Search Results (93)

The neurofibromin 1 (NF1) splice-site mutation c.61-2A>G (rs1131691100) is a rare, pathogenic, autosomal dominant variant that disrupts NF1 tumor-suppressor function, causing neurofibromatosis type 1 (NF1). Its pathogenic mechanism is poorly understood, and the potential for personalized therapeutic genome editing remains unknown due to the absence of a standard framework for investigating splicing disorders. Here, we performed a comprehensive multi-omics analysis of a de novo c.61-2A>G case from South Korea, integrating short- and long-read whole genome sequencing, whole transcriptome sequencing, and methylation profiling. We confirm that c.61-2A>G abolishes the canonical splice acceptor site, activating a cryptic splice acceptor 16 nucleotides downstream in exon 2. This splicing shift generates a 16-nucleotide deletion, causing a frameshift and premature stop codon that truncates the protein’s N-terminal region. Long-read sequencing further reveals that the mutation creates a novel CpG dinucleotide, which is methylated in the majority of reads. Finally, we assessed therapeutic correction strategies, revealing that CRISPR-Cas9 prime editing is the only viable approach for in vivo correction. This study provides the first comprehensive multi-omics characterization of the NF1 c.61-2A>G mutation and establishes a minimal framework for precision therapeutic development in silico in monogenic splicing disorders. Full article

This study investigates the codon usage characteristics of Japanese encephalitis virus (JEV) genotype 5 (G5). Based on 339 complete JEV genome sequences, we systematically compared the codon usage patterns of G5 with other genotypes (G1–G4) using a multi-faceted approach, including evolutionary analysis, nucleotide composition, Relative Synonymous Codon Usage (RSCU), Principal Component Analysis (PCA), Effective Number of Codons Plot analysis (ENC-Plot), Parity Rule 2 analysis (PR2), Neutrality plot analysis, dinucleotide abundance analysis and Codon Adaptation Index analysis (CAI). The results indicate that G5 forms a distinct evolutionary branch, with both its overall GC content (50%) and GC content at the third codon position (GC3, 53%) being lower than those of other genotypes. RSCU analysis revealed a preferential use of A/U-ended codons in G5, indicating a trend towards reduced GC3 usage. ENC analysis demonstrated a stronger codon usage bias in G5 (mean ENC = 54.2). Furthermore, ENC-plot, PR2, and neutrality plot analyses collectively suggested that G5 is subject to stronger natural selection pressure. Analysis of dinucleotide abundance showed a significant increase in CA values in G5, while CAI analysis indicated higher translational efficiency in human hosts compared to Culex mosquito hosts. Our findings suggest that G5 JEV, potentially through reduced Cytosine-phosphate-Guanine (CpG) usage and optimized codon preference, may enhance its capabilities for immune evasion and host adaptation, and could possess the potential for efficient replication in humans or other mammalian hosts. This research provides crucial theoretical insights into the molecular evolutionary mechanisms of G5 JEV and informs related vaccine development. Full article

Background and Objectives: Human Papillomavirus (HPV) is a leading cause of cervical and other anogenital cancers, with over 200 known genotypes classified into high-risk, probable high-risk, and low-risk groups. While conventional diagnostic and classification approaches often rely on sequence alignment, phylogenetic relationships, or protein structure analyses, these methods are limited in scalability, cost efficiency, and generalizability to emerging HPV types. This study aims to develop a novel, machine learning-based framework for classifying HPV genotypes by oncogenic risk using genome-derived numerical features. A key objective is to introduce TATA-box, CAAT-box, and CpG-island-based features to HPV risk prediction for the first time. Methods: We constructed a comprehensive feature set that integrates regulatory sequence motifs (TATA-box, CAAT-box, CpG islands) with dinucleotide and trinucleotide (k-mer) composition derived from full HPV genomes. Multiple machine learning algorithms were implemented to evaluate classification performance across all risk categories. Model accuracy, precision, recall, and F1-score were calculated to assess the effectiveness and robustness of the proposed feature set. Results: The proposed method achieves an average precision of 0.95, a recall of 0.95, an F1-score of 0.95, and an accuracy of 97.47%. The experimental findings indicate that the proposed method not only attains high classification accuracy across all HPV risk groups but also surpasses existing models in generalizability by utilizing genomic data and novel biologically informed features. Conclusions: This study introduces regulatory motif-based numerical features to HPV classification for the first time and demonstrates that integrating these with k-mer descriptors yields a highly accurate and scalable machine learning model. Unlike previous studies, which often focus on specific HPV genes or a limited subset of types, our method is scalable, robust, and capable of classifying known and emerging HPV types with high reliability. This highlights its potential for real-world deployment in large-scale epidemiological screening and vaccine development programs. Full article

Background/Objectives: Gliomas are the most common tumours of the central nervous system (CNS), classified into grades I to IV based on their malignancy. Genetic and epigenetic alterations play a crucial role in glioma progression. DNA methyltransferases (DNMTs) are vital enzymes responsible for DNA methylation, with DNMT1 and DNMT3 catalysing the addition of a methyl group to the 5-carbon of cytosine in CpG dinucleotides. Targeting DNMTs with DNA methyltransferase inhibitors (DNMTi) has become a promising therapeutic approach in tumour treatment. In this study, in silico screening tools were employed to evaluate potential inhibitors of DNMT1, DNMT3A, and DNMT3B for the treatment of glioblastoma multiforme (GBM). Methods: The Gene2Drug platform was used to screen compounds and rank them based on their capacity to dysregulate DNMT genes. PRISM viability assays were performed on 68 cell lines, and DepMap data were analyzed to assess the antitumor activities of these compounds and their target genes. Candidate drug similarity was evaluated using DSEA, and compounds with p < 1 × 10⁻³ were considered statistically significant. Gene-compound interactions for DNMT1, DNMT3A, and DNMT3B were confirmed using Expression Public 24Q2, while Prism Repositioning Public data were analyzed via DepMap. Results: Glioblastoma cell lines showed sensitivity to compounds including droperidol, demeclocycline, benzthiazide, ozagrel, pizotifen, tracazolate, norcyclobenzaprine, monocrotaline, dydrogesterone, 6-benzylaminopurine, and nifedipine. SwissTargetPrediction was utilised to identify alternative molecular targets for selected compounds, revealing high-probability matches for droperidol, pizotifen, tracazolate, monocrotaline, dydrogesterone, and nifedipine. Conclusions: Integrating computational approaches with biological insights and conducting tissue-specific and experimental validations may significantly enhance the development of DNMT-targeted therapies for gliomas. Full article

Cellular organisms store heritable information in two forms, genetic and epigenetic, the latter being largely dependent on cytosine methylation (5mC). Chargaff’s Second Parity Rule (CSPR) describes the nucleotide composition of cellular genomes in terms of intra-strand DNA symmetry. However, it remains unknown whether DNA methylation patterns display intra-strand DNA symmetry. Computational analysis was conducted of the DNA methylation patterns observed in human cell lines and in tissue samples from healthy donors. Analysis of 5mC marks in mutually reverse-complementary pairs of short oligomers, containing CpG dinucleotide in the middle, revealed deviations from CSPR and methylation asymmetry that can be observed for two non-overlapping mirror groups defined by CpG methylation values. Deviations from CSPR, together with combinatorial probabilities of pattern distributions and computer simulations, highlight the non-random nature of methylation processes and enabled us to identify specific cell types as outliers. Further analysis revealed a compensatory methylation asymmetry that reduces deviations from intra-strand symmetry and implies the existence of strand-specific methylation during cell differentiation. Among six pairs of reverse-complementary tetranucleotides, four pairs with specific sequence motifs display pronounced methylation asymmetry. This mirror asymmetry may be associated with chromosome folding and the formation of a complex three-dimensional landscape. Full article

