Search Results (1,650)

Cell-wall polysaccharide O-acetylation contributes to cell-wall assembly, organ development, and plant–pathogen interactions, but the cucumber TBL gene family remains poorly characterized. Here, 37 CsTBL genes were identified genome-wide and analyzed using phylogenetic, syntenic, conserved-motif, gene-structure, promoter, protein-structure, Gene Ontology, and transcriptome approaches, followed by RT-qPCR analysis after powdery mildew inoculation. All CsTBL proteins contained the conserved GDS and DxxH motifs, whereas accessory motifs and predicted structural features varied among clades. Intraspecific analysis identified dispersed, WGD/segmental, and tandem duplication categories, and cross-species synteny was more extensive with melon than with Arabidopsis. Homology-derived annotations associated CsTBL genes with cell-wall polysaccharide metabolism, Golgi/endomembrane compartments, and O-acetyltransferase activity, including six genes assigned to xylan O-acetyltransferase-related annotations. Expression profiling revealed tissue- and developmental-stage-dependent patterns, whereas the publicly available powdery mildew RNA-seq dataset provided descriptive temporal expression profiles in Podosphaera xanthii-inoculated samples. Independent RT-qPCR analysis using time-matched mock controls revealed distinct post-inoculation responses among six selected genes. Relative to the corresponding mock controls, CsTBL2 was consistently repressed; CsTBL15 showed transient induction at 1 dpi followed by repression; CsTBL24 exhibited a biphasic response; CsTBL25 was induced at all sampled post-inoculation time points; CsTBL26 showed progressive induction; and CsTBL30 reached its highest observed expression level at 3 dpi. Integrated functional annotation and expression evidence highlighted CsTBL26 as a priority candidate for further functional characterization, while CsTBL24 and CsTBL25 represented fruit-associated candidates with distinct powdery mildew responses; CsTBL30 remained an additional strongly infection-responsive candidate. These findings provide an evolutionary and expression-based framework for the functional characterization of the cucumber TBL gene family. Full article

Wheat (Triticum aestivum), a key global crop, faces rising drought stress that limits root growth and water uptake. Root meristem growth factors (RGFs) are small peptides that regulate root stem cell maintenance, meristem activity, and lateral root formation in model plants, yet the RGF gene family remains unexplored in wheat. Here, we performed a comprehensive genome-wide analysis of the TaRGF gene family, identifying 15 genes distributed across the A, B, and D subgenomes and classified into five homeologous groups (TaRGF1–TaRGF5), predominantly located on chromosomes 2 and 6. All TaRGFs contained a characteristic RGF motif, with dibasic cleavage sites and Asp–Tyr motifs indicating conserved maturation mechanisms. Based on the phylogenetic analysis, the TaRGF5 homeologs showed the highest similarity to Arabidopsis thaliana RGF5. Tested RNA-seq data revealed predominantly root-enriched expression for all TaRGF genes, with TaRGF5 exhibiting the most root-preferential and downregulation under drought stress. Quantitative real-time PCR (qRT-PCR) confirmed that drought stress suppressed the expression of TaRGF5A, TaRGF5B, and TaRGF5D in roots of wheat cultivar Sids-13 across all time points, unlike the higher accumulation seen in controls. Promoter analysis predicted a unique BES1 transcription factor binding site exclusively in TaRGF5B, linking brassinosteroid signaling to peptide-mediated root regulation. Structural modeling and molecular docking predicted an interaction between wheat TaRGF5 homeologs and root growth factor-insensitive receptor kinase (TaRGI3), characterized by conserved sulfotyrosine-mediated binding and favorable interaction energetics. Based on this characterization of the wheat RGF gene family, particularly the potential role of TaRGF5 in root development and drought-adaptation signaling, we propose targeting this gene for functional analysis to improve wheat resilience under water-limited conditions. Full article

