Mammalian Genome最新文献

Osteoporosis, characterized by decreased bone mineral density, is a common skeletal disorder in the aging population. Cellular senescence is a key factor in the pathophysiology of osteoporosis. This study aimed to identify senescence-related biomarkers and evaluate the functional role in osteoporosis by integrating microarray analysis, Mendelian randomization (MR), and experimental validation. Osteoporosis-related microarray dataset was downloaded from the Gene Expression Omnibus database for differential expression analysis. We integrated summary-level data from genome-wide association studies on osteoporosis with protein quantitative trait loci data to identify genes with causal relationships to osteoporosis. The senescence-related biomarker gene was identified using the SenMayo gene set and evaluated for the predictive performance through receiver operating characteristic (ROC) curve analysis. Functional enrichment analysis was conducted to explore the underlying mechanisms. Validation of gene expression was performed using quantitative real-time PCR in 50 clinical samples from patients with osteoporosis and controls. A total of 33 differentially expressed genes were identified between osteoporosis and control samples. MR analysis revealed 90 genes with causal effects on osteoporosis. Subsequently, CXCL1 was identified as the key senescence-related biomarker gene. ROC curve analysis demonstrated good predictive performance with an area under the curve value of 0.708. Functional enrichment analysis showed a significant association between CXCL1 and immune-related pathways in osteoporosis. The expression of the gene was successfully validated in clinical samples. This study identified and validated CXCL1 as a senescence-related biomarker with causal effects on osteoporosis through a combination of microarray analysis, MR, and experimental validation. These findings offer insights into the molecular mechanisms of osteoporosis and could inform the development of treatment strategies.

Zinc finger and SCAN domain-containing (ZSCAN) family members have been implicated in cancer progression. This paper was to assess the role of ZSCAN18 in oral squamous cell carcinoma (OSCC). The OSCC datasets were obtained from the GEO database, and the differentially expressed gene ZSCAN18 was screened for the next analysis. ZSCAN18 protein levels in OSCC tissues and cell lines were investigated. ZSCAN18 was manually overexpressed in OSCC cells to analyze cell proliferation, invasion, migration, and stemness. The protein level of GLI1, a marker protein of the Hedgehog pathway, was detected to determine the effect of ZSCAN18 on this signaling pathway. A mouse xenograft tumor model was constructed to observe tumor growth. Rescue experiments were designed to validate the impact of the FOXP2/ZSCAN18 axis on OSCC. ZSCAN18 was lowly expressed in OSCC and predicted poor prognoses. ZSCAN18 overexpression inhibited OSCC progression, tumor cell stemness, and the Hedgehog pathway. FOXP2, an upstream transcription factor of ZSCAN18, transcriptionally activated ZSCAN18. Rescue experiments further confirmed that FOXP2 transcriptionally activated ZSCAN18 and thus inhibited stemness and tumor growth. Collectively, FOXP2 mediates ZSCAN18 transcriptional activation to inhibit OSCC by blocking Hedgehog signaling.

Non-Small Cell lung cancer (NSCLC) is known for its fast progression, metastatic potency, and a leading cause of mortality globally. At diagnosis, approximately 30-40% of NSCLC patients already present with metastasis. Epithelial to mesenchymal transition (EMT) is a developmental program implicated in cancer progression and metastasis. Transforming Growth Factor-β (TGFβ) and its signalling plays a prominent role in orchestrating the process of EMT and cancer metastasis. In present study, a comprehensive molecular interaction map of TGFβ induced EMT in NSCLC was developed through an extensive literature survey. The map encompasses 394 species interconnected through 554 reactions, representing the relationship and complex interplay between TGFβ induced SMAD dependent and independent signalling pathways (PI3K/Akt, Wnt, EGFR, JAK/STAT, p38 MAPK, NOTCH, Hypoxia). The map, built using Cell Designer and compliant with SBGN and SBML standards, was subsequently translated into a logical modelling framework using CaSQ and dynamically analysed with Cell Collective. These analyses illustrated the complex regulatory dynamics, capturing the known experimental outcomes of TGFβ induced EMT in NSCLC including the co-existence of hybrid EM phenotype during transition. Hybrid EM phenotype is known to contribute for the phenotypic plasticity during metastasis. Network-based analysis identified the crucial network level properties and hub regulators, while the transcriptome-based analysis cross validated the prognostic significance and clinical relevance of key regulators. Overall, the map developed and the subsequent analyses offer deeper understanding of the complex regulatory network governing the process of EMT in NSCLC.

