Molecular Genetics and Genomics最新文献

The aim of this study was to explore the distribution and evolution of the biosynthetic gene cluster that directs the synthesis of 6-thioguanine, a purine antimetabolite that has applications as a chemotherapeutic, and has been studied for anti-inflammatory, antibacterial, and antiviral properties. Some bacteria, like members of the genus Erwinia, carry the ycfRABCD operon that directs the synthesis of 6-thioguanine. To explore its evolution, we surveyed for the presence of the cluster across all bacteria available in the public databases, and identified two distinct configurations of the gene cluster. One configuration is found exclusively within the Erwiniaceae and the Yersiniaceae (Gammaproteobacteria), and the second, which carries an additional gene, is found within members of the Alpha- and Betaproteobacteria. We found that the genomic location of ycf operon is conserved across divergent bacteria, with phylogenetic and %GC analyses suggesting that the cluster is evolutionarily old and vertically inherited. In some lineages, the cluster has been lost, while in others it has been acquired horizontally from distantly related groups. Maintenance of the cluster across diverse bacterial species suggests multiple roles for 6-thioguanine in the general ecology of these species.

Low-density lipoprotein receptor-related protein 5 (LRP5), a co-receptor of frizzled (FZD) in the WNT/β-catenin signaling pathway, recognizes Wnt ligands. This study aimed to assess the anti-cancer effects of silencing LRP5 on glioblastoma (GBM) and brain cancer stem cells (BCSCs). Additionally, the effect of temozolomide (TMZ) was also examined in these cells with suppressed LRP5 expression. LRP5 expression was silenced in U87MG, T98G, and BCSC cells using siRNA. Protein expression levels were determined by Western blotting. Cell viability after LRP5 silencing and/or TMZ treatment was evaluated using the CVDK-8 assay. Flow cytometry was used to examine apoptosis and cell cycle progression. Clonogenic, cell invasion, and wound-healing assays were used to assess colony formation, invasion, and migration, respectively. siRNA-mediated silencing reduced protein expression of LRP5 and Wnt/β-catenin target genes in GBM and BCSC cells. Furthermore, suppression of LRP5 reduced cell viability, and its combination with TMZ enhanced anti-proliferative effects. Silencing LRP5 and/or TMZ treatment caused cell cycle arrest and significantly diminished the aggressive characteristics of GBM and BCSC cells. These findings suggest that LRP5 may serve as a potential therapeutic target for treating GBM. Targeting LRP5 may enhance the effectiveness of the chemotherapy agent TMZ in GBM.

The importance of amino acid metabolism in regulating cancers progression was investigated by accumulating research. But the role of amino acid metabolism-related genes (AAMRGs) played in the colorectal cancer (CRC) progression remains unclear. We used Cox-LASSO analysis to construct an AAMRG prognostic signature and performed Gene set enrichment analysis (GSEA) for further investigation. Moreover, RT‒qPCR was adopted to estimate the expression of AAMRGs in clinical samples. Cell-based assays, including CCK-8, colony formation, and transwell assays were also performed to identify the roles of fibulin 5 (FBLN5) in CRC progression. We established a 10-AAMRG prognostic signature and stratified CRC samples into two risk groups, which showed significant differences in immune infiltration and EMT. RT-qPCR and human protein atlas data confirmed the mRNA and protein expression of these 10 AAMRGs, validating our bioinformatics findings. Importantly, functional assays revealed that FBLN5 overexpression suppressed CRC cell proliferation, migration, and invasion in vitro, as well as tumor growth in vivo. Our study establishes a novel 10-AAMRG signature as a promising predictor of therapeutic response and prognosis in CRC, and we identify FBLN5 as a pivotal protective factor in CRC progression, offering potential therapeutic value for targeted interventions.

