Project description:In the central nervous system, nuclear factor erythroid-2-related factor 2 (Nrf2) protects neurons from oxidant injury, thereby ameliorating neurodegeneration. We explored the key circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) involved in Nrf2-induced neuroprotection. We used microarrays to examine the circRNAs (DEcircRNAs), lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) differentially expressed between Nrf2 (+/+) and Nrf2 (-/-) mice and identified DEcircRNA/DElncRNA-miRNA-DEmRNA interaction networks. In total, 197 DEcircRNAs, 685 DElncRNAs and 356 DEmRNAs were identified in prefrontal cortical tissues from Nrf2 (-/-) mice. The expression patterns of selected DEcircRNAs (except for mmu_circ_0003404) and DElncRNAs in qRT-PCR analyses were generally consistent with the microarray analysis results. Functional annotation of the DEmRNAs in the DEcircRNA/DElncRNA-miRNA-DEmRNA networks indicated that five non-coding RNAs (mmu_circ_0000233, ENSMUST00000204847, NONMMUT024778, NONMMUT132160 and NONMMUT132168) may contribute to Nrf2 activity, with the help of mmu_circ_0015035 and NONMMUT127961. The results also revealed that four non-coding RNAs (cicRNA.20127, mmu_circ_0012936, ENSMUST00000194077 and NONMMUT109267) may influence glutathione metabolism. Additionally, 44 DEcircRNAs and 7 DElncRNAs were found to possess coding potential. These findings provide clues to the molecular pathways through which Nrf2 protects neurons.
Project description:Many cell activities are organized as a network, and genes are clustered into co-expressed groups if they have the same or closely related biological function or they are co-regulated. In this study, based on an assumption that a strong candidate disease gene is more likely close to gene groups in which all members coordinately differentially express than individual genes with differential expression, we developed a novel disease gene prioritization method GroupRank by integrating gene co-expression and differential expression information generated from microarray data as well as PPI network. A candidate gene is ranked high using GroupRank if it is differentially expressed in disease and control or is close to differentially co-expressed groups in PPI network. We tested our method on data sets of lung, kidney, leukemia and breast cancer. The results revealed GroupRank could efficiently prioritize disease genes with significantly improved AUC value in comparison to the previous method with no consideration of co-expressed gene groups in PPI network. Moreover, the functional analyses of the major contributing gene group in gene prioritization of kidney cancer verified that our algorithm GroupRank not only ranks disease genes efficiently but also could help us identify and understand possible mechanisms in important physiological and pathological processes of disease.
Project description:Alzheimer's disease (AD) is a major contributor to dementia in the elderly, characterized by progressive impairments in memory and behaviour. AD is marked by pathological hallmarks: amyloid plaques and neurofibrillary tangles (NFTs). Despite extensive efforts to understand these hallmarks, there is still a lack of efficient therapeutic approaches due to limited knowledge of the fundamental cellular mechanisms underlying the disease. One potential avenue of research involves the investigation of the roles of non-coding RNAs, particularly, microRNAs (miRNAs), which bind to the 3' UTRs of target mRNAs to suppress expression. In our study, we analysed the temporal superior T1 isocortex of control and AD patients, identifying differentially expressed miRNAs using next-generation sequencing (NGS). To validate these findings, we utilized an additional technique, RT-qPCR. Overall, our study confirms the previous findings on the dysregulation of miR-129-5p, miR-132-3p, and miR-146b-5p, while also providing novel insights into the dysregulation of miR-151a-5p and miR-1-3p. Importantly, the expression levels of miR-129-5p, miR-146b-5p, miR-132-3p, and miR-151a-5p were significantly correlated with the neuropathological Braak stages and with biochemically quantified tau phosphorylation levels in brain homogenates. Additionally, we found that miR-146b-5p and miR-151a-5p significantly modulated tau seeding in tau biosensor cell model, highlighting their potential roles in tau pathology.