Genome editing, in particular the CRISPR/Cas9 system, is widely used to generate new animal models. However, the generation of mutations, such as conditional knock-out or knock-in, can remain complex and inefficient, in particular because of the difficulty to deliver the donor DNA (single or double stranded) into the nucleus of fertilized oocytes. The use of recombinant adeno-associated viruses (rAAV) as donor DNA is a rapidly developing approach that promises to improve the efficiency of creation of animal models. In this mini-review, we explore the progress and challenges of using CRISPR/Cas9 in combination with rAAV for precise genome editing. We will summarise the current knowledge of rAAV transduction, data on its use in rodent embryos in combination with CRISPR/Cas9 to easily generate sequence replacements or insertions, the limitations of rAAV and the unexpected events observed to date, and the protocol optimisations already in place to facilitate its use in the generation of animal models.

Recent advances in the development of pre-clinical models based on non-animal technologies (NATs) have stimulated expectations that the use of animals in research may soon be phased out. The true value of innovations in NATs and their applications lies, however, in enabling an expanded and integrated portfolio of complementary animal and non-animal model systems to improve the accuracy and efficiency of pre-clinical research and therapeutic development. The term NATs covers a range of techniques spanning in silico, cell free, organ-on-chip as well as in vitro techniques including three-dimensional cell culture models termed organoids. Of these, in vitro systems are currently the most broadly used in biomedicine laboratories and are the first NATs for which Australia has invested in nationwide support. The focus of this commentary is the importance of understanding the strengths and limitations of in vitro and animal models such that an integrated portfolio of complementary genetic models continues to evolve to best support pre-clinical research and therapeutic development pipelines.

The causal relationships between neuroticism and osteoarthritis (OA) were inconclusive in observational studies. We conducted bidirectional two-sample Mendelian randomization (MR) and transcriptome-wide association studies to determine the associations and the underlying transcriptomic basis. The summary-level genome-wide association study data for any site OA, knee OA, erosive hand OA, and hip OA were mainly derived from UK Biobank, and neuroticism was derived from CTGlab. We then utilized weighted regression and propensity score matching (PSM) models to investigate the relationship between neuroticism and OA in 11,948 participants of European ancestry from the National Health and Nutrition Examination Survey from 2005 to 2018. Bidirectional two-sample MR studies revealed that feelings of being fed-up, a sense of miserableness, mood swings, and a higher neuroticism score were all linked to an increased risk of OA. These factors were specifically associated with OA at various sites, including the knee. Conversely, there was no evidence to suggest that OA had any influence on traits related to neuroticism. In a comprehensive analysis that accounted for variables such as age, sex, blood lipids, blood glucose, body weight, smoking, alcohol consumption, and physical activity, it was determined that mental fluctuation significantly increased the incidence of self-reported OA (OR 1.37, 95% CI 1.20-1.58, P < 0.001) based on weighted regression. Further confirmation was provided by PSM analysis, which showed that mental fluctuation was associated with a higher incidence of self-reported OA (OR 1.28, 95% CI 1.08-1.52, P = 0.004). Moreover, differentially expressed genes were enriched in several biological processes, including the cell cycle, lipid metabolism, RNA processing, and immuno-inflammatory responses. The results revealed significant genetic and population-based associations, as well as underlying mechanisms, between neuroticism and osteoarthritis, supporting the concept of a brain-joint axis.

