A systems approach identifies networks and genes linking sleep and stress: implications for neuropathology
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE60312 | GEO | 2015/01/08
SECONDARY ACCESSION(S): PRJNA258009
REPOSITORIES: GEO
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Project description:Sleep dysfunction and stress susceptibility are co-morbid complex traits, which often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multi-level organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J×A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests the interplay between sleep, stress, and neuropathology emerge from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework to interrogate the mechanisms underlying sleep, stress susceptibility, and related neuropathology. Examination of genomic and transcriptomic networks in a random subset of 100 (B6xA/J)F2 mice modeling the natural spectrum of stress susceptibility.
2015-01-08 | E-GEOD-60312 | biostudies-arrayexpress
Project description:A systems approach identifies networks and genes linking sleep and stress: implications for neuropathology
| PRJNA258009 | ENA
Project description:Resveratrol (RSV) has been confirmed to benefit human health. Resveratrol supplemented in the feeds of animals improved pork, chicken, and duck meat qualities. In this study, we identified differentially expressed (DE) messenger RNAs (mRNAs) (n = 3,856) and microRNAs (miRNAs) (n = 93) for the weighted gene co-expression network analysis (WGCNA) to investigate the co-expressed DE mRNAs and DE miRNAs in the primary bovine myoblasts after RSV treatment. The mRNA results indicated that RSV treatments had high correlations with turquoise module (0.91, P-value = 0.01) and blue module (0.93, P-value < 0.01), while only the turquoise module (0.96, P-value < 0.01) was highly correlated with the treatment status using miRNA data. After biological enrichment analysis, the 2,579 DE genes in the turquoise module were significantly enriched in the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The top two GO terms were actin filament-based process (GO:0030029) and actin cytoskeleton organization (GO:0030036). The top two KEGG pathways were regulation of actin cytoskeleton (bta04810) and tight junction (bta04530). Then, we constructed the DE mRNA co-expression and DE miRNA co-expression networks in the turquoise module and the mRNA–miRNA targeting networks based on their co-expressions in the key module. In summary, the RSV-induced miRNAs participated in the co-expression networks that could affect mRNA expressions to regulate the primary myoblast differentiation. Our study provided a better understanding of the roles of RSV in inducing miRNA and of the characteristics of DE miRNAs in the key co-expressed module in regulation of mRNAs and revealed new candidate regulatory miRNAs and genes for the beef quality traits.
2021-12-31 | GSE186730 | GEO
Project description:Williams Syndrome (WS) is a rare neurodevelopmental disorder caused by heterozygous deletions in a chromosome 7q11.23 region typically encompassing 26-28 genes. WS patients exhibit a wide spectrum of symptoms, including cardiovascular disease, intellectual disability, visuospatial deficits and hypersociability a behavioral profile that contrasts with autism spectrum disorder (ASD). However, the relationship between neuropsychiatric phenotypes and dysregulated gene networks caused by the 7q11.23 deletion is unknown. We report results from a large-scale integrated transcriptome analysis of peripheral blood in clinically evaluated subjects with WS, ASD and matched controls. We identified significantly differential expressed genes in WS as compared with ASD or controls, even after removing genes spanning the 7q11.23 region. Using weighted gene co-expression network analysis (WGCNA), we found that three co-expression modules were upregulated in WS, and were significantly associated with the intermediate phenotypes such as anxiety and attention problems. Notably, these three co-expression modules were only composed of genes located outside of 7q11.23 critical region. One module was associated with immune systems and B cell proliferation. Its top hub gene, BCL11A, is implicated in ASD and chromatin modification. Another module was enriched with genes associated with astrocytes and oligodendrocytes, and the third module was associated with RNA processing and neurons.MicroRNA (miRNA) profiling revealed differentially expressed miRNAs whose targets were enriched in each co-expression module associated with WS. These results identify genes and potential driver miRNAs, located outside of 7q11.23 critical region, that are novel candidates for mediating the neuropsychiatric phenotypes in WS.