Project description:To identify genome-wide differentially expressed microRNAs (miRNAs) between Huntington's disease (HD) and control Human pre-frontal cortex samples
Project description:The prefrontal cortex (PFC) constitutes a large part of the human central nervous system and is essential for the normal social affection and executive function of humans and other primates. Despite ongoing research in this region, the development of interactions between PFC genes over the lifespan is still unknown. To investigate the conversion of PFC gene interaction networks and further identify hub genes, we obtained time-series gene expression data of human PFC tissues from the Gene Expression Omnibus (GEO) database. A statistical model, loggle, was used to construct time-varying networks and several common network attributes were used to explore the development of PFC gene networks with age. Network similarity analysis showed that the development of human PFC is divided into three stages, namely, fast development period, deceleration to stationary period, and recession period. We identified some genes related to PFC development at these different stages, including genes involved in neuronal differentiation or synapse formation, genes involved in nerve impulse transmission, and genes involved in the development of myelin around neurons. Some of these genes are consistent with findings in previous reports. At the same time, we explored the development of several known KEGG pathways in PFC and corresponding hub genes. This study clarified the development trajectory of the interaction between PFC genes, and proposed a set of candidate genes related to PFC development, which helps further study of human brain development at the genomic level supplemental to regular anatomical analyses. The analytical process used in this study, involving the loggle model, similarity analysis, and central analysis, provides a comprehensive strategy to gain novel insights into the evolution and development of brain networks in other organisms.
Project description:Expression of brain-derived neurotrophic factor (BDNF) is developmentally regulated in prefrontal cortex (PFC). The underlying molecular mechanisms, however, remain unclear. Here, we explore the role of microRNAs (miRNAs) as post-transcriptional inhibitors of BDNF. A sequential approach involving in silico, miRNA microarray, in situ hybridization and qRT-PCR studies identified a group of 10 candidate miRNAs, segregating into five miRNA families (miR-30a-5p/b/c/d, miR-103/107, miR-191, miR-16/195, miR-495), which exhibited distinct developmental and lamina-specific expression in human PFC. Luciferase assays confirmed that at least two of these miRNAs, miR-30a-5p and miR-195, target specific sequences surrounding the proximal polyadenylation site within BDNF 3'-untranslated region. Furthermore, neuronal overexpression of miR-30a-5p, a miRNA enriched in layer III pyramidal neurons, resulted in down-regulation of BDNF protein. Notably, a subset of seven miRNAs, including miR-30a-5p, exhibited an inverse correlation with BDNF protein levels in PFC of subjects age 15-84 years. In contrast, the role of transcriptional mechanisms was more apparent during the transition from fetal to childhood and/or young adult stages, when BDNF mRNA up-regulation was accompanied by similar changes in (open chromatin-associated) histone H3-lysine 4 methylation at BDNF gene promoters I and IV. Collectively, our data highlight the multiple layers of regulation governing the developmental expression of BDNF in human PFC and suggest that miRNAs are involved in the fine-tuning of this neurotrophin particularly in adulthood.
Project description:Chronic alcohol consumption may induce gene expression alterations in brain reward regions such as the prefrontal cortex (PFC), modulating the risk of alcohol use disorders (AUDs). Transcriptome profiles of 23 AUD cases and 23 matched controls (16 pairs of males and 7 pairs of females) in postmortem PFC were generated using Illumina's HumanHT-12 v4 Expression BeadChip. Probe-level differentially expressed genes and gene modules in AUD subjects were identified using multiple linear regression and weighted gene co-expression network analyses. The enrichment of differentially co-expressed genes in alcohol dependence-associated genes identified by genome-wide association studies (GWAS) was examined using gene set enrichment analysis. Biological pathways overrepresented by differentially co-expressed genes were uncovered using DAVID bioinformatics resources. Three AUD-associated gene modules in males [Module 1 (561 probes mapping to 505 genes): r = 0.42, P(correlation) = 0.020; Module 2 (815 probes mapping to 713 genes): r = 0.41, P(correlation) = 0.020; Module 3 (1,446 probes mapping to 1,305 genes): r = -0.38, P(correlation) = 0.030] and one AUD-associated gene module in females [Module 4 (683 probes mapping to 652 genes): r = 0.64, P(correlation) = 0.010] were identified. Differentially expressed genes mapped by significant expression probes (P(nominal) ? 0.05) clustered in Modules 1 and 2 were enriched in GWAS-identified alcohol dependence-associated genes [Module 1 (134 genes): P = 0.028; Module 2 (243 genes): P = 0.004]. These differentially expressed genes, including ALDH2, ALDH7A1, and ALDH9A1, are involved in cellular functions such as aldehyde detoxification, mitochondrial function, and fatty acid metabolism. Our study revealed differentially co-expressed genes in postmortem PFC of AUD subjects and demonstrated that some of these differentially co-expressed genes participate in alcohol metabolism.