K-mer analysis is a powerful tool for understanding genome structure and evolution. A “k-mer” refers to a short DNA sequence made up of k nucleotides (where k is a specific integer), while an “m-mer” is a similar concept but with a shorter sequence length. The functional mechanisms of CG-containing k-mers, as well as their potential role in evolutionary processes, remain unclear. To explore this issue, we analyzed 8-mers in several species with varying genomic complexities and evolutionary divergences: Homo sapiens, Saccharomyces cerevisiae, Bombyx mori, Ciona intestinalis, Danio rerio, and Caenorhabditis elegans, which were grouped by CG dinucleotide content (0CG, 1CG, and 2CG). We examined the relative frequencies of shorter m-mers (with m = 3 and 4) within each CG-defined group, using information-theoretic, distance-based, and angular metrics. Our results show that 0CG motifs follow random patterns, while 1CG and 2CG motifs display significant deviations, likely due to functional constraints such as nucleosome-binding and CpG island association. The observed unimodal distribution of 8-mers arises from the convergence of the three CG-defined groups. Among them, the 2CG group shows the highest divergence in m-mer composition, followed by 1CG, reflecting varying degrees of selective pressure. Furthermore, species-specific differences in CG-classified 8-mer patterns could provide valuable insights into phylogenetic relationships. Through extensive comparison, we explore how CG content and sequence composition influence genomic organization and contribute to evolutionary divergence across different taxa. These findings deepen our understanding of short motif functions, genome organization, and sequence evolution. Full article

DNA methylation is an epigenetic modification where a methyl group is added to a DNA molecule, typically at the cytosine base within a CpG dinucleotide. This process can influence gene expression without changing the underlying DNA sequence. Essentially, methylation can act like a switch that regulates which genes are active in a cell. DNA methylation (DNAm) models often describe the dynamic changes of methylation levels at specific DNA sites, considering methylation and demethylation processes. A common approach involves representing the methylation state as a continuous variable, and modelling its change over time or in response to various factors using differential equations. These equations can incorporate parameters such as the methylation and demethylation rates, factors like DNA replication, the influence of regulatory proteins, and other related parameters. Understanding DNAm dynamics in relation to age is crucial for elucidating ageing processes and developing biomarkers. This work introduces a theoretical framework for modelling DNAm dynamics using a fractional calculus approach, extending standard models based on the integer-order differential equations. The proposed fractional-calculus representation of the methylation process, defined by the fractional-order differential equation and its solution based on the Mittag–Leffler function, provides improved results compared to the standard model that uses a first-order differential equation, which contains an exponential function in its solution, in terms of the comparison criteria (sum of absolute errors, sum of squared errors, mean absolute percentage error, R-squared, and adjusted R-squared). Moreover, the Mittag–Leffler model provides a more general representation of DNAm dynamics, making the standard exponential model only one specific case. Full article

DNA methylation is a well-studied epigenetic modification that regulates gene expression, maintains genome integrity, and influences cell fate. It is strictly regulated by a group of enzymes known as DNA methyltransferases (DNMTs). Most DNA methylation occurs at cytosines within symmetrical CpG dinucleotide base pairs, often located at gene promoters or other regulatory elements. Thus, methylation of a promoter CpG island leads to stable transcriptional repression of the associated gene. Nonetheless, abnormal gene expression caused by alterations in DNA methylation has been linked to infertility in both males and females, as well as to reproductive potential and improper post-fertilization embryo development. Recent epigenetic advancements have highlighted the significant association between epigenetic modification and reproductive health outcomes, garnering considerable attention. In this review, we explore significant advancements in understanding DNA methylation, emphasizing its establishment, maintenance, and functions in male and female reproductive sex cells. We also shed light on the recent discoveries on the influence of environmental exposures, nutrition, infection, stress, and lifestyle choices on DNA methylation. Finally, we discuss the latest insights and future directions concerning the diverse functions of DNA methylation in reproductive outcomes. Full article

Background/Objectives: The experience of pregnancy and parturition has been associated with long-term health effects in mothers, imparting protective effects against some diseases while the risk of other diseases is increased. The mechanisms that drive these altered disease risks are unknown. This study examined DNA methylation (DNAm) changes from pre-pregnancy to several years after giving birth in parous women compared to nulliparous controls over the same time interval. Methods: Using 180 parous-associated CpGs, three analyses were carried out to test DNAm changes from pre-pregnancy at age 18 years to gestation; from gestation to post-pregnancy at age 26 years in parous women; and from 18 to 26 years in nulliparous women using linear mixed models with repeated measures. Results: The directions of DNAm changes were the same between the parous and nulliparous groups. Most CpG dinucleotides (67%, 121 of 180) had a decreasing trend while a small number (7%, 13 of 180) had an increasing trend. Of the CpGs showing increasing or decreasing DNAm, approximately half had DNAm change to a smaller extent in parous women and the other half changed more in parous women than nulliparous controls. 9% (17 of 180) changed significantly in nulliparous women only, leading to a significant difference in DNAm levels in parous women at the post-pregnancy 26 years time point. Conclusions: Pregnancy and parturition may accelerate methylation changes in some CpGs, but slow down or halt methylation changes over time in other CpGs. Full article

DNA methylation is an important epigenetic modification with a plethora of effects on cells, ranging from the regulation of gene transcription to shaping chromatin structure. Notably, DNA methylation occurs thanks to the activity of DNA methyltransferases (DNMTs), which covalently add a methyl group to the cytosine in position 5′ in CpG dinucleotides. Different strategies have been developed to study the effects of DNA methylation in cells, involving either DNMTs inhibition (passive DNA demethylation) or the use of Ten-eleven translocation protein (TET) family enzymes, which directly demethylate DNA (active DNA demethylation). In this manuscript, we will briefly cover the most commonly used strategies in the last two decades to achieve DNA demethylation, along with their effects on cells. We will also discuss some of the newest inducible ways to inhibit DNMTs without remarkable side effects, as well as the effect of non-coding RNAs on DNA methylation. Lastly, we will briefly examine the use of DNA methylation inhibition in biomedical research. Full article

Molar incisor hypomineralization (MIH) is a dental condition that affects the enamel of permanent molars and/or incisors, often leading to tooth decay. Although several etiological hypotheses have come forward, including prenatal medical problems and postnatal illness, the pathogenesis of MIH is yet unclear. Aimed at exploring the epigenomic landscape of this dental condition, we collected dental tissue from a MIH-affected child and an age-matched control patient and investigated their DNA methylation status through an in-depth analysis of nanopore long-read sequencing data. We identified 780,141 CpGs with significantly different methylation levels between the samples; intriguingly, the density of these dinucleotides was higher in the regions containing genes involved in dental morphogenesis and inflammatory processes leading to periodontitis. Further examination of 54 genes associated with MIH or hypomineralized second primary molar disorders revealed very distinct methylation of intragenic transposable elements (SINEs, LINEs, and LTRs), while functional profiling analysis of 571 differentially methylated regions genome-wide uncovered significant enrichment processes including ameloblasts differentiation and calcium ion binding, as well as SP1 and other zinc finger transcription factors. Taken together, our findings suggest that DNA methylation could play a role in the pathogenesis of MIH and represent a stepping stone towards a comprehensive understanding of this multifactorial disorder. Full article

Genetics and epigenetics are mechanisms proposed for explaining post-COVID-19 condition. This secondary analysis aimed to investigate if DNA methylation levels of the ACE2 promoter are different depending on the genotype of five COVID-19-related polymorphisms in individuals who had been previously hospitalized due to SARS-CoV-2 infection. We collected non-stimulated saliva samples from 279 (48.7% female, age: 56.0 ± 12.5 years) previously hospitalized COVID-19 survivors. The participants self-reported for the presence of post-COVID symptomatology that started after the infection and persisted at the time of the appointment. Three potential genotypes of ACE2 rs2285666 and rs2074192, TMPRSS2 rs12329760 and rs2070788, and ACE1 rs1799752 polymorphisms were identified from saliva samples. Further, methylation levels at five different locations (CpG) of dinucleotides in the ACE2 promoter were quantified using bisulfited pyrosequencing. Differences in the methylation percentage (%) of each CpG according to the genotype of the five polymorphisms were analyzed. Participants were evaluated up to 17.8 (SD: 5.2) months after hospital discharge. Eighty-eight percent (88.1%) of patients reported at least one post-COVID symptom (mean number of post-COVID symptoms: 3.0; SD: 1.9). Overall, we did not observe significant differences in the methylation levels of the ACE2 promoter according to the genotype of ACE2 rs2285666 and rs2074192, TMPRSS2 rs12329760 and rs2070788, or ACE1 rs1799752 single nucleoid polymorphisms. This study did not find an association between genetics (genotypes of five COVID-19-associated polymorphisms) and epigenetics (methylation levels of the ACE2 promoter) in a cohort of COVID-19 survivors with post-COVID-19 condition who were hospitalized during the first wave of the pandemic. Full article

Recoding strategies have emerged as a promising approach for developing safer and more effective vaccines by altering the genetic structure of microorganisms, such as viruses, without changing their proteins. This method enhances vaccine safety and efficacy while minimizing the risk of reversion to virulence. Recoding enhances the frequency of CpG dinucleotides, which in turn activates immune responses and ensures a strong attenuation of the pathogens. Recent advancements highlight synonymous recoding’s potential, offering improved genetic stability and immunogenicity compared to traditional methods. Live vaccines attenuated using classical methods pose a risk of reversion to virulence and can be time-consuming to produce. Synonymous recoding, involving numerous codon alterations, boosts safety and vaccine stability. One challenge is balancing attenuation with yield; however, innovations like Zinc-finger antiviral protein (ZAP) knockout cell lines can enhance vaccine production. Beyond viral vaccines, recoding can apply to bacterial vaccines, as exemplified by modified Escherichia coli and Streptococcus pneumoniae strains, which show reduced virulence. Despite promising results, challenges like ensuring genetic stability, high yield, and regulatory approval remain. Briefly, ongoing research aims to harness these innovations for comprehensive improvements in vaccine design and deployment. In this commentary, we sought to further engage the community’s interest in this elegant approach by briefly highlighting its main advantages, disadvantages, and future prospects. Full article

Matrix Gla protein (MGP) is a vitamin K-dependent γ-carboxylated protein that was initially identified as a physiological inhibitor of ectopic calcification, primarily affecting cartilage and the vascular system. Mutations in the MGP gene were found to be responsible for the Keutel syndrome, a condition characterized by abnormal calcifications in the cartilage, lungs, brain, and vascular system. MGP has been shown to be dysregulated in several tumors, including cervical, ovarian, urogenital, and breast cancers. Using bioinformatic approaches, transcription factor binding sites (TFBSs) containing CpG dinucleotides were identified in the MGP promoter, including those for YY1, GATA1, and C/EBPα. We carried out functional tests using transient transfections with a luciferase reporter assay, primarily for the transcription factors YY1, GATA1, C/EBPα, and RUNX2. By co-transfection analysis, we found that YY1, GATA1, and C/EBPα repressed the MGP promoter. Furthermore, the co-transfection with RUNX2 activated the MGP promoter. In addition, MGP expression is negatively or positively correlated with the studied TFs’ expression levels in several cancer types. This study provides novel insights into MGP regulation by demonstrating that YY1, GATA1, and C/EBPα are negative regulators of the MGP promoter, and DNA methylation may influence their activity. The dysregulation of these mechanisms in cancer should be further elucidated. Full article

Helichrysum italicum (Roth) G. Don is a Mediterranean medicinal plant with great potential in the cosmetics, culinary and pharmaceutical fields due to its unique bioactive compounds. Its recent introduction into agroecosystems has enhanced the exploitation of genetic diversity in natural populations, although limited molecular markers have made this challenging. In the present study, primers were designed for all 43 SSRs (72.1% mononucleotide, 21% dinucleotide and 6.9% trinucleotide repeats) identified in the chloroplast genome. Populations from Cape Kamenjak (Croatia) and Corsica (France) were analyzed with ten carefully selected cpSSR markers. From the initial set of 16 cpSSRs amplified in all samples, 6 cpSSR markers were removed due to low-length polymorphisms, size homoplasy and nucleotide polymorphisms that could not be detected with allele length. Of the 38 haplotypes detected, 32 were unique to their geographic origin. The highest number of private haplotypes was observed in the Cape Kamenjak population (seven out of nine detected). Based on clustering analyses, the Kamenjak population was the most similar to the Capo Pertusato (south Corsica) population, although only one sub-haplotype was shared. Other Corsican populations were more similar to each other. A cross-species transferability test with Helichrysum litoreum Guss. and Helichrysum arenarium (L.) Moench was successfully conducted and private alleles were identified. Full article