2018-11-06 | GSE89595 | GEO
Project description:Williams Syndrome (WS) is a rare neurodevelopmental disorder caused by heterozygous deletions in a chromosome 7q11.23 region typically encompassing 26-28 genes. WS patients exhibit a wide spectrum of symptoms, including cardiovascular disease, intellectual disability, visuospatial deficits and hypersociability a behavioral profile that contrasts with autism spectrum disorder (ASD). However, the relationship between neuropsychiatric phenotypes and dysregulated gene networks caused by the 7q11.23 deletion is unknown. We report results from a large-scale integrated transcriptome analysis of peripheral blood in clinically evaluated subjects with WS, ASD and matched controls. We identified significantly differential expressed genes in WS as compared with ASD or controls, even after removing genes spanning the 7q11.23 region. Using weighted gene co-expression network analysis (WGCNA), we found that three co-expression modules were upregulated in WS, and were significantly associated with the intermediate phenotypes such as anxiety and attention problems. Notably, these three co-expression modules were only composed of genes located outside of 7q11.23 critical region. One module was associated with immune systems and B cell proliferation. Its top hub gene, BCL11A, is implicated in ASD and chromatin modification. Another module was enriched with genes associated with astrocytes and oligodendrocytes, and the third module was associated with RNA processing and neurons. MicroRNA (miRNA) profiling revealed differentially expressed miRNAs whose targets were enriched in each co-expression module associated with WS. These results identify genes and potential driver miRNAs, located outside of 7q11.23 critical region, that are novel candidates for mediating the neuropsychiatric phenotypes in WS.
2018-11-06 | GSE89594 | GEO
Project description:Sleep and affective behaviors are highly interrelated phenotypes, commonly altered in a variety of neuropsychiatric diseases, including major depressive disorder (MDD). To understand the transcriptomic organization underlying sleep and affective function, we studied a population of (C57BL/6J x 129S1/SvImJ) F2 mice by measuring 283 affective and sleep phenotypes and profiling gene expression across four brain regions, including the frontal cortex, hippocampus, thalamus, and hypothalamus. We identified converging molecular bases for sleep and affective phenotypes at both the single-gene and gene-network levels. Utilizing publicly available transcriptomic datasets collected from sleep-deprived mice and major depressive disorder (MDD) patients, we identified three cortical gene networks altered by sleep/wake changes and depression. The network-level actions of sleep loss and depression were opposite to each other, providing a mechanistic basis for the sleep disruptions commonly observed in depression as well as the reported acute antidepressant effects of sleep deprivation. We highlight one particular network composed of circadian rhythm regulators and neuronal activity-dependent immediate-early genes. The key upstream driver of this network, Arc, may act as a nexus linking sleep and depression. Our data provide mechanistic insights into the role of sleep in affective function and MDD.