Project description:BackgroundChanges in gene expression levels during brain development are thought to have played an important role in the evolution of human cognition. With the advent of high-throughput sequencing technologies, changes in brain developmental expression patterns, as well as human-specific brain gene expression, have been characterized. However, interpreting the origin of evolutionarily advanced cognition in human brains requires a deeper understanding of the regulation of gene expression, including the epigenomic context, along the primate genome. Here, we used chromatin immunoprecipitation sequencing (ChIP-seq) to measure the genome-wide profiles of histone H3 lysine 4 trimethylation (H3K4me3) and histone H3 lysine 27 acetylation (H3K27ac), both of which are associated with transcriptional activation in the prefrontal cortex of humans, chimpanzees, and rhesus macaques.ResultsWe found a discrete functional association, in which H3K4me3HP gain was significantly associated with myelination assembly and signaling transmission, while H3K4me3HP loss played a vital role in synaptic activity. Moreover, H3K27acHP gain was enriched in interneuron and oligodendrocyte markers, and H3K27acHP loss was enriched in CA1 pyramidal neuron markers. Using strand-specific RNA sequencing (ssRNA-seq), we first demonstrated that approximately 7 and 2% of human-specific expressed genes were epigenetically marked by H3K4me3HP and H3K27acHP, respectively, providing robust support for causal involvement of histones in gene expression. We also revealed the co-activation role of epigenetic modification and transcription factors in human-specific transcriptome evolution. Mechanistically, histone-modifying enzymes at least partially contribute to an epigenetic disturbance among primates, especially for the H3K27ac epigenomic marker. In line with this, peaks enriched in the macaque lineage were found to be driven by upregulated acetyl enzymes.ConclusionsOur results comprehensively elucidated a causal species-specific gene-histone-enzyme landscape in the prefrontal cortex and highlighted the regulatory interaction that drove transcriptional activation.
Project description:We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex. We identified extensive layer-enriched expression signatures and refined associations to previous laminar markers. We overlaid our laminar expression signatures on large-scale single nucleus RNA-sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions in which morphological architecture is not as well defined as cortical laminae. Last, we created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research ( http://research.libd.org/spatialLIBD ).
Project description:Clinical trials and animal studies have indicated that long-term use or multiple administrations of anesthesia may lead to fine motor impairment in the developing brain. Most studies on anesthesia-induced neurotoxicity have focused on the hippocampus and prefrontal cortex (PFC); however, the role of other vital encephalic regions, such as the amygdala, is still unclear. Herein, we focused on sevoflurane, the most commonly used volatile anesthetic in infants, and performed a transcriptional analysis of the PFC and amygdala of macaques after multiple exposures to the anesthetic by RNA sequencing. The overall, overlapping, and encephalic region-specific transcriptional patterns were separately analyzed to reveal their functions and differentially expressed gene sets that were influenced by sevoflurane. Specifically, functional, protein-protein interaction, neighbor gene network, and gene set enrichment analyses were performed. Further, we built the basic molecular feature of the amygdala by comparing it to the PFC. In comparison with the amygdala's changing pattern following sevoflurane exposure, functional annotations of the PFC were more enriched in glial cell-related biological functions than in neuron and synapsis development. Taken together, transcriptional studies and bioinformatics analyses allow for an improved understanding of the primate PFC and amygdala.