RNA-sequencing and Mathematical Modeling Identify Suite of Light-sensitive Circadian Genes in an Orb-web Weaving Spider

BackgroundMost organisms rely on a molecular circadian clock to orchestrate a wide range of physiological processes to match the 24-hour day. These molecular clocks are typically based on a negative feedback loop among a small set of proteins that govern the circadian output. Light or other environmental conditions can reset the circadian clock, but true circadian behaviors continue to cycle even in constant darkness, with an intrinsic period called the free-running period (FRP). Spiders have unusual FRPs, with some species having extremely short FRP (e.g. 18 hours for trashline orb weaver), and many having highly variable FRPs (intraspecific variation of up to 10 hours). In the absence of any genetic model of circadian rhythms in spiders, we developed a mathematical model to optimize experimental conditions for identifying circadian genes that also respond to light cues. ResultsOur mathematical model involved a single gene that encodes a protein that inhibits its own transcription. In our model, light degrades the circadian transcript, which allows a broad range of FRPs to be entrained to a 24-hour day. Our model predicted that exposing spiders to a pulse of light in the middle of the night would cause a pattern of expression between two later time points that was opposite the pattern exhibited by spiders who did not receive a pulse of light. RNA-sequencing of four groups of adult female orb weaving spiders, Metazygia wittfeldae, under these experimental conditions resulted in 528 significantly differentially expressed (DE) transcripts between the two collection times or between the light pulse and no light pulse. Consistent with our model, we found a cluster of transcripts with the flipped pattern of expression between the two collection times, dependent on the application of light.ConclusionsOur DE transcripts represent the first genetic evidence for circadian output in spiders. Furthermore, those transcripts with a flipped pattern of expression represent prime candidates for light-sensitive circadian genes, which may be involved in entraining the circadian clock to light. Functions of these genes varied from growth and development to reproduction to gene regulation, consistent with other circadian systems.

REGγ regulates circadian clock by modulating BMAL1 protein stability

Endogenous clocks generate rhythms in gene expression, which facilitates the organisms to cope through periodic environmental variations in accordance with 24-h light/dark time. A core question that needs to be elucidated is how such rhythms proliferate throughout the cells and regulate the dynamic physiology. In this study, we demonstrate the role of REGγ as a new regulator of circadian clock in mice, primary MEF, and SY5Y cells. Assessment of circadian conduct reveals a difference in circadian period, wheel mode, and the ability to acclimate the external light stimulus between WT and KO littermates. Compared to WT mice, REGγ KO mice attain the phase delay behavior upon light shock at early night. During the variation of 12/12 h light/dark (LD) exposure, levels of Per1, Per2, Cry1, Clock, Bmal1, and Rorα circadian genes in suprachiasmatic nucleus are significantly higher in REGγ KO than in WT mice, concomitant with remarkable changes in BMAL1 and PER2 proteins. In cultured cells depleted of REGγ, serum shock induces early response of the circadian genes Per1 and Per2 with the cyclic rhythm maintained. Mechanistic study indicates that REGγ directly degrades BMAL1 by the non-canonical proteasome pathway independent of ATP and ubiquitin. Silencing BMAL1 abrogates the changes in circadian genes in REGγ-deficient cells. However, inhibition of GSK-3β, a known promoter for degradation of BMAL1, exacerbates the action of REGγ depletion. In conclusion, our findings define REGγ as a new factor, which functions as a rheostat of circadian rhythms to mitigate the levels of Per1 and Per2 via proteasome-dependent degradation of BMAL1.

A Comparison of Different Approaches to Clinical Phenotyping of Lithium Response: A Proof of Principle Study Employing Genetic Variants of Three Candidate Circadian Genes

Optimal classification of the response to lithium (Li) is crucial in genetic and biomarker research. This proof of concept study aims at exploring whether different approaches to phenotyping the response to Li may influence the likelihood of detecting associations between the response and genetic markers. We operationalized Li response phenotypes using the Retrospective Assessment of Response to Lithium Scale (i.e., the Alda scale) in a sample of 164 cases with bipolar disorder (BD). Three phenotypes were defined using the established approaches, whilst two phenotypes were generated by machine learning algorithms. We examined whether these five different Li response phenotypes showed different levels of statistically significant associations with polymorphisms of three candidate circadian genes (RORA, TIMELESS and PPARGC1A), which were selected for this study because they were plausibly linked with the response to Li. The three original and two revised Alda ratings showed low levels of discordance (misclassification rates: 8–12%). However, the significance of associations with circadian genes differed when examining previously recommended categorical and continuous phenotypes versus machine-learning derived phenotypes. Findings using machine learning approaches identified more putative signals of the Li response. Established approaches to Li response phenotyping are easy to use but may lead to a significant loss of data (excluding partial responders) due to recent attempts to improve the reliability of the original rating system. While machine learning approaches require additional modeling to generate Li response phenotypes, they may offer a more nuanced approach, which, in turn, would enhance the probability of identifying significant signals in genetic studies.