Background/Objectives: Basal metabolic rate (BMR) is implicated in age-related phenotypes, and presbyopia represents a hallmark of ocular ageing. However, the association between BMR and presbyopia remains underexplored. Therefore, using a two-sample Mendelian randomisation (MR) approach, the present study aimed to evaluate the potential causal relationship between BMR and presbyopia in individuals of European ancestry. Methods: Instrumental variables comprised single-nucleotide polymorphisms associated with BMR at genome-wide significance (p < 5.0 × 10⁻⁸), derived from genome-wide association study summary statistics from the UK Biobank. Summary statistics for presbyopia were obtained from the FinnGen project. Causal estimates were primarily assessed using the inverse-variance weighted method and further evaluated using the weighted median method, MR–Egger regression, and the MR–Pleiotropy Residual Sum and Outlier test. Results: Genetically predicted higher BMR, expressed per 1-standard-deviation increase on the inverse-rank-normalised scale, was associated with lower odds of presbyopia. The inverse-variance weighted analysis yielded an odds ratio (OR) of 0.79 (95% confidence interval [CI]: 0.67–0.93; p = 0.004), with a directionally consistent estimate from the weighted median analysis (OR = 0.76, 95% CI: 0.59–0.99; p = 0.045). MR–Egger and SIMEX-corrected MR–Egger analyses yielded estimates in the same inverse direction, although their 95% CIs included the null (OR = 0.73, 95% CI: 0.50–1.05; p = 0.093 and OR = 0.71, 95% CI: 0.47–1.06; p = 0.092, respectively). The MR-PRESSO global test was nominally significant (p = 0.049), although no individual outlier was identified. In additional MVMR analyses incorporating BMI or standing height, the direct effect of BMR was not statistically significant in either model. Conclusions: These findings suggest a potential inverse association between higher genetically predicted BMR and the odds of presbyopia. However, MVMR analyses did not support a direct effect of BMR independent of BMI or height, warranting caution in interpreting the observed association as specific to metabolic rate. Further studies are required to validate these results and clarify the underlying biological mechanisms. Full article

Background/Objectives: Dehydrins (DHNs) are late embryogenesis abundant proteins that play protective roles under water-deficit conditions; however, their organization and function remain unexplored in sesame (Sesamum indicum), an important oilseed crop frequently cultivated in arid and semi-arid regions. This study aimed to identify and characterize the DHN gene family in sesame and evaluate the expression of its members under drought stress. Methods: Genome-wide identification was performed using the Dehydrin domain HMM profile, followed by phylogenetic analysis, conserved motif and gene structure characterization, synteny analysis, promoter cis-element profiling, and secondary/tertiary structure prediction. Transcriptional responses were profiled by qPCR in two sesame cultivars (drought-sensitive and drought-tolerant) under PEG-induced osmotic stress at germination and seedling stages. Results: Four DHN genes were identified, spanning three phylogenetic subfamilies (I–III) and three DHN subclasses: SK_n (SiDHN1/2), Y_nK_n (SiDHN3), and Y_nSK_n (SiDHN4). SiDHN1 and SiDHN2 likely arose from a segmental duplication, and a single conserved syntenic pair was found between SiDHN4 and olive (Olea europaea). Secondary structure predictions uncovered contrasting structural propensities: SiDHN1/2 are predicted to be α-helix-rich, partially ordered proteins (41–44% predicted α-helix), whereas SiDHN3/4 are predicted to be predominantly intrinsically disordered (~75–80% random coil). SiDHN3 was consistently upregulated across all conditions (1.84–9.12-fold), while SiDHN4 exhibited strong genotype-specific induction of 9.39-fold exclusively in the drought-tolerant cultivar during germination. Conclusions: The sesame DHN family achieves functional breadth through structural diversification—an ordered–disordered continuum mirrored by divergent expression programming—rather than through numerical expansion. SiDHN3 and SiDHN4 are identified as primary candidates for drought tolerance improvement in sesame. Full article

Chinese hickory (Carya cathayensis Sarg.) is an economically important tree species widely cultivated in southeastern China, where trunk canker disease caused by Botryosphaeria dothidea poses a serious threat to tree health and production. Pectin-degrading enzymes are important virulence-associated factors that facilitate fungal colonization and host tissue maceration, but their evolutionary diversification and functional roles in B. dothidea during woody host infection remain poorly understood. Comparative genomic analysis revealed lineage-specific variation in the GH28 glycoside hydrolase family among the examined Botryosphaeriaceae species, with B. dothidea exhibiting an expanded GH28 repertoire relative to the analyzed species. Expression analysis and functional assays revealed that BdGH28_3 showed the highest transcript abundance during infection stage and contributed to the full virulence of B. dothidea. A predicted protein–protein interaction (PPI) network suggested potential associations between BdGH28_3 and other pectinolytic enzymes, including polygalacturonases, pectin lyases, and pectinesterases. Collectively, these findings identify GH28 diversification as a distinctive feature of the B. dothidea genome and establish BdGH28_3 as a virulence-associated member, providing a foundation for investigating GH28-mediated pathogenicity in woody hosts. Full article

