Most organisms have evolved specific mechanisms to respond to changes in environmental conditions such as light and temperature over the course of day. These periodic changes in the physiology and behaviour of organisms, referred to as circadian rhythms, are a consequence of intricate molecular mechanisms in the form of transcription and translational feedback loops. The plant circadian regulatory network is a complex web of interconnected feedback loops involving various transcription factors such as CCA1, LHY, PRRs, TOC1, LUX, ELF3, ELF4, RVE8, and more. This network enables plants to adapt and thrive in diverse environmental conditions. It responds to entrainment signals, including light, temperature, and nutrient concentrations and interacts with most of the physiological functions such as flowering, growth and stress response. Mathematical modelling of these gene regulatory networks enables a deeper understanding of not only the function but also the perturbations that may affect the plant growth and function with changing climate. Over the years, numerous mathematical models have been developed to understand the diverse aspects of plant circadian regulation. In this review, we have delved into the systematic development of these models, outlining the model components and refinements over time. We have also highlighted strengths and limitations of each of the models developed so far. Finally, we conclude the review by describing the prospects for investigation and advancement of these models for better understanding of plant circadian regulation.

Comprehension of the genetic basis of temperament has been improved by recent advances in the identification of genes and genetic variants. However, due to the complexity of the temperament traits, the elucidation of the genetic architecture of temperament is incomplete. A systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to analyze candidate genes related to bovine temperament, using bovine as the population, SNPs and genes as the exposure, and temperament test as the outcome, as principal search terms for population, exposure, and outcome (PEO) categories to define the scope of the search. The search results allowed the selection of 36 articles after removing duplicates and filtering by relevance. One hundred-two candidate genes associated with temperament traits were identified. The genes were further analyzed to construct an interaction network using the STRING database, resulting in 113 nodes and 346 interactions and the identification of 31 new candidate genes for temperament. Notably, the main genes identified were SST and members of the Kelch family. The candidate genes displayed interactions with pathways associated with different functions such as AMPA receptors, hormones, neuronal maintenance, protein signaling, neuronal regulation, serotonin synthesis, splicing, and ubiquitination activities. These new findings demonstrate the complexity of interconnected biological processes that regulate behavior and stress response in mammals. This insight now enables our targeted analysis of these newly identified temperament candidate genes in bovines.

Alternative RNA splicing provides cells with transcriptomic and proteomic diversity by adding another layer of regulation to gene expression. Accumulating evidence has revealed that defects in alternative splicing contribute to a variety of features of cancer development, including the modulation of cancer heterogeneity, evasion of apoptosis of cancer cells, rewiring cancer metabolism and facilitating cancer metastasis via fine‑tuning the epithelial‑to‑mesenchymal transition process. In this review, well‑known aberrant alternative splicing events associated with multiple aspects of cancer progression were presented based on available data obtained from an extensive literature search used to construct splicing regulatory networks for each of these events. The study aims to provide a more comprehensive understanding of cancer‑associated splicing networks and more precise guidance for targeting these events for cancer treatment.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD), and its pathogenesis has not been clarified. Current research suggests that DKD involves multiple cell types and extra-renal factors, and it is particularly important to clarify the pathogenesis and identify new therapeutic targets. Single-cell RNA sequencing (scRNA-seq) technology is high-throughput sequencing of the transcriptomes of individual cells at the single-cell level, which is an effective technology for exploring the development of diseases by comparing genetic information, reflecting the differences in genetic information between cells, and identifying different cell subpopulations. Accumulating evidence supports the role of scRNA-seq in revealing the pathogenesis of diabetes and strengthening our understanding of the molecular mechanisms of DKD. We reviewed the scRNA-seq data this time. Then, we analyzed and discussed the applications of scRNA-seq technology in DKD research, including annotation of cell types, identification of novel cell types (or subtypes), identification of intercellular communication, analysis of cell differentiation trajectories, gene expression detection, and analysis of gene regulatory networks, and lastly, we explored the future perspectives of scRNA-seq technology in DKD research.

