Search Results (292)

Grape (Vitis vinifera spp.) accessions exhibit rich diversity, and understanding their genetic variation and evolutionary relationships is crucial for cultivar selection and utilization. A highly representative SNP marker set was developed in this study based on re-sequencing data analysis, to clarify the phylogenetic relationships among 96 grape accessions and to evaluate the genetic resolution of core markers. Using PN40024 as the reference genome, high-quality SNP loci were screened from resequencing data of the 96 accessions. A phylogenetic tree was constructed, and genetic diversity was analyzed using PCA and population structure analysis. The results showed that the 96 accessions were mainly divided into four groups: European (‘Merlot’, ‘Chardonnay’), American (‘Beta’, ‘Concord’), Euro-American hybrids (‘Vidal’, ‘Miguang’), and wild populations along with their hybrid progeny (‘Zuoyouhong’, ‘Huajia 8’). PCA and ADMIXTURE validated population differentiation, revealing clear separation between wild and cultivated accessions. Through screening of core SNP markers, 384,304 candidate SNPs suitable for probe design were identified. Further refinement yielded 2000 and 10,000 SNP markers. Detailed analysis of core marker characteristics showed that their minor allele frequency (MAF) was predominantly between 0.1 and 0.3, with the majority distributed in CDS (38.65%), intronic (30.2%), and intergenic regions. The most common mutation types were [A/G] (35%) and [C/T] (34%) transitions. The 2000 core SNPs were associated with 1220 functional genes and were significantly enriched in pathways such as protein binding, RNA transport, and plant–pathogen interaction. These findings provide an efficient tool for grape genetic diversity analysis, cultivar identification, and molecular breeding, laying the groundwork for the precise utilization of grape germplasm resources. Full article

Coxiella burnetii (C. burnetii) is a zoonotic pathogen with significant public and veterinary significance. Whilst livestock are considered as primary reservoirs of the pathogen, ticks play a crucial role in transmission and environmental contamination. Within Namibia, there is serological evidence of pathogen circulation in livestock and wildlife. However, no study has ever been conducted to determine the prevalence of C. burnetii in ticks in Namibia. Thus, this study investigated the prevalence and genetic diversity of C. burnetii in ticks collected from two different ecological settings. A total of 502 ticks (Rhipicephalus, Amblyomma, and Hyalomma) collected from 278 cattle (139 from each of the tropical Zambezi and arid Khomas regions) were screened for C. burnetii using PCR targeting the genus-specific 16S rRNA and the species-specific isocitrate dehydrogenase (icd) genes. Based on the isocitrate dehydrogenase (icd) genes, an overall prevalence of 8% (40/502) was observed for C. burnetii, with significantly higher infection rates observed in the more tropical Zambezi region (11.7%) when compared to the more arid Khomas region (2.8%) [p = 0.0005]. Variation was observed amongst tick species [p = 0.00121], with prevalence being slightly higher in Amblyomma ticks (12.9%) and Hyalomma (10.6%) as compared to Rhipicephalus ticks (3.6%). Phylogenetic analysis based on the icd gene sequences confirmed 99–100% identity with C. burnetii strains from around the world, thus confirming the circulation of this pathogen in ticks, ultimately supporting their potential role in the epidemiology of this pathogen in Namibia. The observed regional prevalence difference could be driven by variation in the ecological factors, with the subtropical climatic conditions of Zambezi likely favoring higher tick infection rates. Our findings highlight the need for One Health–based surveillance to mitigate the risks associated with pathogen risk. This study provides the first molecular evidence of C. burnetii in ticks in Namibia, highlighting their role in the pathogen’s epidemiology and providing relevant information for informed control strategies. Full article

