Multi-omics Analysis Revealing the Impact of Excessive Maternal Folate Supplementation on Offspring Brain Development [spatial transcriptome]
Folate is crucial for diverse biological processes including neurogenesis. While folate supplementation during pregnancy is standard for preventing neural tube defects (NTDs), concerns are growing over the potential risks of excessive maternal intake. In this study, we employed spatial transcriptomics and single-nucleus multi-omics techniques to investigate the impact of increased maternal folate intake on offspring brain development. Elevated folate intake broadly affected gene pathways linked to neurogenesis and neuronal axon myelination across multiple brain regions. Furthermore, specific gene expression alterations related to learning and memory processes emerged in thalamic and ventricular regions. Single-nucleus multi-omics analysis revealed that maturing excitatory neurons in dentate gyrus are particularly vulnerable to suboptimal maternal folate intake. Aberrant gene expression and chromatin accessibility changes were primarily centered on pathways governing ribosomal biogenesis, which is critical for synaptic formation. Altogether, our findings provide novel insights into how excessive maternal folate supplementation affects offspring brain development, notably by influencing gene expression and chromatin accessibility.
from sddb import Catalog
cohort = Catalog().collection("geo-gse269543")
cohort.members # the 4 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-gse269543")
coll.ordered_artifacts.to_dataframe() # the 4 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-gse269543 --dest data/ Licenses: 4 NCBI GEO policy
Cite this collection
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