Candidatus Hepatincolaceae is a poorly characterized family of obligate Alphaproteobacterial symbionts that are widely detected in ecdysozoans. They were previously assumed to play a nutrient-scavenging role in the gut lumen. In this study, two high-quality metagenome-assembled genomes (MAGs, 1.39 Mb and 1.48 Mb in size) were recovered from the gut of the snapping shrimp Alpheus brevicristatus via metagenomic sequencing. Phylogenetic and whole-genome similarity analyses confirm that these two MAGs represent two novel, undescribed genera within the family Ca. Hepatincolaceae. Metabolic reconstruction reveals that they not only retain the canonical nutrient-scavenging pathways conserved across all Hepatincolaceae members, but also encode previously undocumented functional modules for antioxidant defense, vitamin B₁ and B₂ biosynthesis, and short-chain fatty acid production. They maintain a high oxygen-affinity cytochrome bd terminal oxidase to thrive in the anoxic gut microenvironment. Consistent with their symbiotic lifestyle, their genomes exhibit typical signatures of reductive evolution, such as reduced genome size, low GC content, and gene loss in amino acid and nucleotide de novo biosynthesis pathways. This study presents the first reported high-quality genomes of marine Ca. Hepatincolaceae symbionts, which are predicted to possess multiple metabolic functions extending beyond nutritional mutualism. Full article

Background: Research in behavioral genetics has demonstrated that genetic factors significantly contribute to individual differences in behavior, while environmental exposures shape gene expression through epigenetic mechanisms. This interaction is also relevant to the development of antisocial behavior and psychopathic traits. One of the first evidence of gene–environment interaction was the association between low-activity variants of the MAOA gene, childhood maltreatment, and increased risk of antisocial behavior [¹]. Similarly, our research in incarcerated populations showed that adverse paternal parenting is associated with higher levels of psychopathy and the HTR1B rs13212041 TT genotype appears to modulate the individual susceptibility to negative experiences [²]. Single genetic variants, however, exert only modest effects and current evidence supports a polygenic model in which multiple genetic factors interact with environmental adversity to influence neurodevelopment and behavioral outcomes. Using a genome-wide/endophenotype informed analysis, for example, we identified novel gene–environment interactions as risk factors for psychopathy, involving three independent genetic loci in interaction with paternal maltreatment, which were previously associated with disruptive behavior, temperament, and neuroticism [³]. More recently, we also evaluated whether machine-learning models, integrating behavioral, environmental, and genetic variables, could be helpful to predict psychopathic traits. Methods: We compared logistic regression, random forest, support vector machine, XGBoost, and multilayer perceptron. Results: Support vector machine showed the highest accuracy for predicting Psychopathy Check List-Revised (PCL-R) Factor 2 (antisocial lifestyle). Feature-importance analyses identified impulsivity (BIS-11), empathy (IRI), childhood maltreatment (MOPS), and 12 SNPs as the most informative predictors. Notably, removing genetic variables or MOPS scores substantially reduced the model accuracy, indicating that both genetic and environmental information meaningfully contributed to prediction of antisocial behavior. Conclusions: These findings confirm that genetic influences are neither deterministic nor sufficient to explain criminal behavior but may contribute to interindividual differences in vulnerability, particularly through their interaction with environmental and psychosocial factors. In forensic psychiatry, the integration of genetic and environmental information into behavioral assessment may provide additional objective correlates that complement, rather than replace, traditional clinical and psychosocial evaluations. Such an integrated approach could potentially contribute to a more comprehensive understanding of individual vulnerability and behavioral trajectories. However, the use of genetic information in assessments of criminal responsibility should be approached with caution and proven expertise, given the complex, multifactorial nature of antisocial and criminal behavior. Full article