Atherosclerosis (AS) causes thickening and hardening of the arterial wall due to accumulation of extracellular matrix, cholesterol, and cells. In this study, we used comprehensive bioinformatics tools and machine learning approaches to explore key genes and molecular network mechanisms underlying AS in multiple data sets. Next, we analyzed the correlation between AS and immune fine cell infiltration, and finally performed drug prediction for the disease. We downloaded GSE20129 and GSE90074 datasets from the Gene expression Omnibus database, then employed the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts algorithm to analyze 22 immune cells. To enrich for functional characteristics, the black module correlated most strongly with T cells was screened with weighted gene co-expression networks analysis. Functional enrichment analysis revealed that the genes were mainly enriched in cell adhesion and T-cell-related pathways, as well as NF-κ B signaling. We employed the Lasso regression and random forest algorithms to screen out 5 intersection genes (CCDC106, RASL11A, RIC3, SPON1, and TMEM144). Pathway analysis in gene set variation analysis and gene set enrichment analysis revealed that the key genes were mainly enriched in inflammation, and immunity, among others. The selected key genes were analyzed by single-cell RNA sequencing technology. We also analyzed differential expression between these 5 key genes and those involved in iron death. We found that ferroptosis genes ACSL4, CBS, FTH1 and TFRC were differentially expressed between AS and the control groups, RIC3 and FTH1 were significantly negatively correlated, whereas SPON1 and VDAC3 were significantly positively correlated. Finally, we used the Connectivity Map database for drug prediction. These results provide new insights into AS genetic regulation.

BACKGROUND: Stent restenosis is a relatively common phenomenon among patients with coronary heart disease undergoing percutaneous coronary intervention (PCI). It seems that a set of clinical, laboratory, and even genetic factors make people susceptible to such a phenomenon and in fact, this is multi-factorial. We aimed to first determine the underlying clinical and laboratory risk factors for the occurrence of stent re-stenosis after PCI based on a systematic review study, and after that, through a bioinformatics study, to evaluate the related genes and microRNAs with the occurrence of stent re-stenosis.
METHODS: In the first step, the manuscript databases including Medline, Web of Knowledge, Google Scholar, Scopus, and Cochrane were deeply searched by the two blinded investigators for all eligible studies based on the considered keywords to introduce clinical and laboratory determinants of stent re-stenosis. In the bioinformatic phase, and following a review of the literature to identify genes and microRNAs involved in restenosis, the interaction of each gene with other genes associated with stent re-stenosis was determined by GeneMANIA network analysis and Cytoscape software. Overall, 67 articles (including 40,789 patients) on clinical and biochemical predictors for stent restenosis and 25 articles on genetic determinants of this event were eligible for the final analysis. The predictors for this event were categorized into four subgroups patient-based parameters including traditional cardiovascular risk profiles, stent-based parameters including type and diametric characteristics of the stents used, coronary lesion-based parameters including several two target lesions and coronary involvement severity and laboratory-based parameters particularly related to activation of inflammatory processes. In the bioinformatic phase, we uncovered 42 genes that have been described to be involved in such a phenomenon considering a special position for genes encoding inflammatory cytokines. Also, 12 microRNAs have been pointed to be involved in targeting genes involved in stent re-stenosis.
CONCLUSIONS: The incidence of stent re-stenosis will be the result of a complex interaction of clinical risk factors, laboratory factors mostly related to the activation of inflammatory processes, and a complex network of gene-to-gene interactions.

Breast cancer (BC) is a global health concern, and development of diagnostic tools and targeted treatments for BC remains challenging. Therapeutic approaches for BC often involve a combination of surgery, radiation therapy, chemotherapy, targeted therapy, and hormone therapy. In recent years, there has been a growing interest in the role of noncoding RNAs (ncRNAs), including long ncRNAs (lncRNAs) and microRNAs (miRNAs), in BC and their therapeutic implications. Various biological processes such as cell proliferation, migration, and apoptosis rely on the activities of these ncRNAs, and their dysregulation has been implicated in BC progression. The regulatory function of the competitive endogenous RNA (ceRNA) network, which comprises lncRNAs, miRNAs, and mRNAs, has been the subject of extensive pathophysiological research. Most lncRNAs serve as molecular sponges for miRNAs and sequester their activities, thereby regulating the expression of target mRNAs and contributing to the promotion or inhibition of BC progression. This review summarizes recent findings on the role of ceRNA networks in BC progression, metastasis, and therapeutic resistance, and highlights the association of ceRNA networks with transcription factors and signaling pathways. Understanding the ceRNA network can lead to the discovery of biomarkers and targeted treatment methods to prevent the spread and metastasis of BC.

