Search Results (1,403)

Codon usage bias (CUB) is a universal feature in both mitochondrial and ribosomal genes, shaped by the combined forces of mutation and selection, and serves as a valuable indicator of evolutionary processes and phylogenetic signals. However, comprehensive analysis of CUB is lacking in the Leuciscinae family. We sequenced and annotated the complete mitochondrial genome of Abramis brama orientalis and examined codon usage patterns in all Leuciscinae species, subsequently finding the dominant evolutionary forces and phylogenetic relationships. We performed a PR2 bias plot, neutrality plot, effective number of codons (ENC) vs. GC3, relative synonymous codon use (RSCU) clustering and Ka/Ks calculations for 22 Leuciscinae species. We constructed the phylogenetic trees of Leuciscinae using Bayesian inference and maximum likelihood on concatenated mitochondrial sequences. The complete mitochondrial genome of Abramis brama orientalis was 16,607 bp, with typical vertebrate structure and high A + T bias. The codons of protein-coding genes in Leuciscinae have a preference for ending in A/C. All protein-coding genes were under strong purifying selection (Ka/Ks < 1). RSCU patterns and phylogenetic analyses showed two lines of Leuciscinae in the RSCU, with A. brama orientalis being a monophyletic group with A. brama. The results demonstrate the strong role for selection in shaping mitochondrial codon usage in Leuciscinae, despite mutational biases. The study clarified the taxonomic status of A. brama orientalis and provided a framework for understanding molecular evolution in this ecologically important freshwater fish family. Full article

Tomato high pigment-2 (hp-2^dg, hp-2, and hp-2^j) mutant lines are characterized by mutations in the DE-ETIOLATED1 (SlDET1; Solyc01g056340) gene. SlDET1 is responsible for encoding a nuclear protein that acts as a negative regulator involved in light signaling, repressing photomorphogenesis. These tomato mutant lines are known for increased levels of antioxidant pigments in fruits, such as flavonoids and carotenoids, compared to the wild-type fruits. In this study, CRISPR/Cas9, followed by the non-homologous end joining mechanism of repair (NHEJ), was used to target the SlDET1 gene and investigate whether the effects of these mutations could mimic the effects of hp-2 mutant lines, improving the nutritional features of tomato fruits. Our results indicated that mutations generated by CRISPR/Cas9 NHEJ in the hp-2 and hp-2^j regions (exon 11) resulted in significant changes in the SlDET1 coding and protein sequences. These mutations caused a low survival rate of edited sprouts and regenerated plants with a very compromised capacity of allelic heritability of these mutations for the following generations. However, regenerated plants containing these site-specific mutations in the SlDET1 gene showed higher levels of phytochemicals in ripe fruits. Furthermore, these edited plants also showed an upregulation of structural genes involved in the synthesis of these biocompounds. Although the SlDET1 gene could be considered an interesting target gene for the nutritional improvement of tomato fruits, our results showed that mutations within its exon 11 are quite critical and can induce severe perturbations in plant physiology, with a compromised possibility to develop new stable edited lines. Full article

Although DNA-based data storage theoretically provides an information density of 2 bits per nucleotide, biochemical constraints transform sequence design into a high-dimensional constrained combinatorial optimization problem. The high computational cost and low encoding efficiency of conventional rule-based approaches make metaheuristic methods an effective alternative. This study proposes the TC-HUR hybrid algorithm to simultaneously optimize information density and conflicting biophysical constraints, including homopolymer (HP) length, GC content, melting temperature ($T_m$), and reverse-complement (RC) similarity. The method escapes local optima using Cauchy jump-enhanced Hunger Games Search (HGS), performs high-precision exploitation via Runge–Kutta (RUN) operators, and refines constraint violations at the nucleotide level through an adaptive intensive mutation mechanism. The algorithm is evaluated on a complex dataset of 1853 nucleotides under different noise regimes. TC-HUR outperforms RUN by 2.5% and HGS by 16.7% in average fitness. While maintaining homopolymer length near the ideal threshold, it reduces reverse-complement similarity to 19.10%, ensuring high sequence diversity. Under high-noise conditions, TC-HUR achieves a normalized edit distance of 0.1290, reducing insertion–deletion (indel) errors by approximately 14%. The results demonstrate that the proposed model effectively generates biophysically synthesizable and noise-resilient DNA codes. Full article