Non-syndromic Inherited Retinal Dystrophies (IRDs) are a set of degenerative retinal diseases that vary clinically and genetically, including Leber congenital amaurosis (LCA) and retinitis pigmentosa (RP). IRDs are a significant cause of vision loss in young adults globally. To date, more than 280 genes have been associated with IRD pathogenesis. This study aims to investigate the genetic basis of non-syndromic IRD in the Qatari population and to assess the diagnostic yield of various genetic tests through a retrospective cohort study. Our study identified 49 eligible patients with IRD, 61.2% of whom were Qatari. Rod-dominated phenotypes accounted for 51% of the hereditary retinal diseases in this cohort. Whole-exome sequencing with mitochondrial genome testing (WES Plus) was the most frequently utilized genetic test. A total of 55 variants were identified across 32 IRD-associated genes. Of the 49 cases, 34 (69.4%) were initially classified as solved, and an additional five were likely to be solved based on familial segregation analysis. Variants in the ABCA4 gene were the most commonly observed, present in eight patients, with the c.5882G>A variant being the most recurrent, identified in three of these cases. Specific genes exhibited recurrent variations, including pan-ethnic variants that are common across multiple populations. These variants merit prioritization in testing due to their global prevalence. WES is recommended as a first-tier test for non-syndromic IRD cases, as it accelerates diagnosis, facilitates earlier interventions, and provides a comprehensive genetic picture by incorporating information from family members. Moreover, our study highlighted the significance of performing family segregation analyses in identifying possible causative variants. This is the first genetic study of IRD in Qatar, laying the groundwork for further research on the epidemiology and genetics of non-syndromic IRD in this understudied region. Full article

Heated tobacco products (HTPs) are marketed as lower-risk alternatives to conventional cigarettes; however, their toxicological impacts remain insufficiently characterized. This study evaluated the effects of HTP emissions on gene expression and mitochondrial function in comparison with conventional cigarettes. Whole cigarette smoke condensates (WCSCs), comprising both gas and particulate phases, were prepared from three commercially available HTPs and from 3R4F reference cigarettes. Human lung epithelial BEAS-2B cells were exposed to WCSCs at 3 μg nicotine/mL for 24 h, followed by transcriptome profiling using RNA sequencing. Principal component analysis demonstrated that HTP-WCSCs induced weaker gene expression changes than 3R4F-WCSC, with only modest variation among HTPs. Gene set enrichment analysis revealed that both HTP- and 3R4F-WCSCs significantly downregulated oxidative phosphorylation (OXPHOS)–related pathways, indicating potential mitochondrial impairment. Functional assays confirmed that both exposures elevated mitochondrial reactive oxygen species (ROS), while mitochondrial morphology, ATP production, membrane potential, and cytosolic ROS were largely unaffected. Collectively, these results show that although HTP emissions elicit weaker transcriptomic perturbations than conventional cigarette emissions, both converge on mitochondrial targets by suppressing OXPHOS gene expression and increasing mitochondrial ROS. Mitochondrial dysfunction may therefore represent a common mechanism underlying tobacco product toxicity. Full article

The genus Takydromus (grass lizards) represents a diverse and ecologically significant group of lacertid lizards widely distributed across East and Southeast Asia. However, phylogenetic relationships within the genus remain contentious, primarily due to limited molecular data and inconsistent results from previous studies based on single or few mitochondrial genes. This study aimed to (1) sequence and characterize the complete mitogenome of T. intermedius; (2) perform a comparative analysis of mitogenomic features across the genus; and (3) reconstruct a robust phylogeny to clarify intra-generic evolutionary relationships. The mitogenome of T. intermedius was 18,770 bp in size and contained the typical set of 37 genes. Comparative analyses revealed characteristic features including AT-richness, strand asymmetry, and considerable length variation in the control region attributable to tandem repeats. The ATP8 gene showed the highest nucleotide diversity, and all protein-coding genes were found to be under strong purifying selection. Phylogenetic trees were reconstructed from a concatenated dataset of 13 protein-coding genes and two rRNA genes using both maximum likelihood and Bayesian inference methods. The resulting phylogeny strongly supported the monophyly of Takydromus and resolved several species relationships; however, it did not support the recognition of Platyplacopus as a distinct subgenus. Moreover, our mitogenomic analysis strongly validates the forest-grassland ecological speciation hypothesis and the southern–northern lineage division in Takydromus. Our study provides valuable mitogenomic resources and underscores the utility of complete mitochondrial genomes in elucidating phylogenetic relationships within Takydromus. These findings lay a solid foundation for future taxonomic and evolutionary studies, although expanded species sampling is needed to fully understand the genus’s diversification history. Full article