Molecular Link between Circadian Rhythmicity and Mood Disorders

Background: The internal clock is driven by circadian genes [e.g., Clock, Bmal1, Per1-3, Cry1-2], hormones [e.g., melatonin, cortisol], as well as zeitgeber [‘synchronisers’]. Chronic disturbances in the circadian rhythm in patients diagnosed with mood disorders have been recognised for more than 50 years. Objectives: The aim of this review is to summarise the current knowledge and literature regarding circadian rhythms in the context of mood disorders, focussing on the role of circadian genes, hormones, and neurotransmitters. Method: The review presents the current knowledge and literature regarding circadian rhythms in mood disorders using the Pubmed database. Articles with a focus on circadian rhythms and mood disorders [n=123], particularly from 1973 to 2020, were included. Results: The article suggests a molecular link between disruptions in the circadian rhythm and mood disorders. Circadian disturbances, caused by the dysregulation of circadian genes, hormones, and neurotransmitters, often result in a clinical picture resembling depression. Conclusion: Circadian rhythms are intrinsically linked to affective disorders, such as unipolar depression and bipolar disorder.

The Histone Variant MacroH2A1 Impacts Circadian Gene Expression and Cell Phenotype in an In Vitro Model of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. A foremost risk factor for HCC is obesity/metabolic syndrome-related non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), which is prompted by remarkable changes in transcription patterns of genes enriching metabolic, immune/inflammatory, and circadian pathways. Epigenetic mechanisms play a role in NAFLD-associated HCC, and macroH2A1, a variant of histone H2A, is involved in the pathogenesis modulating the expression of oncogenes and/or tumor suppressor genes and interacting with SIRT1, which crucially impacts the circadian clock circuitry. Hence, we aimed to appraise if and how macroH2A1 regulated the expression patterns of circadian genes in the setting of NAFLD-associated HCC. We took advantage of an in vitro model of liver cancer represented by HepG2 (human hepatocarcinoma) cells stably knocked down for macroH2A1 and conducted whole transcriptome profiling and deep phenotyping analysis. We found up-regulation of PER1 along with several deregulated circadian genes, enriching several important pathways and functions related to cancer onset and progression, such as epithelial-to-mesenchymal transition, cell cycle deregulation, and DNA damage. PER1 silencing partially mitigated the malignant phenotype induced by the loss of macroH2A1 in HCC cells. In conclusion, our findings suggest a modulatory role for the core circadian protein PER1 in liver carcinogenesis in the context of a lack of the macroH2A1 epigenetic and transcriptional landscape.

Identification of a circadian gene signature that predicts overall survival in lung adenocarcinoma

Background Lung adenocarcinoma (LUAD) is one of the most common subtypes of lung cancer which is the leading cause of death in cancer patients. Circadian clock disruption has been listed as a likely carcinogen. However, whether the expression of circadian genes affects overall survival (OS) in LUAD patients remains unknown. In this article, we identified a circadian gene signature to predict overall survival in LUAD. Methods RNA sequencing (HTSeq-FPKM) data and clinical characteristics were obtained for a cohort of LUAD patients from The Cancer Genome Atlas (TCGA). A multigene signature based on differentially expressed circadian clock-related genes was generated for the prediction of OS using Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and externally validated using the GSE72094 dataset from the GEO database. Results Five differentially expressed genes (DEGs) were identified to be significantly associated with OS using univariate Cox proportional regression analysis (P < 0.05). Patients classified as high risk based on these five DEGs had significantly lower OS than those classified as low risk in both the TGCA cohort and GSE72094 dataset (P < 0.001). Multivariate Cox regression analysis revealed that the five-gene-signature based risk score was an independent predictor of OS (hazard ratio > 1, P < 0.001). Receiver operating characteristic (ROC) curves confirmed its prognostic value. Gene set enrichment analysis (GSEA) showed that Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to cell proliferation, gene damage repair, proteasomes, and immune and autoimmune diseases were significantly enriched. Conclusion A novel circadian gene signature for OS in LUAD was found to be predictive in both the derivation and validation cohorts. Targeting circadian genes is a potential therapeutic option in LUAD.

Investigating the contributions of circadian pathway and insomnia risk genes to autism and sleep disturbances

Sleep disturbance is prevalent in youth with Autism Spectrum Disorder (ASD). Researchers have posited that circadian dysfunction may contribute to sleep problems or exacerbate ASD symptomatology. However, there is limited genetic evidence of this. It is also unclear how insomnia risk genes identified through GWAS in a general population are related to ASD risk and common sleep problems like insomnia in ASD. We investigated the contribution of copy number variants (CNVs) encompassing circadian pathway genes and insomnia risk genes to ASD risk as well as parent reported sleep disturbances in children diagnosed with ASD. We studied 5860 ASD probands and 2092 unaffected siblings from the Simons Simplex Collection and MSSNG database, as well as 7463 individuals from two unselected populations (IMAGEN and Generation Scotland). We identified 320 and 626 rare CNVs encompassing circadian genes and insomnia risk genes respectively. Deletions and duplications with circadian genes were overrepresented in ASD probands compared to siblings and unselected controls. For insomnia-risk genes, deletions (but not duplications) were also associated with ASD. Results remained significant after adjusting for cognitive ability. CNVs containing circadian pathway and insomnia risk genes showed a stronger association with ASD, compared to CNVs containing other genes. Duplications containing circadian genes were associated with shorter sleep duration(22 minutes). Only insomnia risk genes intolerant to haploinsufficiency increased insomnia traits when duplicated. Overall, CNVs encompassing circadian and insomnia risk genes increase ASD risk despite small impacts on sleep disturbances.