Major airway diseases, including chronic obstructive pulmonary disease (COPD), asthma, bronchiectasis and chronic rhinosinusitis without nasal polyps (CRSsNP), frequently coexist and share inflammatory, epithelial and remodeling features. However, whether these clinically distinct airway disorders are driven by a unified genetic liability and how this shared liability maps to disease-relevant tissues, genes and immune-regulatory programs remain incompletely understood. We integrated GWAS summary statistics for COPD, asthma, bronchiectasis and CRSsNP using linkage disequilibrium score regression, local genetic correlation analysis and Genomic structural equation modeling. A latent shared airway disease factor, termed gAirwayDisease, was constructed to capture common genetic liability across the four conditions. We then applied an integrative functional genomics framework, including gsMap spatial enrichment, PoPS gene prioritization, MAGMA gene-set enrichment, GTEx v8 lung MTWAS, OneK1K and DICE immune-cell MTWAS, scMORE regulon analysis and phenome-wide Mendelian randomization. All six airway disease pairs showed positive genetic correlations, with estimates ranging from 0.508 to 0.685. Genomic SEM supported a single shared factor, with positive standardized loadings for COPD, asthma, bronchiectasis and CRSsNP and excellent model fit. Spatial mapping localized gAirwayDisease-associated signals to airway- and epithelial-associated anatomical domains. PoPS prioritized immune and airway-relevant genes, including SMAD3, GATA3, IL1R1, RUNX3 and STAT6, while MAGMA enrichment highlighted B-cell activation, T-cell activation and transcriptional regulatory pathways. Lung MTWAS identified SLC9A2 and ORMDL3 as top genetically regulated expression signals. OneK1K immune-cell MTWAS highlighted recurrent IL18R1 associations across CD4 and CD8 T-cell subsets. scMORE further identified 36 significant regulon–cell type pairs across dendritic cells, B cells, monocytes, T cells and NK cells, including BCL11A, TCF4, KLF4, RUNX1 and STAT4 regulons. MR-PheWAS linked genetically predicted gAirwayDisease to respiratory, allergic, lung function and immune-related traits. This study defines gAirwayDisease as a genetically informed latent factor capturing shared liability across major airway diseases. Integrated functional genomic analyses highlight airway epithelial and immune regulatory programs associated with shared disease susceptibility and prioritize candidate genes and regulons for future experimental validation. Full article

Background/Objectives: Colorectal cancer (CRC) remains a leading cause of cancer-associated mortality worldwide. The current therapeutic interventions are heavily constrained by the development of resistance and severe systemic toxicity. To address these challenges, this study integrated a multi-disciplinary framework involving high-throughput in silico screening followed by in vitro experimental validation to identify novel genetic targets of CRC and evaluate the efficacy of FDA-approved drugs. The primary objective was to identify safe and selective therapeutic agents capable of modulating their effect. Methods: The methodology employed a systematic screening of recent large-scale Genome-Wide Association Studies (GWASs) to pinpoint novel targets, followed by in silico pathogenicity prediction, homology modelling and high-throughput virtual screening of over 1615 FDA-approved drugs. The prioritized candidates were validated in vitro using MTT cytotoxicity assays and differential gene expression analysis across CRC cell lines (HCT116 and HT29) and a non-tumorigenic control, Human embryonic kidney cell line HEK293. Results: In silico analysis identified CLUH, CLSTN3 and SLC11A2 as novel potential targets. Based on in silico predicted deleterious mutations and subsequent molecular docking-based virtual screening, Telmisartan, Dutasteride and Venetoclax were prioritized. This prioritization was supported by their high binding affinity and dose-dependent cytotoxicity in MTT assays; thus, suggesting their repurposing potential for CRC treatment. Telmisartan exhibited a superior therapeutic profile not only in terms of the statistically significant cytotoxicity (p < 0.01), but also its selective effect on HCT116 and HT29 when compared to high safety profile in HEK293. This was further validated when Telmisartan selectively downregulated CLUH and SLC11A2 in CRC cell lines, HCT116 and HT29 while maintaining expression levels in the non-cancerous HEK293 cell line remained significantly unaffected. Furthermore, a 100 ns molecular dynamics simulation confirmed the stable binding conformation and structural reliability of the SLC11A2 (Trp179Ser)–Telmisartan complex. Conclucions: Our findings conclude that Telmisartan is a promising candidate for drug repurposing for CRC treatment and capable of modulating selected novel biomarkers CLUH and SLC11A2. However, further multi-omics-based confirmatory studies and pre-clinical validation studies are needed in the future to confirm the long-term efficacy of this repositioning strategy. Full article