Network pharmacology is a powerful approach for studying complex drug–target interactions and biological pathways. However, existing tools often require extensive manual intervention and lack integrated analysis capabilities. Here, we present NeXus v1.2, an automated platform for network pharmacology and multi-method enrichment analysis including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) that addresses these limitations. NeXus v1.2 enables the seamless integration of multi-layer biological relationships, handling complex interactions between genes, compounds, and plants while maintaining analytical rigor. The platform implements three enrichment methodologies: Over-Representation Analysis (ORA), GSEA, and GSVA, circumventing limitations associated with arbitrary threshold-based approaches. NeXus v1.2 was validated using multiple datasets spanning 111 to 10,847 genes, demonstrating robust scalability and performance across dataset sizes. The platform was initially tested using a representative dataset comprising 111 genes, 32 compounds, and 3 plants, showing consistent performance in processing various relationship patterns, including shared compounds between plants and multitargeted genes. The processing time for this dataset was 4.8 s with peak memory usage of 480 MB. Large-scale validation with datasets up to 10,847 genes confirmed scalability, with linear time complexity and completion times under 3 min. NeXus v1.2 automatically generates comprehensive visualizations, including network maps, enrichment analyses, and relationship patterns, while maintaining the biological context of interactions. The tool successfully processed and analyzed enrichment patterns across multiple functional domains, generating publication-quality visualization outputs at 300 DPI resolution. The platform demonstrated enhanced automation in handling incomplete relationship data and maintaining analytical integrity across different biological layers. Compared to manual workflows requiring 15–25 min, NeXus v1.2 reduced the analysis time to under 5 s (>95% reduction) while ensuring the comprehensive coverage of biological relationships. NeXus v1.2 provides improved automation and integration for network pharmacology analysis, offering an efficient and user-friendly platform for complex biological network analysis. Its modular architecture enables the future integration of AI technologies and expansion into various therapeutic applications. Full article

Indoor cat allergens, particularly the major allergen Fel d 1 protein, represent significant environmental triggers for allergic rhinitis, asthma, and other immune-related disorders in humans. With the continuous global increase in pet ownership, cat allergen proteins are prevalent in diverse settings and can even be transmitted to pet-free locations via clothing and animal fur, thereby posing health risks to sensitized individuals. This review systematically summarizes the molecular characteristics, distribution patterns, and mechanisms of human sensitization to indoor cat allergen proteins. It focuses on a comparative analysis of the principles, sensitivity, and application of commonly used immunological methods (such as various modified ELISAs, immunoblotting, and high-throughput multiplex detection technologies) alongside emerging real-time sensing platforms (including QCM, SAW, and LIF). Furthermore, this review summarizes key factors affecting indoor allergen concentrations, such as cat characteristics, architectural environments, human activities, and spatiotemporal variations. It also evaluates the efficacy and limitations of current allergy control strategies, covering source control (e.g., gene editing, immunomodulation), environmental management (e.g., air filtration), and medical treatments (e.g., allergen immunotherapy), and discusses future prospects. This review aims to offer a scientific foundation and systematic reference for the detection, control, and public health protection related to indoor cat allergens. Full article

