Identification of region-specific astrocyte subtypes at single cell resolution
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Abstract
Astrocytes, a major cell type found throughout the central nervous system, have general roles in the modulation of synapse formation and synaptic transmission, blood-brain barrier formation, and regulation of blood flow, as well as metabolic support of other brain resident cells. Crucially, emerging evidence shows specific adaptations and astrocyte-encoded functions in regions, such as the spinal cord and cerebellum. To investigate the true extent of astrocyte molecular diversity across forebrain regions, we used single-cell RNA sequencing. Our analysis identifies five transcriptomically distinct astrocyte subtypes in adult mouse cortex and hippocampus. Validation of our data in situ reveals distinct spatial positioning of defined subtypes, reflecting the distribution of morphologically and physiologically distinct astrocyte populations. Our findings are evidence for specialized astrocyte subtypes between and within brain regions. The data are available through an online database (https://holt-sc.glialab.org/), providing a resource on which to base explorations of local astrocyte diversity and function in the brain.
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It is well established that both astrocytes and microglia show regional heterogeneity at the transcriptome level.
“A possible explanation for this phenomenon is that we analyzed the cortex and hippocampus together, while it is well established that both astrocytes and microglia show regional heterogeneity at the transcriptome level (Batiuk et al., 2020;Tan et al., 2020).”
From Single-cell resolution analysis of the crosstalk between chemogenically activated astrocytes and microglia (2020) · cites this paper as Batiuk et al., 2020
The Results (Single-cell mRNA sequencing reveals astrocyte heterogeneity) report transcriptomic differences between cortical and hippocampal astrocyte subtypes, supporting the astrocyte part of the jointly cited claim. Our copy does not establish regional transcriptomic heterogeneity in microglia. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe cells projected on the UMAP space were annotated using canonical marker genes for neurons, progenitors, intermediate progenitors, astrocytes, other glial cells, and monocytes.
“The cells projected on the UMAP space were annotated using canonical marker genes for neurons, progenitors, intermediate progenitors, astrocytes, other glial cells, and monocytes (17, 84, 85).”
From Understanding monocyte-driven neuroinflammation in Alzheimer’s disease using human cortical organoid microphysiological systems (2025) · cites this paper as [84]
The Results section (‘Single-cell mRNA sequencing reveals astrocyte heterogeneity’; page unavailable) says cell types were identified using known marker genes, supporting the annotation method. But this paper shows tSNE plots, not UMAP, and the passages do not establish the full listed set of cell types, particularly monocytes. (LLM, conf=0.86)
Experimental — accuracy not yet measuredScRNAseq and snRNAseq are becoming established as valuable tools to gain insight into basal and reactive-astrocyte heterogeneity.
“ScRNAseq and snRNAseq are becoming established as valuable tools to gain insight into basal94 and reactive-astrocyte heterogeneity (Fig. 1e)40,78,95.”
From Reactive astrocyte nomenclature, definitions, and future directions (2021) · cites this paper as [94]
The Abstract and Results show that single-cell RNA sequencing identified distinct astrocyte subtypes in adult mouse cortex and hippocampus, supporting its use to study basal heterogeneity. This paper does not establish the corresponding claim for single-nucleus RNA sequencing; its own study also does not examine reactive astrocyte heterogeneity. (LLM, conf=0.83)
Experimental — accuracy not yet measuredLess is known about the transcriptomic heterogeneity of astrocytes across different cortical areas in the aging human brain.
“but less is known about the transcriptomic heterogeneity of astrocytes across different cortical areas in the aging human brain.”
From Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease (2024) · cites this paper as [31]
The Results report transcriptomic heterogeneity between and within regions of the adult mouse brain, and the Introduction notes evidence for region-specific astrocyte subtypes in human tissue. Neither passage establishes how much is known about differences across cortical areas in the aging human brain; the paper's own single-cell analysis is in mice. (LLM, conf=0.77)
Experimental — accuracy not yet measuredThese astrocytes (Batiuk et al.'s cluster 5) seem to be enriched in cortical layers 2/3 and 5, and in the dentate gyrus of the hippocampus.
“These astrocytes seem to be enriched in cortical layers 2/3 and 5, and in the dentate gyrus of the hippocampus (Batiuk et al., 2020).”
From Single-cell resolution analysis of the crosstalk between chemogenically activated astrocytes and microglia (2020) · cites this paper as Batiuk et al., 2020
A recent study (Batiuk et al., 2020) determined the transcriptomic profile of astrocytes in the hippocampus and cortex of C57BL/6J mice at post-natal day 56 and showed the existence of five transcriptionally different astrocytic clusters.
“Furthermore, a recent study (Batiuk et al., 2020) determined the transcriptomic profile of astrocytes in the hippocampus and cortex of C57BL/6J mice at post-natal day 56 and showed the existence of five transcriptionally different astrocytic clusters.”
From Single-cell resolution analysis of the crosstalk between chemogenically activated astrocytes and microglia (2020) · cites this paper as Batiuk et al., 2020
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- Authors
- Batiuk, M. Y., Martirosyan, A., Wahis, J., de Vin, F., Marneffe, C., Kusserow, C., Koeppen, J., Viana, J. F., Oliveira, J. F., Voet, T., Ponting, C. P., Belgard, T. G., & Holt, M. G.
- Affiliations
- VIB-KU Leuven Center for Brain & Disease Research (BE)
- University of Minho (PT)
- Universidade Politécnica do Cávado e do Ave (PT)
- Wellcome Sanger Institute (GB)
- University of Oxford (GB)
- Corresponding author
- Holt, Matthew G.
- ORCID
- Venue
- Nature Communications
- Published
- 2020-03-05
- Volume
- 11
- Issue
- 1
- Pages
- 1220-1220
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7058027
- OpenAlex
- W3009790191
- Cited by
- 805
- References
- 71
- Citations by year
- 2026: 102 · 2025: 135 · 2024: 137 · 2023: 132 · 2022: 139 · 2021: 112 · 2020: 46 · 2019: 1 · 2018: 1
- FWCI
- 34.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- European Commission (604102, 2007–2013, FP7 2007-2013, FP7/2007)
- Fonds Wetenschappelijk Onderzoek (12V7519N, G066715N, AKUL/13/39, I001818N)
- KU Leuven
- Fondation contre le Cancer (2015-143)
- Medical Research Council (FP7/20072013, MC_UU_00007/15)
- FP7 Ideas: European Research Council (281961)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- astrocytes, astrocyte subtypes, forebrain, cerebral cortex, hippocampus, single-cell transcriptomics, mouse brain
- MeSH terms
- Animals, Astrocytes, Gene Expression Regulation, Mice, Inbred C57BL, Organ Specificity, RNA, Messenger, Calcium Signaling, Cell Shape, Neurogenesis, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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