Neutrophil extracellular traps (NETs) are increasingly recognized for their involvement in ischemic stroke (IS), yet their precise contribution to IS outcomes is not fully understood. This study aims to elucidate the role of NETs in IS progression and identify potential biomarkers and therapeutic targets. In this study, mice were subjected to middle cerebral artery occlusion (MCAO). RNA sequencing was conducted on brain tissue samples to identify differentially expressed genes (DEGs) using the "limma" package. The diagnostic potential of these biomarkers was assessed using receiver operating characteristic (ROC) curve analysis. Additionally, single-cell RNA sequencing data were analyzed with the Seurat package to further investigate the cellular dynamics. We identified DEGs, and NETs-related genes associated with IS progression. Specifically, Ceacam3, Tnf, Selp, and Fcgr4 were found to be upregulated in MCAO samples, exhibiting diagnostic value as biomarkers for IS. Immune infiltration analysis indicated associations between these genes and various immune cell types. Gene Set Enrichment Analysis (GSEA) revealed their involvement in IS-related pathways, including ferroptosis, IL-17 signaling, leukocyte transendothelial migration, necroptosis, and NETs formation. Single-cell data confirmed the expression of Tnf, Selp, and Fcgr4 in neutrophils. CellChat analysis uncovered key cell-cell interactions in IS, emphasizing the role of neutrophils in communicating with microglia and T cells via the JAM pathway, with Thbs1 and Cd47 as key mediators. The findings provide insights into the cellular and molecular mechanisms underlying IS and may pave the way for novel therapeutic strategies targeting NETs in IS patients.

The mitochondria-associated endoplasmic reticulum membrane is implicated in atherosclerosis (AS). However, its precise molecular mechanisms remain undefined. This study identified KLRC1 and SOCS2 as key protective genes against AS through transcriptomic analysis integrated with Mendelian randomization. Both genes exhibited significantly reduced expression in the AS group. Immune infiltration analysis revealed a strong positive correlation between activated CD8⁺ T cells and these genes, while eosinophils displayed the most pronounced negative correlation with KLRC1, and regulatory T cells exhibited the strongest negative association with SOCS2. Notably, SOCS2 emerged as a pivotal protective factor, offering novel insights into AS pathogenesis and providing a robust theoretical foundation for early diagnosis and potential therapeutic strategies.

Globally, male infertility (MI) is a major concern. Several other comorbidities related to MI are testicular germ cell tumor (TGCT) and prostate adenocarcinoma (PRAD). This study focuses on finding the common biomarkers among these diseases and their interaction with Melatonin (MLT). The differential expressed genes were retrieved using the GEPIA2 database for TGCT and PRAD, whereas the DISGENET database for MI-related genes. InteractiVenn was performed in response to identify the common genes. The STAG3, RNF212, DDX3Y, DPY19L2, TPCN1, KLK3, GNRH1, DMD, CCDC146, and DNAH1 are found to be involved in all these diseases. The gene ontologies and pathway enrichment analysis were done for these significant genes in response to identifying and accessing the involvement of these genes in other processes. MLT is a neuroendocrine hormone with high therapeutic properties. MLT showed the best binding energy with DDX3Y among all the proteins. Molecular dynamic simulation (MDS) of MLT with DDX3Y was performed and found to be -52.382 ± 13.110 kJ/mol binding energy. The RMSD, RMSF, SASA, RG, H-bond, FEL, PCA, and MM-PBSA analysis confirm the stability and compactness of the DDX3Y-MLT complex. The MDS results indicate that MLT is a promising therapeutic option for enhancing DDX3Y expression, which will support spermatogenesis. Additionally, the hub genes were identified based on MCC parameters from the merged interactive network of common genes in response to finding significant genes that can be a potential biomarker for the diagnosis of diseases.

Oxidative stress influences the tumor microenvironment, driving breast cancer progression and drug resistance. This study aimed to develop a prognostic gene signature based on oxidative stress-related genes (OSRGs) to assess patient outcomes and immune status. UCSC Xena ( http://xena.ucsc.edu/ ) and GEO ( https://www.ncbi.nlm.nih.gov/geo/ ) databases were used to obtain RNA-seq data and corresponding clinical information. The classification of OSRG subtypes was performed using consensus cluster. The oxidative stress related scoring (OSRS) model was established combining Lasso regression and multivariable Cox regression. The analysis of tumor mutation burden (TMB) and somatic mutation were carried out using the R package 'maftools'. Python package 'pySCENIC' was used to construct and analyze the transcription factor network. Additionally, immune infiltration was analyzed using R packages 'CIBERSORT' and 'ESTIMATE'. Three OSRG subgroups were identified and the Differentially Expressed Genes (DEGs) among them were enriched in humoral immunity, cytokine communication and drug metabolism pathways. OSRS model was established based on the DEGs and revealed association with patients' overall survival, somatic mutations, immune statuses, and drug resistance. Finally, transcription factor TFAP2B was identified as a key regulatory factor in high OSRS cells, and associated with a negative prognostic outcome in Basal-like breast cancer patients.