Seasonal influenza A evolves quickly through mutations in haemagglutinin (HA) and neuraminidase (NA), which can reduce vaccine match and lower protection. Many sequence-only models do not link codon-level mutations to three-dimensional (3D) protein context and long-term evolutionary signals within one scoring framework. This study presents TRIAD-Influenza (TRIAD: Token–Residue–Integrated Architecture for Drift), a multi-view transformer that combines (i) codon- and residue-level sequence representations, (ii) structure-derived residue interaction features from predicted HA/NA models, and (iii) an embedding-space phylogeny that captures cluster and drift context. The pipeline curates more than $3\times {10}^5$ paired HA/NA coding sequences from the NCBI Virus resource (2010–2024) using strict quality control and codon-aware alignment and predicts 3D structures for nearly all unique HA and NA proteins to build contact graphs and surface/stability descriptors. TRIAD-Influenza outputs a continuous, structure-aware risk score for each HA/NA pair and produces interpretable mutation hotspot maps using gradient saliency and a contact-weighted mutation risk index (CMRI). On rolling-origin temporal cross-validation and for a temporally held-out internal test window with strong class imbalance (∼3.4% high-risk), the model shows strong ranking performance (AUROC $\approx 0.89$; AUPRC $\approx 0.44$; Brier score $=0.069$) while operating at surveillance speed (median latency $\approx 1.6$ ms per HA/NA pair). External validation on independent GISAID/Nextstrain cohorts (2023–2024; 5000 isolates) preserves discrimination (AUROC $\approx 0.85$–$0.86$). Predicted risk scores correlate with experimental haemagglutination inhibition (HI) antigenic distances (Spearman $\rho$ up to ≈0.82 at the virus-aggregated level), and CMRI hotspots enrich known epitope and deep mutational scanning escape residues (odds ratios $\approx 2.7$–$3.6$). Overall, token–residue–phylogeny coupling enables rapid, structure-aware prioritisation of emerging influenza A HA/NA sequences and delivers compact hotspot maps for expert review and targeted experiments. Full article

Despite significant advancements in Artificial Intelligence, its widespread adoption in the clinical domain remains restricted due to the inherent complexity, fragmented nature, and diversity of healthcare systems. Each healthcare provider has unique data, clinical guidelines, data availability, system architectures, heterogeneity, and distribution. These challenges hinder the application of Clinical Decision Support Systems because of a limited understanding of how existing systems can be effectively redeployed across different healthcare providers. Redeployment is needed because it enables the reuse of existing knowledge, maximizes reusability, and avoids code duplication, thereby reducing the costs, effort, and time required to develop the Clinical Decision Support System from scratch. In addition, it ensures faster deployment and wider accessibility in the case of resource-constrained healthcare providers. An essential for redeployment is to identify the possible situations in which variables differ between two dynamic environments. To address this gap, we propose a structured multi-dimensional framework that systematically analyzes the potential differences between the variables. To represent the output of differences across dimensions based on variables in a systematic, machine-readable manner, we proposed a conceptual model, “VarDiff”, and a decision matrix of possible outcomes across five differential dimensions. This conceptual model provides a systematic, structural, and logical representation of a multidimensional framework for identifying differences among variables across data ecosystems. It formalizes variable characteristics in terms of semantic entities to observe differences among variables. The adaptation categories help identify the specific adaptation type, enabling the selection of relevant adaptation strategies in the “Mutator” component. Full article

Cancer immunotherapy has transformed the clinical management of several malignancies; however, its efficacy remains limited in tumors with low mutational burden and restricted availability of classical mutation-derived neoantigens. In this context, increasing evidence indicates that the tumor immunopeptidome extends far beyond canonical protein-coding regions, incorporating peptides derived from non-coding transcripts through non-canonical translation mechanisms. Long non-coding RNAs (lncRNAs), traditionally regarded as transcriptional or post-transcriptional regulators, have recently emerged as an unexpected source of small open reading frame-encoded peptides (lncPEPs). A subset of these peptides is processed and presented by major histocompatibility complex class I molecules, generating tumor-specific neoantigens capable of eliciting CD8⁺ T cell responses. Owing to the high tissue and context specificity of lncRNA expression, lncRNA-derived neoantigens offer unique advantages over mutation-based targets, including increased tumor selectivity and potential recurrence across patient subsets. In this review, we synthesize current knowledge on the biogenesis, detection, and immunogenic potential of lncRNA-derived peptides, highlighting experimental and computational strategies for their identification within the cancer immunopeptidome. We discuss the challenges associated with their validation and clinical translation, as well as their relevance for the development of vaccines and adoptive T cell–based therapies. Finally, we illustrate these concepts using epithelial ovarian cancer as a representative model of low-mutational-burden tumors, where lncRNA-derived neoantigens may help overcome current limitations of immunotherapy and enable patient stratification for personalized treatment approaches. Full article

Background/Objectives: Coffin–Lowry syndrome (CLS) is a rare X-linked disease caused by pathogenic variants in the RPS6KA3 gene. It is generally characterized by syndromic intellectual disability and distinctive facial features, skeletal abnormalities, stimulus-induced drop attacks in males, and variable manifestations in females. Methods: We report clinical and genetic findings in a series of 10 cases, eight males and two females, evaluated at the Regional Centre of Medical Genetics Dolj—Emergency Clinical County Hospital Craiova. Results: Genetic testing identified 10 de novo variants in the RPS6KA3 gene consisting of six missense mutations, one nonsense variant, one frameshift, and two variants in non-coding or intronic regions. Case management requires multidisciplinary coordination and is limited to resources mostly available in reference centers. Conclusions: CLS highlights the importance of molecular diagnosis in rare genetic disorders, particularly when clinical features are subtle or atypical. These findings have practical implications for clinical management, suggesting the need for comprehensive genetic screening and individualized care approaches. Full article

Codon usage bias (CUB) in mitochondrial genomes reflects evolutionary forces such as mutation, selection, and genetic drift, yet its dynamics in early-diverging fungal lineages like Conidiobolus (Zoopagomycota) remain unclear. This study systematically analyzed mitochondrial core protein-coding genes (PCGs) from eight Conidiobolus species to elucidate the drivers of CUB and phylogenomic patterns. Nucleotide composition revealed pronounced AT richness (73.32% ± 3.38%) and low GC3 (13.40% ± 5.11%), indicating a preference for A/T-ending codons. Neutrality and ENC-GC3s plots demonstrated that natural selection, rather than mutation pressure, predominantly shaped codon bias, supported by weak GC12-GC3 correlations (slopes: 0.037–0.335) and significant ENC deviations from mutation-driven expectations. PR2-bias analysis further highlighted a strong bias toward A over T and C over G. Correspondence analysis linked major codon usage variations to GC3s, CAI, and FOP indices. Phylogenetic reconstructions based on relative synonymous codon usage (RSCU) and concatenated mitochondrial sequences revealed discordant topologies, particularly in the placement of C. polytocus and C. polyspermus, suggesting divergent evolutionary trajectories. Optimal codon analysis identified species-specific preferences dominated by A/T termini. These findings underscore natural selection as the primary force driving AT-biased mitochondrial CUB in Conidiobolus, while phylogenomic discordance highlights complex evolutionary pressures in this ecologically diverse fungal genus. This study provides foundational insights into mitochondrial genome evolution and codon adaptation mechanisms in early-diverging fungi. Full article