Circular RNA (circRNA), a type of non‑coding RNA, plays a regulatory role in biological processes. The special loop structure of circRNA makes it highly stable and specific in diseased tissues and cells, especially in tumors. Competing endogenous RNAs (ceRNAs) compete for the binding of microRNA (miRNA) at specific binding sites and thus regulate gene expression. ceRNAs play an important role in various diseases and are currently recognized as the most prominent mechanism of action of circRNAs. circRNAs can modulate the proliferation, migration, invasion and apoptosis of tumor cells through the ceRNA mechanism. With further research, circRNAs may serve as novel markers and therapeutic targets for ovarian cancer (OC). In the present review, the research progress of circRNAs as ceRNAs in OC was summarized, focusing on the effects of the circRNA/miRNA/mRNA axis on the biological functions of OC cells through mediating pivotal signaling pathways. The role of circRNAs in the diagnosis, prognostic assessment and treatment of OC was also discussed in the present review.

Changes in the nervous system are related to a wide range of mental disorders, which include neurodevelopmental disorders (NDD) that are characterized by early onset mental conditions, such as schizophrenia and autism spectrum disorders and correlated conditions (ASD). Previous studies have shown distinct genetic components associated with diverse schizophrenia and ASD phenotypes, with mostly focused on rescuing neural phenotypes and brain activity, but alterations related to vision are overlooked. Thus, as the vision is composed by the eyes that itself represents a part of the brain, with the retina being formed by neurons and cells originating from the glia, genetic variations affecting the brain can also affect the vision. Here, we performed a critical systematic literature review to screen for all genetic variations in individuals presenting NDD with reported alterations in vision. Using these restricting criteria, we found 20 genes with distinct types of genetic variations, inherited or de novo, that includes SNP, SNV, deletion, insertion, duplication or indel. The variations occurring within protein coding regions have different impact on protein formation, such as missense, nonsense or frameshift. Moreover, a molecular analysis of the 20 genes found revealed that 17 shared a common protein-protein or genetic interaction network. Moreover, gene expression analysis in samples from the brain and other tissues indicates that 18 of the genes found are highly expressed in the brain and retina, indicating their potential role in adult vision phenotype. Finally, we only found 3 genes from our study described in standard public databanks of ophthalmogenetics, suggesting that the other 17 genes could be novel target for vision diseases.

To identify genes that may play a role in urethral stricture and summarize the results of studies that have documented variations in gene expression among individuals with urethral stricture compared to healthy individuals.
A systematic search was conducted in Cochrane, Ovid, Web of Science, and PubMed, limiting the results to articles published between January 1, 2000 and January 30, 2023. Only studies comparing the difference in gene expression between individuals with urethral stricture and healthy individuals utilizing molecular techniques to measure gene expression in blood, urine, or tissue samples were included in this systematic review. Gene network and pathway analyses were performed using Cytoscape software, with input data obtained from our systematic review of differentially expressed genes in urethral stricture.
Four studies met our criteria for inclusion. The studies used molecular biology methods to quantify gene expression data from specimens. The analysis revealed gene expressions of CXCR3 and NOS2 were downregulated in urethral tissue samples, while TGFB1, UPK3A, and CTGF were upregulated in plasma, urine and urethral tissue samples, respectively, in patients with urethral stricture compared to healthy controls. The analysis demonstrated that the most significant pathways were associated with phosphoinositide 3-kinase (PI3 kinase) and transforming growth factor beta 1/suppressor of mothers against decapentaplegic (TGF-β1/SMAD) signaling pathways.
This systematic review identified gene expression variations in several candidate genes and identified underlying biological pathways associated with urethral stricture. These findings could inform further research and potentially shift treatment and prevention strategies for urethral stricture.