Mitochondrial genomes play essential roles in plant energy metabolism and evolution, yet their structural complexity and diversity in plants remain poorly understood. This study aims to address the question by analyzing four newly assembled Mentha mitochondrial genomes (M. longifolia, M. suaveolens, M. pulegium, and M. requienii), which serve as valuable genomic resources for phylogenetic and evolutionary studies. Comparative analyses revealed structural diversity, codon usage bias, extensive RNA editing, and abundant repetitive sequences driving genomic rearrangements in the four mitochondrial genomes. Chloroplast-derived DNA fragments were dynamically integrated into the four Mentha mitochondrial genomes, highlighting ongoing interorganellar DNA transfer between plastids and mitochondria. Phylogenetic reconstructions based on mitochondrial, nuclear, and chloroplast genomes exhibit considerable discordance, reflecting complex evolutionary processes such as hybridization, introgression, and allopolyploidization within the genus. In conclusion, the structural diversity, codon usage bias, and ongoing interorganellar DNA transfer observed in Mentha mitochondrial genomes underscore their dynamic evolutionary nature. The discordance among mitochondrial, plastid, and nuclear phylogenies reflects complex evolutionary processes (possibly hybridization and allo-polyplodization) of Mentha species. These findings enhance the understanding of the mechanisms underlying the complexity and diversity of Mentha species and provide broader insights into the evolution of plant mitochondrial genomes.

Sphingolipids are essential components of eukaryotic membranes and play central roles in cellular growth and stress responses. In the budding yeast Saccharomyces cerevisiae, Lcb1 and Lcb2 constitute the serine palmitoyltransferase complex, which catalyzes the initial step of sphingolipid biosynthesis. Repression of LCB1 expression leads to inhibition of sphingolipid biosynthesis, resulting in severe growth defects. Here, we aimed to identify novel genes functionally associated with sphingolipid metabolism by screening for suppressor mutations that confer resistance to sphingolipid biosynthesis inhibition. To conditionally suppress sphingolipid biosynthesis, we employed a tetracycline-repressible promoter to control LCB1 expression. This screen revealed that deletion of SAC7, YTA7, RNR1, RPL23B, or RPL35A confers resistance to LCB1 repression. The suppressive effect of YTA7, RNR1, RPL23B, and RPL35A deletions was also observed under conditions in which growth inhibition was induced by repression of AUR1, a gene involved in the conversion of ceramides to complex sphingolipids. These genes encode proteins related to ribosomal subunits or DNA biosynthesis. Furthermore, sublethal concentrations of cycloheximide (a translation inhibitor), diazaborine (a ribosome maturation inhibitor), hydroxyurea (a DNA biosynthesis inhibitor), and zeocin (a DNA double-strand break inducer) alleviated growth defects caused by LCB1 repression. Diazaborine or hydroxyurea partly suppressed the decrease in complex sphingolipids induced by Lcb1 repression. Additionally, these treatments suppressed the reduction in Lcb1 and Aur1 protein expression levels. These findings reveal a previously unappreciated link between ribosome function, DNA biosynthesis, and sphingolipid metabolism and provide insight into how cells adapt to metabolic stress.

Equitable hereditary‑cancer genomics requires variant interpretation that performs reliably in under‑represented and admixed populations-not only in well‑sampled European cohorts. Building on Bianco and Planello (2025), this Comment outlines an equity‑by‑design workflow that couples regional allele‑frequency baselines (e.g., GenomeIndia, IndiGenomes, ABraOM) with calibrated functional evidence from saturation genome editing and related multiplex assays, implemented within updated ClinGen/ACMG‑AMP Bayesian point‑based frameworks. The pipeline defines sub‑national AF strata, quantifies AF uncertainty, maps quantitative functional readouts to PS3/BS3 strengths, and integrates AF, functional, in‑silico and clinical signals with transparent scoring while tracking fairness metrics (e.g., VUS rate ratios) and using patient‑centered reporting language. Overall, routinely combining local population priors with decision‑grade functional likelihoods provides a practical, auditable pathway to reduce VUS disparities and strengthen the global validity of clinical genomic interpretation.

To break the germplasm bottleneck that constrains afforestation in coastal and inland saline alkali soils, this study focused on Salix spp., a fast growing, ecological tree genus, and aimed to establish a highly efficient, low chimera protocol for tetraploid willow induction through refined colchicine treatment. The overarching objective was to expand forest genetic diversity and provide both theoretical insights and elite plant materials for the development of salt-tolerant willow cultivars. The colchicine-based chromosome doubling procedure was systematically optimized; 0.1% (w/v) colchicine for 12 h was identified as the optimal condition, and ploidy levels were verified by flow cytometry. Compared with the diploid controls, the induced tetraploids exhibited pronounced gigas characteristics: leaf length and width increased by 1.6- and 1.4-fold, respectively, and leaf fresh weight was 2.4-fold higher. After 14 d of 50 mmol/L NaCl treatment, tetraploids contained only 50% of the K⁺ level observed in diploids, resulting in a significantly higher K⁺/Na⁺ ratio. POD activity in tetraploids was approximately twice that of diploids, and total chlorophyll content was likewise 1.2-fold higher, collectively demonstrating superior growth performance and physiological homeostasis under saline conditions. These results demonstrate that the optimized chromosome doubling protocol markedly improves tetraploid induction efficiency and effectively enhances the salt tolerance of S. suchowensis. Future research will integrate whole genome re-sequencing to dissect dosage effects and identify key genomic loci governing salt tolerance, establish a marker assisted selection framework for accelerated tetraploid breeding, and conduct multi-site field trials to comprehensively evaluate stability and ecological adaptability. Such efforts are expected to expedite the commercial deployment of high salt tolerant willow cultivars in coastal shelter belt construction and large-scale saline alkali land restoration.

Chromosomal abnormality detection is a fundamental task in clinical genetics, as accurate identification of structural and numerical defects is essential for reliable diagnosis and treatment planning. However, many existing learning-based approaches failed to effectively capture diverse discriminative features, limiting their classification performance. To address this challenge, this study proposes FLEMBODA AI, an advanced computational framework designed to enhance the efficiency, accuracy, and robustness of automated chromosome defect detection. At first, the karyotype image is collected. Then, the input is augmented and pre-processed using normalization and a G-bending enhancement approach to ensure that the model's effectiveness generalizes across diverse datasets. After that, the chromosomes are segmented from the pre-processed image using a U-Net approach to isolate chromosomes from the karyotype image. Then, the segmented chromosomes are given as input to the Hybrid Fuzzy-Convolutional Neural Network (Hybrid Fuzzy-CNN) approach. In this, the CNN model performs the Feature Extraction (FE) process, and the Fuzzy logic is used for the classification of chromosomal abnormalities. Here, the VGG-16 is used for weight assignment for the classification. Then, using the Mask Region-centric CNN (Mask R-CNN), chromosome defect localization is performed. Experimental results demonstrate that FLEMBODA AI achieves a recall of 95.3%, precision of 94.8%, and an F1-score of 95.0%, outperforming baseline models. Additionally, the U-Net segmentation model attains an accuracy of 93.8%, contributing significantly to improved abnormality localization and classification performance. Overall, the proposed FLEMBODA AI framework provides a reliable as well as effective solution for automated chromosomal abnormality detection, with strong potential for application in clinical diagnostics and future large-scale genetic analysis systems.

Understanding and predicting protein-protein interactions (PPIs) between Penaeus vannamei and white spot syndrome virus (WSSV) is essential for elucidating viral infection mechanisms and developing antiviral strategies in shrimp aquaculture. Traditional experimental methods and classical homology-based computational approaches such as STRING have been used to identify shrimp-WSSV PPIs, but both face inherent limitations in accuracy and scalability. Recently, the breakthrough of AlphaFold3 has enabled PPI prediction from the perspective of complex structures, although its performance requires systematic evaluation. To address these gaps, this study establishes an integrated computational framework that combines homology-based network inference and structure-based (topology-based) complex modeling for predicting shrimp-WSSV PPIs. Homology-based interaction networks and 3D structural models of putative PPIs between three WSSV proteins and host proteins were constructed, including 2580 PPIs of wsv067, 389 PPIs of wsv172, and 2310 PPIs of wsv188. Notably, we found substantial discrepancies between STRING- and AlphaFold3-derived predictions, indicating that reliance on a single method may yield an numerous false positives. Nevertheless, interactions with high STRING scores showed a greater likelihood of forming structurally stable complexes in AlphaFold3. By applying dual thresholds (STRING score > 700 and composite AlphaFold3 score > 0.7) and validating representative complexes using molecular dynamics simulations, we identified a small but reliable set of high-confidence PPIs. These host proteins were primarily enriched in DNA replication, highlighting potential targets that may facilitate WSSV replication after invasion. Together, this work establishes a practical framework for prioritizing virus-host PPIs and reveals mechanistically plausible interactions between WSSV and shrimp, offering promising perspectives for antiviral target discovery and health management in aquaculture.