Single-cell-scale spatial transcriptome of the developing and adult mouse ovary
Mammalian ovary development is essential for female fertility, involving the complex spatial patterning of diverse cell types to establish the finite reserve of ovarian follicles. While single-cell transcriptome analyses have provided important insights into the mechanisms driving specification and developmental trajectories of ovarian cells, they disrupt this crucial spatial context. To overcome this limitation, we used 10X Genomics Visium HD spatial transcriptomics to analyze the developing mouse ovary while maintaining its native cellular architecture. We captured all ovarian cell types at eight key fetal and postnatal timepoints, generating a near single cell resolution library of spatial gene expression across ovarian development. This comprehensive dataset allows analysis of dynamic transcriptional signatures associated with unique spatial patterning throughout development, including the establishment of cortex and medulla and assembly of ovarian follicles in each region. This dataset represents a fundamental resource for the investigation of regulatory mechanisms driving spatial patterning of the ovary, and opens new avenues to explore the spatial determinants of female fertility and reproductive longevity.
from sddb import Catalog
cohort = Catalog().collection("geo-gse307688")
cohort.members # the 8 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/") 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-gse307688")
coll.ordered_artifacts.to_dataframe() # the 8 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()] # sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse307688 --dest data/ Licenses: 8 NCBI GEO policy
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