Collections / Spatial transcriptomics map of the embryonic mouse brain: a tool to explore neurogenesis

Spatial transcriptomics map of the embryonic mouse brain: a tool to explore neurogenesis

The developing brain has a complex and well-organized anatomical structure comprising different types of neural and non-neural cells. Stem cells, progenitors, and newborn neurons tightly interact with their neighbouring cells and tissue microenvironment, and this intricate interplay ultimately shapes the output of neurogenesis. Given the relevance of spatial cues during brain development, we acknowledge the necessity for a transcriptomics atlas within the tissue context accessible to the neurodevelopmental community. To fulfil this need, we offer an open-access spatial gene expression browser of the embryonic mouse brain at the peak of neurogenesis. Using 10x Visium technology, we generated spatially-resolved RNAseq data from E13.5 embryonic brain sections. Unsupervised clustering reliably defined specific cell type populations of diverse lineages and maturational states. Differential expression analysis revealed unique transcriptional signatures across specific embryonic brain areas, uncovering novel features inherent to particular anatomical domains. Furthermore, we integrated single-cell RNAseq data from E13.5 mouse brains into our Spatial Transcriptomics data, adding tissue context to single-cell resolution. In summary, we provide a valuable tool that enables the exploration and discovery of unforeseen molecular players involved in neurogenesis, particularly in the crosstalk between different cell types.

Datasets4
Size~68 MB
AssayVisium
Samplemouse · brain
KindOther
PMID:37855382 ↗
Python · lamindb
import lamindb as ln
import spatialdata as sd

coll = ln.Collection.get(key="geo-gse240715")
coll.ordered_artifacts.df()                 # the 4 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]

# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()}
Open in Vitessce
Visium
Mouse brain
GSM7708220
mouse brain 15 MB 984 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuebrain
Size15 MB
Obs984
Magnificationother · 3.361 µm/px
bronze H&E Open in Vitessce
Open in Vitessce
Visium
Mouse brain
GSM7708218
mouse brain 17 MB 1,196 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuebrain
Size17 MB
Obs1,196
Magnificationother · 3.577 µm/px
bronze H&E Open in Vitessce
Open in Vitessce
Visium
Mouse brain
GSM7708221
mouse brain 18 MB 1,266 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuebrain
Size18 MB
Obs1,266
Magnificationother · 3.322 µm/px
bronze H&E Open in Vitessce
Open in Vitessce
Visium
Mouse brain
GSM7708219
mouse brain 18 MB 1,152 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuebrain
Size18 MB
Obs1,152
Magnificationother · 3.517 µm/px
bronze H&E Open in Vitessce

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