Currently, the global incidence of head and neck squamous cell carcinoma (HNSCC) continues to increase, with a large proportion of cases being diagnosed at advanced stages. Conventional oncological treatments are often associated with poor quality of life, while the aggressive biological behavior of these tumors results in recurrence in approximately half of treated patients according to current evidence. The need for rapid, targeted diagnosis and personalized treatment has driven research toward the identification of tumor biomarkers with diagnostic, prognostic, and predictive value for treatment response. In this scoping review, we performed a comprehensive literature search to map the available evidence on tumor biomarkers in HNSCC. We identified a wide range of biomarkers, several of which exhibit overlapping roles, and classified them according to their genomic, proteomic, cytokine-related, tumor microenvironment, metabolic, and microbiota-associated characteristics. This scoping review also summarizes the current evidence regarding biomarkers involved in carcinogenesis, treatment response and therapy resistance, while highlighting their current level of clinical applicability. Although only a limited number of biomarkers have currently been implemented in routine clinical practice in head and neck cancers, the studies included in this review identified several promising candidates with the potential to be incorporated into clinical practice following further prospective validation and methodological standardization. Many additional biomarkers are still under investigation, opening new perspectives for future diagnostic and therapeutic targets and supporting the development of personalized multimodal treatment strategies for patients with HNSCC. Full article

Rainbow trout (Oncorhynchus mykiss) is an important cold-water aquaculture species and a tractable salmonid model for functional genomics. Rapid advances in chromosome-level genome assemblies, genetic variation resources, regulatory annotations, tissue and cell models, controlled challenge systems, and genome-editing technologies have established an increasingly integrated framework for linking genomic variation with measurable phenotypes. Evidence from studies of mucosal immunity, disease-resistance genetics, and environmental stress responses indicates that these resources can improve candidate-gene prioritization and mechanistic interpretation across molecular, cellular, tissue, and whole-fish levels. However, differential gene expression, quantitative trait locus and genome-wide association signals, genomic predictions, and cell-type localization remain largely associative and rarely provide direct evidence of causality. Interpretation is further complicated by salmonid-specific whole-genome duplication, because retained paralogues may exhibit tissue-specific divergence, functional redundancy, and compensatory responses. Further progress will require the integration of pangenomics, regulatory annotation, single-cell and spatial analyses, and paralogue-aware functional perturbation in both cell-based and whole-fish systems. Such integration will strengthen causal inference, clarify genotype–phenotype relationships, and support disease-resistant breeding, healthy aquaculture, and environmental risk assessment. Full article

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression through a sequence-specific recognition of their targets, leading to degradation or inhibition of translation. In the case of plant miRNAs, they have been involved in a multitude of biological processes, from developmental processes to environmental stress responses. Massive sequencing by RNA-seq is becoming a widely used technique to discover plant miRNAs. However, if costs are considered, bioinformatics prediction is a valuable tool for miRNA discovery in plants. Among the tools available, ShortStack is the best for comprehensive prediction and annotation of miRNAs. Therefore, ShortStack was used in this study to predict miRNAs of common bean (Phaseolus vulgaris), one of the most important legumes in the world. Briefly, a high-stringency, homology-based in silico pipeline was followed to systematically predict miRNAs of P. vulgaris without the dependency on high-throughput experimental sequencing infrastructure; meaning that this study was based exclusively on computationally generated miRNA datasets derived from miRbase. Therefore, no biological small RNA-seq, degradome sequencing, or expression validation were performed in this study. In total, 57 distinct, non-redundant clusters were predicted, from which 35 miRNAs showed unique characteristic sequences. Comparative genomic cross-referencing against historical seminal common bean datasets supported our predicted loci, finding that 18 out of the 35 miRNA sequences were located at the same genomic coordinates as the previously reported loci. In addition, functional categorization of all the potential target genes revealed their putative roles in plant development and other cellular processes. It is important to emphasize that, although the predicted loci in P. vulgaris represent candidate miRNAs that require independent experimental validation, this work serves as a foundational approach to be applied for the prediction of miRNAs in underexplored plant species or those with limited genomic resources. Full article

Low-coverage whole-genome resequencing (lcWGS) is emerging as a powerful population-scale genomic strategy for livestock and poultry research. By integrating sparse sequencing reads with genotype likelihoods, haplotype information and imputation models, lcWGS enables genome-wide variant discovery and genetic inference across large animal cohorts. This feature is particularly valuable for breeding populations, indigenous breeds and conservation resources, where broad sampling is essential for capturing population-specific variation and linking genomic diversity with economically and adaptively important traits. In this review, we synthesize the statistical foundations, analytical workflows and major applications of lcWGS in livestock and poultry genomics. We discuss how lcWGS supports genetic diversity assessment, population structure analysis, genome-wide association studies, genomic selection, selection-signature detection, environmental adaptation research and genetic resource conservation. We further highlight the importance of coordinated study design, including sequencing depth, sample size, reference-panel construction, imputation strategy, phenotype quality and downstream analytical models. Beyond its role as a cost-efficient genotyping approach, lcWGS provides a flexible framework for integrating population genomics with functional annotation, multi-omics resources, long-read assemblies, graph pan-genomes and interpretable prediction models. These developments are expanding the potential of lcWGS from variant discovery toward biological interpretation, precision breeding, climate-resilient animal production and the sustainable management of livestock and poultry genetic resources. Full article

