The role of circadian rhythm in the regulation of cellular protein profiles in the brain

Beker, Mustafa Çağlar; Kılıç, Ertuğrul

doi:10.3906/sag-2010-336

Cited by 8 publications

(5 citation statements)

References 32 publications

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“…The levels of Pde10a transcript and protein display daily rhythms, which could be seen in preparations of the whole retina. Other studies have revealed the role of Pde10a gene in the circadian regulation [ 46 , 47 ]. The network graph constructed from the dynamic partial correlation is presented in the Additional file 1 : Fig.…”

Section: Resultsmentioning

confidence: 99%

Inferring circadian gene regulatory relationships from gene expression data with a hybrid framework

Hu,

Jing,

et al. 2023

BMC Bioinformatics

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Background The central biological clock governs numerous facets of mammalian physiology, including sleep, metabolism, and immune system regulation. Understanding gene regulatory relationships is crucial for unravelling the mechanisms that underlie various cellular biological processes. While it is possible to infer circadian gene regulatory relationships from time-series gene expression data, relying solely on correlation-based inference may not provide sufficient information about causation. Moreover, gene expression data often have high dimensions but a limited number of observations, posing challenges in their analysis. Methods In this paper, we introduce a new hybrid framework, referred to as Circadian Gene Regulatory Framework (CGRF), to infer circadian gene regulatory relationships from gene expression data of rats. The framework addresses the challenges of high-dimensional data by combining the fuzzy C-means clustering algorithm with dynamic time warping distance. Through this approach, we efficiently identify the clusters of genes related to the target gene. To determine the significance of genes within a specific cluster, we employ the Wilcoxon signed-rank test. Subsequently, we use a dynamic vector autoregressive method to analyze the selected significant gene expression profiles and reveal directed causal regulatory relationships based on partial correlation. Conclusion The proposed CGRF framework offers a comprehensive and efficient solution for understanding circadian gene regulation. Circadian gene regulatory relationships are inferred from the gene expression data of rats based on the Aanat target gene. The results show that genes Pde10a, Atp7b, Prok2, Per1, Rhobtb3 and Dclk1 stand out, which have been known to be essential for the regulation of circadian activity. The potential relationships between genes Tspan15, Eprs, Eml5 and Fsbp with a circadian rhythm need further experimental research.

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Section: Resultsmentioning

confidence: 99%

Inferring circadian gene regulatory relationships from gene expression data with a hybrid framework

Hu,

Jing,

et al. 2023

BMC Bioinformatics

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“…Gng7 is the abnormal protein of dopaminergic signaling 56 . CPne5 is the circadian rhythm-related proteins, and circadian rhythm have a direct or indirect effect on the neurodegenerative processes 57 , and more importantly, the gene is involved in PD-induced toxins like paraquat 58 . In accordance with the expression characteristics of these genes (Fig.…”

Section: Resultsmentioning

confidence: 99%

Defining specific cell states of MPTP-induced Parkinson’s disease by single-nucleus RNA sequencing

Guo

Huang

et al. 2022

Preprint

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Parkinson's disease (PD), a neurodegenerative disease with the impairment of movement execution that is related to age, genetic and environmental factors. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyri-dine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on cell-gene of PD has not been fully elucidated. By single-nucleus RNA sequencing, we uncovered the PD-specific cells and revealed remarkable changes in their cellular states, including astrocytosis, endothelial cells absence, as well as a cluster of PD-exclusive medium spiny neuron cells. Furthermore, trajectory analysis of astrocyte and endothelial cells populations predicted candidate target gene sets that might be associated with PD. Notably, the detailed regulatory roles of astrocyte-specific transcription factors Dbx2 and Sox13 in PD were first revealed in our work. Finally, we characterized the cell-cell communications of PD-specific cells and found that the overall communication strength was enhanced in PD compared with matched control, especially the signaling pathways of NRXN and NEGR. Our work provides comprehensive overview on the changes of cellular states of the MPTP-induced mouse brain.

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“…PSMB6, also known as 20S proteasome subunit beta-1, codes for the β1 core catalytic subunit of the proteasome (Vriend and Marzban, 2017). A study showed that PSMB6 was a critical regulator of circadian rhythm, which may also have a direct or indirect effect on neurodegenerative diseases (Beker and KiliÇ, 2020). Mitochondrial ribosomal protein large 17 (MRPL17) and Mitochondrial ribosomal protein large 24 (MRPL24) are one of the 82 protein components of mitochondrial ribosomes, playing an essential role in the mitochondrial translation process, but their relationship with neurodegenerative diseases is currently unclear (Nottia et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Transcriptomic analysis identifies shared biological foundations between ischemic stroke and Alzheimer’s disease

Liu

Wan²,

Shi³

et al. 2022

Front. Neurosci.

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AimAlzheimer’s disease (AD) and ischemic stroke (IS), two major neurological diseases, are suggested to be associated in clinical and pathophysiological levels. Previous studies have provided some insights into the possible genetic mechanisms behind the correlation between AD and IS, but this issue is still not clear. We implemented transcriptomic analysis to detect common hub genes and pathways to help promote the understanding of this issue.Materials and methodsFour gene expression profiling datasets (GSE16561, GSE58294, GSE63060, and GSE63061) of peripheral whole blood, which contain 108 IS samples, 284 AD samples, and 285 matched controls, were employed to detect differentially expressed genes (DEGs) for AD and IS, which were further analyzed for shared biological pathways, candidate drugs, and transcription factors. Protein-protein interaction (PPI) network and drug-target interaction analysis were applied to identify hub genes and drug targets, respectively. Result verification was done with other independent datasets (GSE37587, GSE46480, and GSE140829). The difference in proportions of various immune cells in the peripheral blood of AD and IS patients were evaluated using CIBERSORT.ResultsWe identified 74 DEGs and 18 biological processes with statistical significance shared by AD and IS, 9 of which were immune-related pathways. Five hub genes scored high in the topological analysis of the PPI network, and we also found eight drug target genes and candidate drugs which were associated with AD and IS. As for immunological changes, an increase in the proportion of M0 macrophages was found in the peripheral circulation of both AD and IS patients, and SOD1 expression was significantly correlated with this change.ConclusionCollectively, the common DEGs and shared pathways found in this study suggest a potential shared etiology between AD and IS, behind which immune system, particularly the M0 macrophage elevation, might have important roles. While, the shared hub genes, potential therapeutic gene targets and drugs reported in this study provide promising treatment strategies for AD and IS.

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The role of circadian rhythm in the regulation of cellular protein profiles in the brain

Cited by 8 publications

References 32 publications

Inferring circadian gene regulatory relationships from gene expression data with a hybrid framework

Inferring circadian gene regulatory relationships from gene expression data with a hybrid framework

Defining specific cell states of MPTP-induced Parkinson’s disease by single-nucleus RNA sequencing

Transcriptomic analysis identifies shared biological foundations between ischemic stroke and Alzheimer’s disease

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