Background/Objectives: Leeches constitute a pharmacologically significant animal group in traditional medicine due to their antithrombotic peptides, which include numerous members of the hirustasin gene superfamily. However, a comparative expression profile of this pharmaceutically important family across different leech species is lacking. Methods: This study conducted a comparative transcriptomic analysis of hirustasin gene superfamily expression in the hematophagous leech Hirudinaria manillensis and the non-hematophagous leech Whitmania pigra. Results: The total expression of the hirustasin gene superfamily, quantified as transcripts per million (TPM), showed no significant difference (p = 0.237) between H. manillensis (11,802.60 ± 1596.59) and W. pigra (8623.12 ± 965.96). However, both species exhibited pronounced intergenic expression heterogeneity. Five dominantly expressed genes (TPM > 1000) in H. manillensis and three in W. pigra were identified, collectively comprising 81% and 62% of the total hirustasin gene superfamily expression per species, respectively. Critically, the dominantly expressed genes exhibited no phylogenetic correspondence between species. Integrating expression profiles with phylogenetic reconstruction identified five high-potential candidate genes: poecistasin_Hman2, hirustasin_like_Hman01, hirustasin_like_Hman11, guamerin_Wpig, and bdellastasin_Wpig. Population-level analysis revealed marked population-specific expression patterns in H. manillensis, contrasting with minimal inter-population divergence in W. pigra. Nevertheless, geographically distinct populations of both species showed significant variation in the expression of their respective dominantly expressed genes. Conclusions: These findings provide a set of high-priority candidate genes and insights into their expression characteristics, serving as a starting point for subsequent functional validation and, when integrated with other screening methods, for future antithrombotic drug discovery. Full article

Rural tropical regions face escalating threats from zoonotic AIV and dengue virus but lack sewered infrastructure for conventional wastewater surveillance. We implemented surface water-based surveillance (SWBS) in peri-urban Dhaka (Bangladesh) and Ruili (China) from July to November 2023 and coupled it with machine learning-enhanced digital epidemiology. Reverse transcription quantitative PCR (RT-qPCR) was employed to detect the M gene of AIV and to subtype H1, H5, H7, H9, and H10 in surface water. Wild bird feces (n = 40) were collected within 3 km of positive sites to source-track AIV. For the dengue virus, a serogroup-specific RT-qPCR assay targeting the CprM gene was used. Genomic sequencing of AIV and dengue virus was performed to elucidate phylogenetic relationships with local clinical strains. Clinical data related to dengue fever were also collected for correlation analysis. Meanwhile, 13 dengue-related keyword search volumes were harvested daily from Google, Bing and Baidu for four cities to reveal the relationship between dengue epidemics and the web search index. AIV H5 was detected in Dhaka city from week 38, peaking at week 39, while dengue virus was persistently detected from week 29 to week 45, aligning with clinical trends. Time-series cross-correlation analysis revealed that variations in surface water viral load led clinical case reports by approximately two weeks (max CCF = 0.572 at lag −2). In Ruili city, dengue virus was detected from week 32 to week 44. To sharpen sensitivity, 383 weekly web search series for 13 dengue keywords from four countries were screened; random-forest and XGBoost models retained five symptom queries that generated a composite index explaining 79% of variance in dengue RNA levels in an independent Ruili test set (n = 24) and reduced superfluous sampling by 35%. Phylogenetic analysis verified identity between water-derived and patient-derived DENV-2, confirming local transmission. The study demonstrates that AIV SWBS is optimally integrated with wild bird sampling for source attribution, whereas dengue SWBS achieves maximal efficiency when combined with real-time web search monitoring, providing tailored, low-cost early-warning modules for resource-constrained tropical settings. Full article

Northern corn leaf blight is a major fungal disease hindering maize production worldwide. Among the various strategies of disease management, the deployment of host plant resistance is the most economic means to mitigate the yield losses, as it is cost-effective and durable. In this study, we performed the genome-wide association study (GWAS) analysis in a set of 336 maize inbred lines. The experimental material was evaluated for northern corn leaf blight disease response across two seasons during the rainy seasons of 2023 and 2024. The ANOVA results and estimates of genetic variability parameters indicated the existence of a substantial amount of genetic variability. High heritability and high genetic advance as percent mean suggested the presence of additive genetic effects in controlling the disease response. GWAS analysis was performed employing GLM, MLM, CMLM, MLMM, FarmCPU and BLINK. The results from GWAS identified 74 marker associations from GLM and FarmCPU models. The QTN S1_7356398, located on chromosome 1, identified from the GLM model, explained 12.12 percent of phenotypic variation. Another QTN S2_51098833 located on chromosome 2, identified from the FarmCPU model, explained 6.14 percent variation. Remaining associations explained lesser PVE, suggesting the quantitative inheritance of NCLB resistance. Candidate gene identification was performed by keeping B73 as a reference genome. The identified QTNs from the current study were found to be located in annotated genes with functional domains implicated in defence mechanisms in maize and other crops. Many candidate genes, including chitinase, putative serine/threonine protein kinase, and aldehyde oxygenase, were identified and found to play a crucial role in plant defence mechanisms against several biotic and abiotic stresses. Full article

Background/Objective: Biochemical recurrence (BCR) after radical prostatectomy (RP) for prostate cancer indicates disease progression. Although type 2 diabetes mellitus (T2D) shows a paradoxical association with prostate cancer risk, the prognostic role of T2D-related genetic variants remains unclear. Methods: We analyzed 113 common T2D susceptibility-related single-nucleotide polymorphisms (SNPs) in 644 Taiwanese men with localized prostate cancer (D’Amico risk classification: 12% low, 34% intermediate, and 54% high) treated with RP. Associations between SNPs and BCR were assessed using Cox regression, adjusting for key clinicopathological factors. Functional annotation was performed using HaploReg and FIVEx, while The Cancer Genome Atlas transcriptomic data were analyzed for C2 calcium-dependent domain-containing 4A (C2CD4A) expression. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were applied to explore related biological pathways. Results: C2CD4A SNP rs4502156 was independently associated with a reduced risk of BCR (hazard ratio = 0.80, p = 0.035). The protective C allele correlated with higher C2CD4A expression. Low C2CD4A expression is associated with advanced pathological stages, higher Gleason scores, and disease progression. GSEA revealed negative enrichment of mitotic and chromatid segregation pathways in high-C2CD4A-expressing tumors, with E2F targets being the most suppressed. GSVA confirmed an inverse correlation between C2CD4A expression and E2F pathway activity, with CDKN2C as a co-expressed functional gene. Conclusions: The T2D-related variant rs4502156 in C2CD4A independently predicts a lower risk of BCR, potentially via suppression of the E2F pathway, and may serve as a germline biomarker for postoperative risk stratification. Full article

Pediatric obesity is rising globally, and emerging evidence suggests that sleep timing may influence metabolic health through epigenetic mechanisms. This study investigated epigenome-wide DNA methylation patterns associated with bedtime in children and explored their biological relevance. Children aged 6–10 years were classified as early (≤8:30 PM) or late (>8:30 PM) bedtime groups. Saliva-derived DNA was analyzed using the Illumina Infinium MethylationEPIC BeadChip Array, and the Sparse Wrapper Algorithm (SWAG) was applied to identify differentially methylated loci. A total of 1006 CpG sites, representing 571 unique genes, were significantly associated with bedtime (p < 0.001). Significant methylation differences were observed between early and late bedtime groups, with ABCG2, ABHD4, MOBKL1A, AK3, SDE2, PRAMEF4, CREM, CDH4, BRAT1, and SDK1 showing the most consistent variation. Functional enrichment analyses (Gene Ontology, KEGG, and DisGeNET) conducted on the SWAG-identified gene set revealed enrichment in biological processes including peptidyl-lysin demethylation, regulation of sodium ion transport, DNA repair, and lipo-protein particle assembly. Key KEGG pathways included circadian entrainment, neurotransmission (GABAergic, dopaminergic, and glutamatergic), growth hormone synthesis, and insulin secretion. DisGeNET analysis identified associations with neurodevelopmental disorders and cognitive impairment. Cross-comparison with established sleep and obesity gene sets identified ten overlapping genes(CDH4, NR3C2, ACTG1, COG5, CAT, HDAC4, FTO, DOK7, OCLN, and ATXN1). These findings suggest that variations in bedtime during childhood may epigenetically modify genes regulating circadian rhythm, metabolism, neuronal connectivity, and stress response, potentially predisposing to later-life developmental, and metabolic challenges. Full article

Salmonella Enteritidis (SE) remains a leading cause of human illness worldwide, and its persistence in poultry environments might be partially attributed to their ability to form biofilm. This study compared the biofilm capacity of 15 SE and 24 Salmonella Kentucky (SK) isolates from poultry products and processing facilities to uncover genetic factors driving biofilm heterogeneity. Biofilm formation and curli/cellulose production were evaluated at 20–22 °C. Genomic analyses included phylogenetic reconstruction, comparative system profiling, SNP variation, and BLASTp v2.17.0 comparisons. Phenotypic assays showed that most SE isolates (73%) were strong biofilm formers, while the majority of SK isolates (62%) failed to form biofilms, despite many carrying the complete curli–cellulose gene set and other biofilm-associated genes. Genomic analysis identified 124 biofilm-related genes, 108 of which were conserved across all isolates, and revealed 24 variants with potential functional impact. Mutations in cellulose biosynthesis (bcs) genes were linked to weaker biofilms, whereas nonsynonymous variants in tol family genes may impair flagellar biosynthesis and matrix stability. These findings demonstrate that genetic variation, not just gene presence, shapes biofilm phenotypes and highlight key molecular targets that may explain why SE persists in poultry production while SK is less successful. Full article

Background/Objectives: Cancer is a chronic and heterogeneous disease, possessing molecular variation within a single type, resulting in its molecular subtypes. Cancer molecular subtyping offers biological insights into cancer variability, facilitating the development of personalized medicines. Various models have been proposed for cancer molecular subtyping, utilizing the high-dimensional transcriptomic, genomic, or proteomic data. The issue of data scarcity, characterized by high feature dimensionality and a limited sample size, remains a persistent problem.The objective of this research is to propose a deep learning framework, DeepCMS, that leverages the capabilities of feed-forward neural networks, gene set enrichment analysis, and feature selection to construct a well-representative subset of the feature space, thereby producing promising results. Methods: The gene expression data were transformed into enrichment scores, resulting in over 22,000 features. From those, the top 2000 features were selected, and deep learning was applied to these features. The encouraging outcomes indicate the efficacy of the proposed framework in terms of defining a well-representative feature space and accurately classifying cancer molecular subtypes. Results: DeepCMS consistently outperformed state-of-the-art models in aggregated accuracy, sensitivity, specificity, and balanced accuracy. The aggregated metrics surpassed 0.90 for all efficiency measures on independent test datasets, showing the generalizability and robustness of our framework. Although developed using colon cancer’s gene expression data, this approach may be applied to any gene expression data; a case study is also devised for illustration. Conclusions: Overall, the proposed DeepCMS framework enables the accurate and robust classification of cancer molecular subtypes using a compact and informative feature set, facilitating improved precision in oncology applications. Full article

Background: Obesity is a leading cause of type 2 diabetes (T2D), with particularly high prevalence in Hispanic populations residing in the USA. However, how genetic variation influences obesity-related blood metabolite levels which, in turn, contribute to T2D progression, is not well understood. Our goal was to identify and understand genetic and dietary connections between obesity and T2D in a Hispanic cohort of older adults. Materials and Methods: We conducted a genome-wide association study on 13 specific metabolites previously associated with T2D and characteristic of individuals with abdominal obesity within the Boston Puerto Rican Health Study cohort. We further examined associations of identified metabolite quantitative trait loci (mQTLs) and their interactions with targeted dietary factors on T2D prevalence and related traits. We used gene set and pathway analysis with protein–protein interaction networks to explore the molecular mechanisms underlying the metabolic connections between obesity and T2D. Results: We identified 30 single-nucleotide polymorphisms (SNPs) acting as mQTLs for these 13 metabolites. These mQTLs were located within 19 gene regions, associated with processes such as linoleic acid metabolism, alpha-linolenic acid metabolism, and glycerophospholipid biosynthesis. Although no mQTLs were directly associated with T2D or related traits, 12 demonstrated interactions with certain food groups that affect T2D risk. Moreover, gene set and pathway analysis with protein–protein interaction networks indicated that alpha-linolenic acid metabolism, lipid metabolism, and glycerophospholipid biosynthesis and metabolism among other pathways are potential connections between T2D and obesity. Conclusions: This study identifies biochemical relationships between genetic susceptibility and dietary influences, contributing to our understanding of T2D progression in Hispanic people with obesity. Full article