the figures.

Each figure's  individual plots can be reproduced and saved using .R scripts. Final composite figures in the paper were assembled in Adobe Illustrator from these components.

Abstract (English)

Microglia are the key immune cells involved in virtually all diseases of the central nervous system (CNS). Numerous previous single-cell sequencing approaches to the study of microglia have revealed extensive diversity in this cell type in the human and mouse brain in different conditions1-5. Importantly, a unifying, comprehensive, disease- and species spanning transcriptomic immune cell-focused atlas of the perturbed CNS, including true single-cell spatial transcriptomic information on neighborhood relationships, is lacking. Here, we generated a novel large-scale single-cell RNA-sequencing-derived taxonomy through the analysis of > 1 million CNS cells enriched for myeloid cells across > 30 different pathologies and conditions. Disease-associated human microglia, together with CNS-associated macrophages and monocytes, were differentiated iteratively into 27 superclusters and 192 clusters, showing substantial overlap with their counterparts in the corresponding murine pathologies. This top-down approach, in combination with targeted and genome-wide subcellular spatial transcriptomics, enabled us to examine and compare the spatial interactome of the identified superclusters and clusters within and across pathologies and species. Using cell-specific mutants, we further characterized the underlying transcriptional programs of activation-associated microglial clusters, identifying distinct dependencies on type I and II interferons and colony stimulating factor 1 receptor pathways. Our data provide new insights into the spatial dynamics of the endogenous CNS immune system during development, health and disease in human and mouse. 

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colors_human_data.csv

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Additional details

Software

Programming language
R , Python
Development Status
Active