Dataset Information

Forebrain assembloids support the development of fast-spiking human PVALB+ cortical interneurons and uncover schizophrenia-associated defects.

ABSTRACT: Disruption of parvalbumin positive (PVALB+) cortical interneurons is implicated in the pathogenesis of schizophrenia. However, how these defects emerge during development is not well understood. The protracted maturation of these cells during postnatal development has made their derivation from human pluripotent stem cells (hPSCs) extremely difficult, precluding hPSC-based disease modeling of their role in neuropsychiatric diseases. Here we present a cortical assembloid system that supports the development of PVALB+ cortical interneurons which match the molecular profiles of primary PVALB+ interneurons and display their distinctive electrophysiological features. Further, we characterized cortical interneuron development in a series of CRISPR-generated isogenic structural variants associated with schizophrenia and identified variant-specific phenotypes in cortical interneuron migration and the molecular profile of PVALB+ cortical interneurons. These findings reveal plausible mechanisms on how disruption of cortical interneuron development may impact schizophrenia risk and provide an exciting human experimental platform to facilitate the study of PVALB+ cortical interneurons.

ORGANISM(S): Homo sapiens

PROVIDER: GSE250482 | GEO | 2025/07/21

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Fast-spiking (FS) interneurons are important elements of neocortical circuitry that constitute the primary source of synaptic inhibition in adult cortex and impart temporal organization on ongoing cortical activity. The highly specialized intrinsic membrane and firing properties that allow cortical FS interneurons to perform these functions are attributable to equally specialized gene expression, which is ultimately coordinated by cell-type-specific transcriptional regulation. Although embryonic transcriptional events govern the initial steps of cell-type specification in most cortical interneurons, including FS cells, the electrophysiological properties that distinguish adult cortical cell types emerge relatively late in postnatal development, and the transcriptional events that drive this maturational process are not known. To address this, we used mouse whole-genome microarrays and whole-cell patch clamp to characterize the transcriptional and electrophysiological maturation of cortical FS interneurons between postnatal day 7 (P7) and P40. We found that the intrinsic and synaptic physiology of FS cells undergoes profound regulation over the first 4 postnatal weeks and that these changes are correlated with primarily monotonic but bidirectional transcriptional regulation of thousands of genes belonging to multiple functional classes. Using our microarray screen as a guide, we discovered that upregulation of two-pore K leak channels between P10 and P25 contributes to one of the major differences between the intrinsic membrane properties of immature and adult FS cells and found a number of other candidate genes that likely confer cell-type specificity on mature FS cells. Experiment Overall Design: We characterized the transcriptional maturation of genetically labeled FS interneurons in mouse S1 cortex using whole-genome microarrays.mRNA was harvested from manually sorted GFPexpressing neurons dissociated from acutely prepared brain slices at a range of developmental time points (P7, P10, P15, P25, and P40) and subsequently reverse transcribed, amplified, labeled, and hybridized to Affymetrix 430 2.0 whole-genome microarrays (three microarrays from three different animals per condition). We used the G42 transgenic mice described by Chattopadhyaya et al. (2004) for all experiments.

Dataset Information

Forebrain assembloids support the development of fast-spiking human PVALB+ cortical interneurons and uncover schizophrenia-associated defects.

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets