Dataset Information

Forniceal deep brain stimulation induces gene expression and splicing changes that promote neurogenesis and synaptic plasticity

ABSTRACT: Clinical trials are currently underway to assess the efficacy of forniceal deep brain stimulation (DBS) for the improvement of memory in Alzheimer’s patients, and forniceal DBS has been shown to improve learning and memory in a mouse model of Rett syndrome (RTT), an intellectual disability disorder. The mechanism of DBS benefits has been elusive, however, so we assessed gene expression, splice isoform abundance, DNA methylation, and proteomic changes following acute forniceal DBS in wild-type mice and a mouse model lacking Mecp2, the gene whose loss of function causes RTT. We found that DBS upregulates genes involved in synaptic function, cell survival, and neurogenesis, and alters the proportions of different isoforms even for genes whose expression is unchanged. DBS rescued ~25% of the gene expression defects in Mecp2-null mice, particularly those involved in synaptic components, and it induced expression of 17-24% of the genes found to be downregulated in intellectual disability mouse models and in post-mortem human brain tissue from patients with Major Depressive Disorder. DBS could thus benefit individuals with a variety of neuropsychiatric disorders.

ORGANISM(S): Mus musculus

PROVIDER: GSE107383 | GEO | 2018/04/17

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Rett syndrome (RTT) is a neurodevelopmental disorder characterized by developmental regression around 6-18 months after birth, followed by a lifetime of intellectual disability, stereotyped behaviors, and motor deficits. RTT is caused by mutations in MeCP2, a methyl-CpG binding protein that was traditionally believed to repress gene expression. Gene expression studies of individual brain regions, however, have revealed that MeCP2 loss-of-function leads to the subtle activation and repression of its gene targets. However, these results may be confounded by the extensive neuronal cell heterogeneity inherent in these brain structures. To minimalize this issue of heterogeneity, we assessed whether Mecp2-null mice exhibited alterations in gene expression patterns in the striatum, a brain nucleus with relatively homogenous neuronal types and is highly relevant to the motor deficits observed in RTT. Despite the homogeneity of the tissue, the fold-change of the 127 differentially expressed genes we identified remained low with a mean change consistent with other studies. However, many of those genes differentially expressed in the striatum have not been previously identified in gene expression analyses of other brain regions. This suggests therefore that the differential expression of genes following loss of MeCP2 occurs in a tissue, or cell-type specific manner and thus MeCP2 function should be understood in a cellular context. In initiating this study, we reasoned that reducing the number of cell types in a microarray experiment may reveal transcriptional changes that are masked in a whole tissue analysis. We therefore focused on tissues more homogeneous in regards to the diversity of neuronal cell types they contain in order to discern gene expression changes in the absence of MeCP2. We chose to isolate the striatum, a tissue composed predominantly of GABAergic medium spiny neurons (MSNs). The striatum was resected from five symptomatic Mecp2-null (KO) male mice bearing the Bird allele and five wild-type (WT) littermates in a C57BL/6 background. We also isolated liver from the same individuals to serve as a non-neuronal control. RNA was isolated from these tissues, converted to cDNA, and hybridized to a single-channel Affymetrix GeneChip Mouse Exon 1.0 ST array for a total of 20 individual arrays.

Dataset Information

Forniceal deep brain stimulation induces gene expression and splicing changes that promote neurogenesis and synaptic plasticity

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets