Search Results (43,126)

Isocitrate dehydrogenase wild-type glioblastoma, a Grade 4 malignant brain neoplasm, remains resistant to multimodal treatment, with a median survival of 16 months from diagnosis with no geographical bias. Despite increasing appreciation of intra-tumour genotypic variation and stem cell plasticity, such knowledge has yet to translate to efficacious molecular targeted therapies in this post-genomic era. Critically, the manifestation of molecular heterogeneity and stem cell biological process within clinically relevant infiltrative disease is little understood. Here, we review the interactions between neural plasticity, intra-tumour heterogeneity and residual infiltrative disease, and we draw upon antibiotic resistance as an insightful analogy to further explain tumour heterogeneity. Full article

Objectives: To provide a basis for further research on the molecular mechanisms underlying type 2 diabetes-associated mild cognitive impairment (DCI) using two bioinformatics methods to screen key genes involved in the progression of mild cognitive impairment (MCI) and type 2 diabetes. Methods: RNA sequencing data of MCI and normal cognition groups, as well as expression profile and sample information data of clinical characteristic data of GSE63060, which contains 160 MCI samples and 104 normal samples, were downloaded from the GEO database. Hub genes were identified using weighted gene co-expression network analysis (WGCNA). Protein–protein interaction (PPI) analysis, combined with least absolute shrinkage and selection operator (LASSO) and receiver operating characteristic (ROC) curve analyses, was used to verify the genes. Moreover, RNA sequencing and clinical characteristic data for GSE166502 of 13 type 2 diabetes samples and 13 normal controls were downloaded from the GEO database, and the correlation between the screened genes and type 2 diabetes was verified by difference and ROC curve analyses. In addition, we collected clinical biopsies to validate the results. Results: Based on WGCNA, 10 modules were integrated, and six were correlated with MCI. Six hub genes associated with MCI (TOMM7, SNRPG, COX7C, UQCRQ, RPL31, and RPS24) were identified using the LASSO algorithm. The ROC curve was screened by integrating the GEO database, and revealed COX7C, SNRPG, TOMM7, and RPS24 as key genes in the progression of type 2 diabetes. Conclusions: COX7C, SNRPG, TOMM7, and RPS24 are involved in MCI and type 2 diabetes progression. Therefore, the molecular mechanisms of these four genes in the development of type 2 diabetes-associated MCI should be studied. Full article

Mitogen-activated protein kinase (MAPK/MPK) cascades are pivotal and highly conserved signaling modules widely distributed in eukaryotes; they play essential roles in plant growth and development, as well as biotic and abiotic stress responses. With the development of sequencing technology, the complete genome assembly of rice without gaps, T2T (Telomere-to-Telomere)—NIP (version AGIS-1.0), has recently been released. In this study, we used bioinformatic approaches to identify and analyze the rice MPK kinases (MKKs) based on the complete genome. A total of seven OsMKKs were identified, and their physical and chemical properties, chromosome localization, gene structure, subcellular localization, phylogeny, family evolution, and cis-acting elements were evaluated. OsMKKs can be divided into four subgroups based on phylogenetic relationships, and the family members located in the same evolutionary branch have relatively similar gene structures and conserved domains. Quantitative real-time PCR (qRT-PCR) revealed that all OsMKKs were highly expressed in rice seedling leaves. The expression levels of all OsMKKs were more or less altered under exogenous hormone and abiotic stress treatments, with OsMKK1, OsMKK6, and OsMKK3 being induced under almost all treatments, while the expression of OsMKK4 and OsMKK10-2 was repressed under salt and drought treatments and IAA treatment, respectively. In this study, we also summarized the recent progress in rice MPK cascades, highlighted their diverse functions, and outlined the potential MPK signaling network, facilitating further studies on OsMKK genes and rice MPK cascades. Full article

Pheochromocytoma and paraganglioma (PPGL) are rare tumors derived from the adrenal medulla and extra-adrenal chromaffin cells. Diagnosis is often challenging due to the great variability in clinical presentation; the complexity of management due to the dangerous effects of catecholamine excess and the potentially malignant behavior require in-depth knowledge of the pathology and multidisciplinary management. Nowadays, diagnostic ability has certainly improved and guidelines and consensus documents for treatment and follow-up are available. A major impulse to the development of this knowledge has come from the new findings on the genetic and molecular characteristics of PPGLs. Germline mutation in susceptibility genes is detected in 40% of subjects, with a mutation frequency of 10–12% also in patients with sporadic presentation and genetic testing should be incorporated within clinical care. PPGL susceptibility genes include “old genes” associated with Neurofibromatosis type 1 (NF1 gene), Von Hippel Lindau syndrome (VHL gene) and Multiple Endocrine Neoplasia type 2 syndrome (RET gene), the family of SDHx genes (SDHA, SDHB, SDHC, SDHD, SDHAF2), and genes less frequently involved such as TMEM, MAX, and FH. Each gene has a different risk of relapse, malignancy, and other organ involvement; for mutation carriers, affected or asymptomatic, it is possible to define a tailored long-life surveillance program according to the gene involved. In addition, molecular characterization of the tumor has allowed the identification of somatic mutations in other driver genes, bringing to 70% the PPGLs for which we know the mechanisms of tumorigenesis. This has expanded the catalog of tumor driver genes, which are identifiable in up to 70% of patients Integrated genomic and transcriptomic data over the last 10 years have revealed three distinct major molecular signatures, triggered by pathogenic variants in susceptibility genes and characterized by the activation of a specific oncogenic signaling: the pseudo hypoxic, the kinase, and the Wnt signaling pathways. These molecular clusters show a different biochemical phenotype and clinical behavior; they may also represent the prerequisite for implementing customized therapy and follow-up. Full article

CLAVATA3 (CLV3)/EMBRYO SURROUNDING REGION (ESR)-related (CLE) genes encode a group of peptide hormones, which coordinate cell proliferation and differentiation in plants. Tiger nut (Cyperus esculentus L.) is a perennial monocot plant that produces oil-rich tubers. However, the mechanisms regulating tuber development in tiger nut are poorly understood, and nothing is known about CLE genes in tiger nut. In this study, we identified 34 CLE genes in the genomes, proteomes, and transcriptomes of C. esculentus (CeCLE). We analyzed their gene structures and expression profiles in different parts of the plant, at three stages of tuber development and in roots in response to dehydration stress. We found a relatively high expression level of CeCLE13 in growing tuber and suggested that the corresponding CLE peptide could be involved in the regulation of tuberization. We also analyzed CeCLE gene sequences in the genome of the most productive K-17 variety in the N. I. Vavilov All-Russian Institute of Plant Genetic Resources collection and found many single nucleotide polymorphisms, insertions, and deletions. Our data provides fundamental information for future research on tiger nut growth and tuberization. Full article

The adoption of genomic selection is prevalent across various plant and livestock species, yet existing models for predicting genomic breeding values often remain suboptimal. Machine learning models present a promising avenue to enhance prediction accuracy due to their ability to accommodate both linear and non-linear relationships. In this study, we evaluated four machine learning models—Random Forest, Support Vector Machine, Convolutional Neural Networks, and Multi-Layer Perceptrons—for predicting genomic values related to birth weight (BW), weaning weight (WW), and yearling weight (YW), and compared them with other conventional models—GBLUP (Genomic Best Linear Unbiased Prediction), Bayes A, and Bayes B. The results demonstrated that the GBLUP model achieved the highest prediction accuracy for both BW and YW, whereas the Random Forest model exhibited a superior prediction accuracy for WW. Furthermore, GBLUP outperformed the other models in terms of model fit, as evidenced by the lower mean square error values and regression coefficients of the corrected phenotypes on predicted values. Overall, the GBLUP model delivered a superior prediction accuracy and model fit compared to the machine learning models tested. Full article

Background: Changes in DNA methylation patterns are a pivotal mechanism of carcinogenesis. In some tumors, aberrant methylation precedes genetic changes, while gene expression may be more frequently modified due to methylation alterations than by mutations. Methods: Herein, 128 serous ovarian tumors were analyzed, including borderline ovarian tumors (BOTS) with (BOT.V600E) and without (BOT) the BRAF V600E mutation, low-grade (lg), and high-grade (hg) ovarian cancers (OvCa). The methylome of the samples was profiled with Infinium MethylationEPIC microarrays. Results: The biggest number of differentially methylated (DM) CpGs and regions (DMRs) was found between lgOvCa and hgOvCa. By contrast, the BOT.V600E tumors had the lowest number of DM CpGs and DMRs compared to all other groups and, in relation to BOT, their genome was strongly downmethylated. Remarkably, the ten most significant DMRs, discriminating BOT from lgOvCa, encompassed the MHC region on chromosome 6. We also identified hundreds of DMRs, being of potential use as predictive biomarkers in BOTS and hgOvCa. DMRs with the best discriminative capabilities overlapped the following genes: BAIAP3, IL34, WNT10A, NEU1, SLC44A4, and HMOX1, TCN2, PES1, RP1-56J10.8, ABR, NCAM1, RP11-629G13.1, AC006372.4, NPTXR in BOTS and hgOvCa, respectively. Conclusions: The global genome-wide hypomethylation positively correlates with the increasing aggressiveness of ovarian tumors. We also assume that the immune system may play a pivotal role in the transition from BOTS to lgOvCa. Given that the BOT.V600E tumors had the lowest number of DM CpGs and DMRs compared to all other groups, when methylome is considered, such tumors might be placed in-between BOT and OvCa. Full article

Background: The fragrance and aroma of Rosaceae plants are complex traits influenced by a multitude of factors, with genetic variation standing out as a key determinant which is largely impacted by polyploidy. Polyploidy serves as a crucial evolutionary mechanism in plants, significantly boosting genetic diversity and fostering speciation. Objective: This review focuses on the Rosaceae family, emphasizing how polyploidy influences the production of volatile organic compounds (VOCs), which are essential for the aromatic characteristics of economically important fruits like strawberries, apples, and cherries. The review delves into the biochemical pathways responsible for VOC biosynthesis, particularly highlighting the roles of terpenoids, esters alcohols, aldehydes, ketones, phenolics, hydrocarbons, alongside the genetic mechanisms that regulate these pathways. Key enzymes, such as terpene synthases and alcohol acyltransferases, are central to this process. This review further explores how polyploidy and hybridization can lead to the development of novel metabolic pathways, contributing to greater phenotypic diversity and complexity in fruit aromas. It underscores the importance of gene dosage effects, isoenzyme diversity, and regulatory elements in determining VOC profiles. Conclusions: These findings provide valuable insights for breeding strategies aimed at improving fruit quality and aligning with consumer preferences. Present review not only elucidates the complex interplay between genomic evolution and fruit aroma but also offers a framework for future investigations in plant biology and agricultural innovation. Full article

Six hundred million cases of disease and roughly 420,000 deaths occur globally each year due to foodborne pathogens. Current methods to screen and identify pathogens in swine, poultry, and cattle products include immuno-based techniques (e.g., immunoassay integrated biosensors), molecular methods (e.g., DNA hybridization and PCR assays), and traditional culturing. These methods are often used in tandem to screen, quantify, and characterize samples, prolonging real-time comprehensive analysis. Next-generation sequencing (NGS) is a relatively new technology that combines DNA-sequencing chemistry and bioinformatics to generate and analyze large amounts of short- or long-read DNA sequences and whole genomes. The goal of this project was to evaluate the quantitative capabilities of the real-time NGS Oxford Nanopore Technologies’ MinION sequencer through a shotgun-based sequencing approach. This investigation explored the correlation between known amounts of the analyte (lambda DNA as a pathogenic bacterial surrogate) with data output, in both the presence and absence of a background matrix (Bos taurus DNA). A positive linear correlation was observed between the concentration of analyte and the amount of data produced, number of bases sequenced, and number of reads generated in both the presence and absence of a background matrix. In the presence of bovine DNA, the sequenced data were successfully mapped to the NCBI lambda reference genome. Furthermore, the workflow from pre-extracted DNA to target identification took less than 3 h, demonstrating the potential of long-read sequencing in food safety as a rapid method for screening, identification, and quantification. Full article

Hepatocellular carcinomas (HCCs) are highly heterogeneous malignancies. They are characterized by a peculiar tumor microenvironment and dense vascularization. The importance of signaling between immune cells, endothelial cells, and tumor cells leads to the difficult recapitulation of a reliable in vitro HCC model using the conventional two-dimensional cell cultures. The advent of three-dimensional organoid tumor technology has revolutionized our understanding of the pathogenesis and progression of several malignancies by faithfully replicating the original cancer genomic, epigenomic, and microenvironmental landscape. Organoids more closely mimic the in vivo environment and cell interactions, replicating factors such as the spatial organization of cell surface receptors and gene expression, and will probably become an important tool in the choice of therapies and the evaluation of tumor response to treatments. This review aimed to describe the ongoing and potential applications of organoids as an in vitro model for the study of HCC development, its interaction with the host’s immunity, the analysis of drug sensitivity tests, and the current limits in this field. Full article

Background: Gut microbiota have been previously reported to be related to a variety of immune diseases. However, the causal connection between Sjögren’s syndrome (SS) and gut microbiota has yet to be clarified. Methods: We employed a two-sample Mendelian randomization (MR) analysis to evaluate the causal connection between gut microbiota and SS, utilizing summary statistics from genome-wide association studies (GWASs) obtained from the MiBioGen and FinnGen consortia. The inverse variance weighted (IVW) approach represents the primary method of Mendelian randomization (MR) analysis. Sensitivity analysis was used to eliminate instrumental variables heterogeneity and horizontal pleiotropy. In addition, we performed an analysis using independent GWAS summary statistics for SS from the European Bioinformatics Institute (EBI) dataset for further verify our results. Results: IVW results demonstrated that the phylum Lentisphaerae (OR = 0.79, 95% CI: 0.63–0.99, p = 0.037), class Deltaproteobacteria (OR = 0.67, 95% CI: 0.47–0.96, p = 0.030), family Porphyromonadaceae (OR = 0.60, 95% CI: 0.38–0.94, p = 0.026), genus Eubacterium coprostanoligenes group (OR = 0.61, 95% CI: 0.4–0.93, p = 0.021), genus Blautia (OR = 0.62, 95% CI: 0.43–0.90, p = 0.012), genus Butyricicoccus (OR = 0.61, 95% CI: 0.42–0.90, p = 0.012), genus Escherichia.Shigella (OR = 0.7, 95% CI: 0.49–0.99, p = 0.045) and genus Subdoligranulum (OR = 0.61, 95% CI: 0.44–0.86, p = 0.005) exhibited protective effects on SS. Relevant heterogeneity of horizontal pleiotropy or instrumental variables was not detected. Furthermore, repeating our results with an independent cohort provided by the EBI dataset, only the genus Eubacterium coprostanoligenes group remained significantly associated with the protective effect on SS (OR = 0.41, 95% CI: 0.18–0.91, p = 0.029). Two-step MR analysis further revealed that genus Eubacterium coprostanoligenes group exerts its protective effect by reducing CXCL6 levels in SS (OR, 0.87; 95% CI = 0.76–0.99, p = 0.033). Conclusions: Our study using two-sample MR analysis identified a causal association between multiple genera and SS. A two-step MR result calculated that genus Eubacterium coprostanoligenes group mediated its protective effect by reducing CXCL6 levels in SS. However, the datasets available from the MiBioGen and FinnGen consortia do not provide sufficient information or comprehensive demographic data for subgroup analyses. Additional validation using various omics technologies is necessary to comprehend the development of SS in the intricate interplay between genes and the environment over a period of time. Full article

This study aimed to explore the role of the trehalose-6-phosphate synthase (TPS) gene family in the adaptation of peas to environmental stress. A comprehensive analysis of the PsTPS gene family identified 20 genes with conserved domains and specific chromosomal locations. Phylogenetic analysis delineated evolutionary relationships, while gene structure analysis revealed compositional insights, and motif analysis provided functional insights. Cis-regulatory element identification predicted gene regulation patterns. Tissue-specific and stress-induced expression profiling highlighted eight genes with ubiquitous expression, with PsTPS15 and PsTPS18 displaying elevated expression levels in roots, nodules, and young stems, and PsTPS13 and PsTPS19 expression downregulated in seeds. Transcriptome analysis identified a differential expression of 20 PsTPS genes, highlighting the significance of 14 genes in response to drought and salinity stress. Notably, under drought conditions, the expression of PsTPS4 and PsTPS6 was initially upregulated and then downregulated, whereas that of PsTPS15 and PsTPS19 was downregulated. Salinity stress notably altered the expression of PsTPS4, PsTPS6, and PsTPS19. Taken together, these findings elucidate the regulatory mechanisms of the PsTPS gene family and their potential as genetic targets for enhancing crop stress tolerance. Full article