The dried roots and rhizomes of Salvia miltiorrhiza are widely used and economically important traditional Chinese medicinal materials. Land salinization affects the growth of S. miltiorrhiza, resulting in a decline in its quality and yield. WNK kinases belong to a unique family of serine/threonine kinases. They act as key regulators of plant growth, development and abiotic stress responses. However, this gene family has not been systematically characterized in Salvia miltiorrhiza. In this study, nine SmWNK genes were identified at the whole-genome level in S. miltiorrhiza. Phylogenetic analysis classified them into four structurally conserved subgroups. These genes are distributed across eight chromosomes and contain two pairs of intraspecific syntenic genes. Interspecific collinearity is far stronger between S. miltiorrhiza and dicots than between S. miltiorrhiza and monocots. Cis-element prediction indicated these cis-elements participate in light signaling, hormone responses, stress responses and developmental regulation. Quantitative real-time PCR revealed that eight SmWNK genes were significantly induced by salt stress, and SmWNK7 was selected as the key candidate for functional validation. Functional assays via heterologous overexpression in tobacco demonstrated that SmWNK7 overexpression promoted root elongation and enhanced salt tolerance. Compared with wild-type tobacco plants, SmWNK7-overexpressing transgenic tobacco lines had higher catalase (CAT) and peroxidase (POD) activities, lower malondialdehyde (MDA) content, and stronger root viability. These changes alleviated oxidative damage by enhancing the antioxidant defense system. Yeast two-hybrid screening yielded 40 SmWNK7-interacting annotated proteins, including 6 transcription factors and 1 protein kinase, which were enriched in 81 GO terms and 27 KEGG pathways. These findings confirm SmWNK7 positively regulates root growth and salt tolerance, laying a theoretical foundation for exploring SmWNK genes’ role in plant stress adaptation. Full article

The calcium ion-transporting ATPase (Ca²⁺-ATPase) gene family maintains plant intracellular Ca²⁺ homeostasis and regulates growth, development and stress immunity; however, its functions remain poorly characterized in Malus domestica. Here, we performed a genome-wide identification of apple Ca²⁺-ATPase genes and obtained 45 members, which were classified into MdACA (39) and MdECA (6) subfamilies and unevenly distributed on 14 chromosomes. Phylogenetic analysis of Ca²⁺-ATPase genes from Malus domestica, Arabidopsis thaliana, and Oryza sativa classified these proteins into five subgroups. The ACA and ECA subfamilies were highly conserved across species, whereas Group D was apple-specific. Collinearity and Ka/Ks analyses indicated that segmental duplication and purifying selection dominated the evolution of apple Ca²⁺-ATPase genes. Promoter cis-element prediction uncovered numerous regulatory elements related to phytohormone signaling, growth, development and stress defense. Codon usage bias analysis indicated that AUG (methionine) was the dominant codon. Tissue expression profiles showed differential expression of apple Ca²⁺-ATPase genes in various organs. Quantitative real-time PCR (qRT-PCR) assays demonstrated widespread responses of Ca²⁺-ATPase genes to Alternaria alternata infection, exogenous CaCl₂, salicylic acid (SA) and methyl jasmonate (MeJA), among which MdACA39 was strongly induced under all treatments. Subcellular localization verified that MdACA39 resides on the plasma membrane. Moreover, transient overexpression of MdACA39 significantly enhanced apple resistance to A. alternata, likely due to the activation of SA, MeJA and Ca²⁺ signaling-mediated immune pathways, the induction of disease resistance-related genes, and elevated antioxidant enzyme activity. Collectively, this study systematically characterizes the apple Ca²⁺-ATPase family and identifies MdACA39 as a key regulator of fungal resistance, providing valuable gene resources for dissecting Ca²⁺ signaling-mediated disease resistance in apple. Full article