Fusarium ear rot (FER), caused by Fusarium verticillioides, is a devastating disease that substantially reduces maize yield and compromises kernel quality. To investigate the genetic and molecular basis of resistance, an F₂ population derived from a cross between the resistant inbred line 3IBZ2 and the susceptible inbred line KW5G321 was analysed. By integrating bulked segregant analysis sequencing (BSA-Seq) with RNA sequencing (RNA-Seq), a major quantitative trait locus (QTL), designated qFER4, was identified on chromosome 4. Genetic analysis further demonstrated that qFER4 confers resistance through partial dominance. Transcriptome profiling of the resistant line revealed 7684 and 7906 differentially expressed genes (DEGs) at 36 and 72 h post inoculation (hpi), respectively. These DEGs were significantly enriched in defence-related biological processes and pathways, including phenylpropanoid biosynthesis, jasmonic acid signalling, MAPK cascades, and plant-pathogen interactions. By combining QTL mapping with transcriptome analyses, four candidate genes within the qFER4 interval were screened. Sequence analysis identified extensive structural variations in the promoter and coding regions of Zm00001d053393, including a premature stop codon predicted to lead to a gain-of-function mutation. In contrast, the other three genes exhibited only minor promoter polymorphisms with identical coding sequences between the parental lines. Overall, this study identifies a novel major-effect QTL and candidate gene associated with FER resistance, providing a foundation for gene function and a valuable genetic resource for breeding FER-resistant maize varieties. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, driven by aggressive tumor biology, extensive intratumoral heterogeneity, and profound resistance to standard therapies. While recurrent genetic alterations such as KRAS mutations are central to PDAC initiation, growing evidence demonstrates that epigenetic dysregulation is a critical determinant of disease progression, cellular plasticity, immune evasion, and therapeutic failure. Epigenetic mechanisms, including DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA regulation, shape transcriptional programs without altering the underlying DNA sequence, rendering them dynamic and potentially reversible therapeutic targets. This review provides a comprehensive overview of key epigenetic proteins implicated in PDAC, encompassing writers, readers, and erasers of chromatin marks. Aberrant activity of histone methyltransferases and acetyltransferases, bromodomain-containing proteins, histone deacetylases, and demethylases orchestrates transcriptional reprogramming that promotes epithelial–mesenchymal transition, stem-like phenotypes, metabolic adaptation, and resistance to chemotherapy and radiotherapy. In parallel, epigenetic alterations within the tumor microenvironment contribute to stromal activation and immune suppression, further limiting therapeutic efficacy. We summarize recent advances in pharmacological targeting of epigenetic regulators and discuss the rationale for combination strategies integrating epigenetic inhibitors with cytotoxic agents, targeted therapies, and immunotherapies. Emphasis is placed on emerging experimental platforms—including patient-derived organoids, co-culture systems, and in vivo models—combined with multi-omic profiling and computational approaches to identify biomarkers of response and optimize therapeutic design. Collectively, this review highlights epigenetic regulation as a central and actionable vulnerability in PDAC and outlines future directions toward biomarker-guided, personalized epigenetic therapies aimed at overcoming resistance and improving clinical outcomes. Full article

To clarify the genetic classification, diagnostic strategies, and precision treatment pathways of steroid-resistant nephrotic syndrome (SRNS), this review systematically reviews the genetic stratification system of SRNS by integrating recent advances in genetic testing technologies and pathogenesis research. It contains the pathogenic mechanisms, diagnostic protocols, and therapeutic correlations of different genetic subtypes, while summarizing current progress and clinical challenges in gene therapy. Results indicate SRNS can be categorized into genetic (38–58%) and non-genetic/immune-mediated (40–60%). A stepwise diagnostic system comprising core proteinuria gene panel testing, whole-genome sequencing (WGS), whole-exome sequencing (WES), and supplementary multi-omics/long-range sequencing is proposed, suited for populations with “typical phenotypes and moderate genetic risk”, “atypical phenotypes and high genetic suspicion”, and “complex structural/non-coding region variants” respectively. Pathogenic mechanisms directly determine therapeutic strategies: COQ2/PDSS2 mutations respond to coenzyme Q10 suplementation, while NPHS1 mutations necessitate early renal transplantation. Adeno-associated virus (AAV)-mediated gene therapy and CRISPR-Cas editing show preclinical promise but face challenges including incomplete detection coverage and clinical translation difficulties. Genetic technologies are driving SRNS management transformation from “empirical treatment” to “mechanism-oriented precision diagnosis and therapy”. Future efforts should focus on overcoming genetic testing limitations and gene therapy translation bottlenecks to enhance diagnostic and therapeutic efficacy. Full article

The development of the human brain starts with the orchestrated expression of our genes during embryogenesis. Non-protein-coding DNA sequences (gene promoters and enhancers) dynamically interact to form a three-dimensional (3D) network, orchestrating gene expression. We discuss novel perspectives on how DNA sequence variants within regulatory DNA, identified by whole-genome sequencing (WGS), contribute to the development of neurodevelopmental disorders (NDDs), including autism spectrum disorders (ASDs). We discuss two recent models explaining the evolution of a subset of regulatory sequences, Human Accelerated DNA Regions (HARs), proposed to be involved in the evolution of uniquely human brain features through their participation in the 3D interactions network. We connect this with the recent proposal that rare, recessive inherited sequence variants within HARs, interacting with distant target genes in neural cells, represent risk factors for the development of ASDs. The SOX2 transcription factor, whose heterozygous mutation causes NDDs, shapes the noncoding-DNA interaction network in neural cells, and binds DNA together with FOS, whose recognition sequence is enriched within HARs carrying human-specific substitutions modulating enhancer activity. SOX2 also binds regulatory regions (including HARs) carrying ASD-associated mutations. We highlight research directions based on these findings, which will hopefully improve our understanding of the connection between SOX2-dependent gene regulatory networks, NDDs, and brain evolution. Full article

JC Polyomavirus (JCPyV) is a non-enveloped virus with circular double stranded DNA responsible for the rare but fatal demyelinating disease known as progressive multifocal leukoencephalopathy (PML). In its host, this virus exists in two different forms: one found in the periphery, named archetype, and another found in the central nervous system, named prototype. This form usually harbors recombinations in the non-coding control region (NCCR), a key region that contains sequences regulating viral replication and containing binding sites for cellular transcription factors. This form also contains mutations in the capsid protein, especially VP1. Due to the diversity of the JCPyV, a natural polymorphism also exists between the different genotypes. In this review, we aimed to summarize the main features of the archetype and prototype strains in order to facilitate the interpretation of sequence data that are increasingly generated by new sequencing technologies. This will also help to distinguish mutations associated with the natural polymorphism from those specific to the prototype form. Full article

Puccinia striiformis f. sp. elymi (Pse) is a specialized forma specialis of stripe rust infecting Elymus dahuricus, yet its mitochondrial evolution remains poorly understood. In this study, we assembled the complete mitogenome of Pse using PacBio HiFi sequencing, yielding a circular mitogenome of 72,952 bp. This reveals a striking asymmetric evolutionary pattern with a 28.34% genomic contraction compared to the wheat stripe rust P. striiformis f. sp. tritici (Pst-CYR32). Our analysis demonstrates that this streamlining is strictly driven by a massive and systematic loss of mitochondrial introns. The Pse mitogenome exhibits negative GC-skew (−0.0184) consistent with strand-asymmetric mutational pressure, while maintaining a strictly conserved and syntenic complement of all 14 core protein-coding genes (PCGs), alongside 24 tRNAs and 2 rRNAs. Phylogenomic analysis positions Pse as sister to the Pst clade with strong support (100% bootstrap). A 748-bp SNP cluster within nad4 (14.2% sequence divergence versus 3.1% genome-wide average) provides a candidate molecular marker for lineage differentiation, pending population-level validation. This study establishes a genomic foundation for investigating mitochondrial reductive evolution in host-specialized rust lineages, highlighting the dynamic role of introns in driving organellar genome size variation. Full article

Chronic lymphocytic leukemia (CLL) is uncommon in Asia, and longitudinal genomic data from Asian cohorts are limited. We conducted serial whole-exome sequencing (WES) in a multicenter Korean cohort of newly diagnosed, elderly CLL treated with chlorambucil–obinutuzumab to evaluate mutational heterogeneity and clonal hematopoiesis of indeterminate potential (CHIP) during treatment and follow-up. Tumor-only variants were filtered, restricted to nonsynonymous or loss-of-function coding/splice-site mutations, and summarized as a binary patient-by-gene matrix for principal component analysis (PCA), trajectory analysis, and k-means clustering. CHIP was defined as ≥1 qualifying mutation in a prespecified CHIP gene set. Baseline PCA was more compact in patients with complete response at end of treatment, whereas partial response or progressive disease cases were more dispersed. PCA trajectories were compact and directionally consistent in complete responders, more dispersed in partial responders, and highly heterogeneous without a dominant direction in progressive disease. Clustering identified dispersed and compact clusters, and CHIP-associated mutations were enriched in the dispersed cluster (55.6% vs. 8.3%, Fisher’s exact p = 0.0086). In paired samples collected 3–5 months after end of treatment, CHIP status changed in some patients. Serial WES may provide complementary information to treatment response, although these observations require confirmation in larger cohorts. Full article