Collections / geo-gse283302

geo-gse283302

Datasets1
Size~29.1 MB
TechnologyVisium
Samplemouse · adrenal gland
KindPublication
Flag a data issue
10.1007/s00418-025-02446-6 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse283302")
cohort.members        # the 1 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-gse283302")
coll.ordered_artifacts.to_dataframe()   # the 1 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-gse283302 --dest data/

Licenses: 1 NCBI GEO policy

Identification of conserved canonical marker genes in human and mouse adrenal glands using Visium spatial transcriptomics.

The adrenal glands are essential endocrine organs whose cortex and medulla maintain systemic homeostasis and mediate stress responses via steroid hormone and catecholamine secretion. Despite anatomical and functional similarities between human and mouse adrenal glands, notable species-specific differences exist. Here, we leveraged spatial transcriptomics (10× Genomics Visium) to comprehensively map gene expression in adult human and mouse adrenal glands, aiming to identify canonical marker genes conserved across species. The analysis was based on a 31-year-old female human sample (GEO dataset) and four 10-week-old male CD-1 mice. Human adrenal sections were processed using optimal cutting temperature (OCT) embedding, whereas mouse adrenal sections were processed as formalin-fixed paraffin-embedded (FFPE) samples, highlighting differences in sample preparation. Using unsupervised clustering of spatial gene expression data, we delineated distinct adrenal cortex and medulla zones in both species, confirming known zonation patterns. Our cross-species analysis revealed highly conserved spatial expression of key known marker genes characteristic of the adrenal cortex (e.g., CYP11B2 for ZG, CYP11B1 for ZF) and medullary chromaffin cells (e.g., TH), as well as a core set of additional marker genes previously less characterized in adrenal biology. By integrating transcriptional profiles, we generated a catalogue of conserved canonical marker genes that define adrenal zonation and function in both humans and mice. These results highlight the fundamental molecular conservation of adrenal gland organization and support the translational value of mouse models in adrenal research. Our findings provide new insights into the evolutionary preservation of adrenal function and a valuable resource for studies on adrenal physiology and disease.

Open in Vitessce
Visium
Mouse adrenal gland
Spatial Transcriptomic Profiling of the Mouse Adrenal Gland and Adjacent Adipose Tissue [GSM8659692]
mouse adrenal gland 29.1 MB 992 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueadrenal gland
Size29.1 MB
Spots992
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1007/s00418-025-02446-6 ↗
BibTeX
@article{Blatkiewicz_2025,
  title = {Identification of conserved canonical marker genes in human and mouse adrenal glands using Visium spatial transcriptomics},
  volume = {164},
  ISSN = {1432-119X},
  url = {http://dx.doi.org/10.1007/s00418-025-02446-6},
  DOI = {10.1007/s00418-025-02446-6},
  number = {1},
  journal = {Histochemistry and Cell Biology},
  publisher = {Springer Science and Business Media LLC},
  author = {Blatkiewicz, Małgorzata and Szyszka, Marta and Hryhorowicz, Szymon and Suszyńska-Zajczyk, Joanna and Porzionato, Andrea and Plewiński, Adam and Malendowicz, Ludwik K. and Rucinski, Marcin},
  year = {2025},
  month = Dec
}