Collections / Single-cell multiomic approaches define a gradual, spatially-regulated epigenetic and transcriptional transition from embryonic to adult neural stem cells [Xenium]

Single-cell multiomic approaches define a gradual, spatially-regulated epigenetic and transcriptional transition from embryonic to adult neural stem cells [Xenium]

Here, we ask how adult neural stem cells (NSCs) arise developmentally, focusing on murine cortical precursors that generate excitatory neurons embryonically and interneurons and glial cells postnatally. Using complementary single-cell spatial, transcriptomic, and epigenomic approaches, we show that postnatal NSC state acquisition involves a gradual transcriptional and epigenetic shift in the entire embryonic cortical precursor cell population and identify a distinct transition precursor state at E17/18 when both embryonic and the first postnatal progeny are being generated. Non-proliferative adult NSCs are also first seen at this transition timepoint, but they arise in a spatial domain distinct from that of the first postnatal progeny, indicating that NSC state acquisition is not a necessary prelude to the switch in cell genesis. These findings support a gradual epigenetically-continuous model for the transition from developing cortical precursors to NSCs and show that this is spatially separable from the transition to generating postnatal cell types.

Datasets10
Size~9.9 GB
Assay10x Xenium
Samplemouse · brain
KindComparison
Flag a data issue
PMID:42314674 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse318202")
cohort.members        # the 10 datasets as a table

print(cohort.licenses())              # check the terms before you download

sdatas = cohort.to_dict()             # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")
Python · lamindb

Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse318202")
coll.ordered_artifacts.to_dataframe()   # the 10 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse318202 --dest data/

Licenses: 10 NCBI GEO policy

Open in Vitessce
10x Xenium
Mouse brain
GSM9489188
mouse brain 650 MB 60,038 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size650 MB
Cells60,038
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489192
mouse brain 779 MB 83,672 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size779 MB
Cells83,672
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489195
mouse brain 1.4 GB 98,395 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size1.4 GB
Cells98,395
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489194
mouse brain 1.8 GB 128,498 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size1.8 GB
Cells128,498
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489187
mouse brain 698 MB 68,239 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size698 MB
Cells68,239
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489190
mouse brain 753 MB 88,276 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size753 MB
Cells88,276
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489193
mouse brain 767 MB 81,207 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size767 MB
Cells81,207
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489196
mouse brain 1.6 GB 115,387 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size1.6 GB
Cells115,387
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489189
mouse brain 702 MB 65,647 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size702 MB
Cells65,647
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
10x Xenium
Mouse brain
GSM9489191
mouse brain 823 MB 90,497 cells silver NCBI GEO policy
Technology10x Xenium
Organismmouse
Tissuebrain
Size823 MB
Cells90,497
silver NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1016/j.stemcr.2026.102967 ↗
BibTeX
@article{Wang_2026,
  title = {Single-cell multiomic approaches define a gradual, spatially regulated epigenetic and transcriptional transition from embryonic to adult neural stem cells},
  volume = {21},
  ISSN = {2213-6711},
  url = {http://dx.doi.org/10.1016/j.stemcr.2026.102967},
  DOI = {10.1016/j.stemcr.2026.102967},
  number = {7},
  journal = {Stem Cell Reports},
  publisher = {Elsevier BV},
  author = {Wang, Beatrix S. and Karamboulas, Konstantina and Tahmasian, Nareh and Dennis, Daniel J. and Kaplan, David R. and Miller, Freda D.},
  year = {2026},
  month = July,
  pages = {102967}
}