Parvalbumins are the main source of food allergies in fish meat, with each fish possessing multiple different parvalbumins. The naming convention of these allergens in terms of allergen codes (numbers) is species-specific. Allergen codes for parvalbumin isoallergens and allergen variants are based on sequence identities relative to the first parvalbumin allergen discovered in that particular species. This means that parvalbumins with similar allergen codes, such as catfish Pan h 1.0201 and redfish Seb m 1.0201, are not necessarily the most similar proteins, or encoded by the same gene. Here, we aim to elucidate the molecular basis of parvalbumins. We explain the complicated genetics of fish parvalbumins in an accessible manner for fish allergen researchers. Teleost or modern bony fish, which include most commercial fish species, have varying numbers of up to 22 parvalbumin genes. All have derived from ten parvalbumin genes in their common ancestor. We have named these ten genes “parvalbumin 1-to-10” (PVALB1-to-PVALB10), building on earlier nomenclature established for zebrafish. For duplicated genes, we use variant names such as, for example, “PVALB2A and PVALB2B”. As illustrative examples of our gene identification system, we systematically analyze all parvalbumin genes in two common allergy-inducing species in Japan: red seabream (Pagrus major) and chum salmon (Oncorhynchus keta). We also provide gene identifications for known parvalbumin allergens in various fish species. Full article

Determining a novel etiology and mechanism of human cancer requires extraction of characteristic mutational signatures derived from chemical substances. This study explored the mutational signatures of N-nitroso bile acid conjugates using Salmonella strains. Exposing S. typhimurium TA1535 to N-nitroso-glycine/taurine bile acid conjugates induced a predominance of C:G to T:A transitions. Two mutational signatures, B1 and B2, were extracted. Signature B1 is associated with N-nitroso-glycine bile acid conjugates, while Signature B2 is linked to N-nitroso-taurine bile acid conjugates. Signature B1 revealed a strong transcribed strand bias with GCC and GCT contexts, and the mutation pattern of N-nitroso-glycine bile acid conjugates in YG7108, which lacks O⁶-methylguanine DNA methyltransferases, matched that of the wild-type strain TA1535, suggesting that O⁶-methyl-deoxyguanosine contributes to mutations in the relevant regions. COSMIC database-based similarity analysis revealed that Signature B1 closely resembled SBS42, which is associated with occupational cholangiocarcinoma caused by overexposure to 1,2-dichlolopropane (1,2-DCP) and/or dichloromethane (DCM). Moreover, the inflammatory response pathway was induced by 1,2-DCP exposure in a human cholangiocyte cell line, and iNOS expression was positive in occupational cholangiocarcinomas. These results suggest that 1,2-DCP triggers an inflammatory response in biliary epithelial cells by upregulating iNOS and N-nitroso-glycine bile acid conjugate production, resulting in cholangiocarcinoma via DNA adduct formation. Full article

Hypermobile Ehlers-Danlos syndrome (hEDS) is a connective tissue disorder marked by joint hypermobility, skin hyperextensibility, and tissue fragility. Recent studies have linked hEDS with mast cell activation syndrome (MCAS), suggesting a genetic interplay affecting immune regulation and infection susceptibility. This study aims to decode the genetic basis of mast cell hypersensitivity and increased infection risk in hEDS by identifying specific genetic variants associated with these conditions. We conducted whole-genome sequencing (WGS) on 18 hEDS participants and 7 first-degree relatives as controls, focusing on identifying genetic variants associated with mast cell dysregulation. Participants underwent clinical assessments to document hEDS symptoms and mast cell hypersensitivity, with particular attention to past infections and antihistamine response. Our analysis identified specific genetic variants in MT-CYB, HTT, MUC3A, HLA-B and HLA-DRB1, which are implicated in hEDS and MCAS. Protein–protein interaction (PPI) network analysis revealed significant interactions among identified variants, highlighting their involvement in pathways related to antigen processing, mucosal protection, and collagen synthesis. Notably, 61.1% of the hEDS cohort reported recurrent infections compared to 28.5% in controls, and 72.2% had documented mast cell hypersensitivity versus 14.2% in controls. These findings provide a plausible explanation for the complex interplay between connective tissue abnormalities and immune dysregulation in hEDS. The identified genetic variants offer insights into potential therapeutic targets for modulating mast cell activity and improving patient outcomes. Future research should validate these findings in larger cohorts and explore the functional implications of these variants to develop effective treatment strategies for hEDS and related mast cell disorders. Full article