MRNA expression analysis of the hippocampus in a vervet monkey model of fetal alcohol spectrum disorder
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ABSTRACT:
PROVIDER: PRJNA725871 | ENA |
REPOSITORIES: ENA
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Project description:Alcohol preferring vervet dams were permitted to ingest alcohol 4 days/week during the second half of gestation (e90-e165) and paired with sucrose matched controls. Cases and controls were sacrificed with subsequent hippocampal extraction at 5 months and 2 years. RNA was extracted according to the manufacturer's protocol and hybridized to the Affymetrix Rhesus Genechip microarray. We sought to identify pathways and genes involved in the development of fetal alcohol spectrum disorder in a non-human primate in order to develop an understanding of how this disorder may develop in humans.
2022-02-23 | GSE173516 | GEO
Project description:Alcohol preferring vervet dams were permitted to ingest alcohol 4 days/week during the second half of gestation (e90-e165) and paired with sucrose matched controls. Cases and controls were sacrificed with subsequent hippocampal extraction at 5 months and 2 years. RNA was extracted according to the manufacturer's protocol and hybridized to the Affymetrix Rhesus Genechip microarray. We sought to identify whether global downregulation in mRNA dataset was related to miRNA expression in a non-human primate model of FASD in order to develop an understanding of how this disorder may develop in humans.
2022-01-24 | GSE181456 | GEO
Project description:miRNA expression analysis of the hippocampus in a vervet monkey model of fetal alcohol spectrum disorder
| PRJNA752101 | ENA
Project description:Transcriptomic profiling is a crucial tool for understanding growth, development, behavior and predisposition to diseases and the development of health biomarkers. Here, we demonstrate the feasibility of transcriptomic assessment of cell-free fetal RNA in vervet monkey amniotic fluid supernatant (AFS).
2019-09-13 | GSE119908 | GEO
Project description:This report is based on an ongoing study to examine gene expression differences in monkey lateral geniculate nucleus (LGN). For this study, samples from an Old World species, vervet monkey (Cercopithecus aethiops), were cross-hybridized to the Rhesus Macaque Genome Array (Affymetrix). Microarray analysis was performed using laser capture microdissected populations of individual neuronal cell bodies isolated from the LGN compared to heterogeneous samples from whole lamina. We show here that cross-species hybridization of microdissected brain tissue samples from vervet monkeys to the Rhesus array produced reliable and biologically relevant data sets. We present the first list of genes enriched in the large neuronal cell bodies of the LGN. We found that these cell bodies are concentrated with genes involved in metabolic processes and protein synthesis, whereas signaling molecules including chemokines and integrins were expressed at higher levels within heterogeneous samples. Our data set provides support for a contribution of Wnt signaling in adult monkey LGN. Keywords: gene expression profile
2007-11-12 | GSE8859 | GEO
Project description:Transcriptome of amniotic fluid in vervet monkey
| PRJNA490653 | ENA
Project description:DNA methylation data from vervet cerebral cortex, blood, and liver using highly conserved mammalian CpGs represented on the mammalian methylation array (HorvathMammalMethylChip40). We selected a total of 240 samples representing the entire vervet lifespan, from neonatal to senile stages: 144 samples from the peripheral blood, 48 samples from the liver, and 48 samples from the cortical brain area BA10.
2023-08-05 | GSE190660 | GEO
Project description:Elucidating the developmental patterns of gene expression across brain regions is a critical step toward understanding brain development and disease. We previously studied the transcriptome of multiple brain regions and peripheral tissues across development in the vervet monkey, and identified transcripts related to hippocampal size in 59 animals across 10 developmental timepoints, ranging between 7 days to 9 years of age. Here, we extended this analysis with a focus on transcriptomic changes in hippocampus across early development in vervet neonates and infants under 1 year of age. We combined this dataset with the previously analyzed data. We identified groups of transcripts with age-related patterns, which correlated well with existing human resources. Additionally, expression quantitative trait locus (eQTL) analysis identified two further genes, RAB31 and CHMP1B, associated with hippocampal volume, refining the previously identified locus. This dataset provides unique developmental expression data in the hippocampus of a non-human primate, and expands our catalog of local and distant eQTL in this brain region.
2020-08-21 | GSE136255 | GEO
Project description:Epigenetic profiling of Fetal Alcohol Spectrum Disorder (FASD)
| PRJNA449761 | ENA
Project description:Background: Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Methods: Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). Results: We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. Conclusion: These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.
2018-02-23 | GSE109042 | GEO