2018-12-21 | GSE109112 | GEO
Project description:Background: Late gestational sleep fragmentation (LG-SF) is one of the major perturbations associated with sleep apnea and other sleep disorders during pregnancy. Objectives: To investigate the effects of late LG-SF on the epigenome of visceral white adipose tissue (VWAT) in the offspring. Methods: Time-pregnant mice were exposed to LG-SF or control sleep (LG-SC) conditions during the last 6 days of gestation. We performed large-scale DNA methylation analyses using MeDIP coupled to microarrays (MeDIP-chip) in VWAT of 24-week-old LG-SF and LG-SC offspring (n=8 mice/group). Univariate multiple-testing adjusted statistical analyses were applied to identify differentially methylated regions (DMRs) between the groups. DMRs were mapped to their corresponding genes, and tested for potential overlaps with biological pathways and gene networks. Results: We detected 2148 DMRs between LG-SF and LG-SC groups (p< 0.0001, MAT algorithm). A large proportion of the DMR-associated genes have reported functions that are altered in obesity and metabolic syndrome. Overrepresented pathways and gene networks were related to metabolic regulation and inflammatory response. Conclusions: Our findings show a major role for epigenomic regulation of pathways associated to metabolic processes and inflammatory response in VWAT. Furthermore, LG-SF-induced epigenetic alterations appear to increase the susceptibility to obesity and metabolic syndrome in the offspring. 16 mouse VWAT samples were analyzed by MeDIP coupled to microarray analysis: Offspring of mothers exposed to late-gestational sleep fragmentation (n=8, LG-SF group) and offspring of mothers mouse exposed to normal sleep conditions (n=8, LG-SC group)
2015-04-02 | E-GEOD-63208 | biostudies-arrayexpress
Project description:Traumatic brain injury (TBI) can lead to significant neuropsychiatric problems and neurodegenerative pathologies, which develop and persist years after injury. Neuroinflammatory processes evolve over this same period. Therefore, we aimed to determine the contribution of microglia to neuropathology at acute (1-day post-injury; dpi), subacute (7 dpi), and chronic (30 dpi) time-points. Microglia were depleted with PLX5622, a CSF1R antagonist, prior to midline fluid percussion injury in male mice and cortical neuropathology/inflammation was assessed using a neuropathology mRNA panel. NanoString Neuropathology gene expression panel was used to quantify expression from RNA microdissected from the mouse cortex.
2020-11-15 | GSE160651 | GEO
Project description:This dataset was gene expression from natural sockeye salmon populations used to test the preservation of coexpression networks that were found in lake whitefish. Here is the abstract of the manuscript:BackgroundM-BM- : A functional understanding of processes involved in adaptive divergence is one of the awaiting opportunities afforded by high throughput transcriptomic technologies. Functional analysis of co-expressed genes has succeeded in the biomedical field in identifying key drivers of disease pathways. However, in ecology and evolutionary biology, functional interpretation of transcriptomic data is still limited. ResultsM-BM- : Here we used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify modules of co-expressed genes in muscle and brain tissue of a lake whitefish backcross progeny. Modules were connected to gradients of known adaptive traits involved in the ecological speciation process between benthic and limnetic ecotypes. Key drivers, i.e. hub genes of functional modules related to reproduction, growth, and behavior were identified, and module preservation was assessed in natural populations. Using this approach, we identified modules of co-expressed genes involved in phenotypic divergence and their key drivers, and further characterized the underlying regulatory structure governing these complex traits. ConclusionsM-BM- : Functional analysis of transcriptomic data can significantly contribute to the understanding of the mechanisms underlying ecological speciation. Our findings point to BMP and Calcium signaling as common pathways involved in coordinated evolution of trophic behavior, trophic morphology (gill rakers), and reproduction. Results also point to housekeeping pathways implicating hemoglobins and constitutive stress response (HSP70) governing growth in lake whitefish. Here are 49 female sockeye salmon transcriptomes as measured by the 16k cGRASP microarray.
2013-02-01 | E-GEOD-42985 | biostudies-arrayexpress
Project description:Depression is a complex and heterogeneous disorder and a leading contributor to the global burden of of disease. Most previous research has focused on individual brain regions and individual genes that contribute to depression. However, emerging evidence in both humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here we use a bioinformatics approach intersecting differential expression analysis with weighted gene co-expression network analysis to identify transcriptional networks that regulate susceptibility to depressive-like symptoms in mice. We performed RNA-sequencing on multiple brain regions from control animals and those either susceptible or resilient to chronic social defeat stress (CSDS) at multiple time points after defeat. We bioinformatically identified several transcriptional networks that regulate depression susceptibility, and in vivo manipulations of these networks confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our findings reveal novel transcriptional networks that control stress susceptibility and offer fundamentally new leads for antidepressant drug discovery.
2016-05-12 | GSE72343 | GEO