Search Results (7,968)

Accurate genealogical records are essential in livestock breeding for maintaining genetic diversity, preventing inbreeding, and mapping of economically important traits in beef production. This study aimed to assess parent–offspring relationships within South African Bonsmara and Nguni cattle populations using both traditional pedigree records and genomic data. Hair samples from 119 Nguni and 311 Bonsmara cattle were genotyped using the BovineSNP50 array, and these were imputed to Illumina BovineHD BeadChip using updated SNP coordinates from the assembly genome (ARC—UCSD 1.2). Quality control and data filtering were performed using PLINK v1.9, while relationship inference was conducted using KING v2.2.8 and PLINK v1.9 software for principal component analysis, IBD metrics and Mendelian error-based exclusion. Categories of relatedness through network relationship analysis revealed a predominance of half-sibling relationships in both breeds, with 2317 such relationships identified in Nguni and 1221 in Bonsmara. Inference of parent–offspring pairs showed discrepancies with the recorded pedigrees, with 49 inferred pairs compared to 47 recorded pairs in Nguni, and 62 inferred pairs compared to 75 pairs recorded in Bonsmara. Relationships based on IBD using PLINK with a ‘PI-HAT’ threshold greater than 0.45 revealed unique parent–offspring inferences that differed from those obtained using KING v2.2.8. Phylogenetic network analysis assigned each individual’s genomic origin independent of the pedigree records, supporting the efficiency of SNP data for genetic assignment. These results demonstrated that SNP-based pedigree verification can accurately identify parent–offspring and half-sibling relationships, providing a reliable foundation for recombination analysis and supporting precise trait mapping and informed selection in breeding programs. Full article

Background: The etiopathogenesis of juvenile systemic lupus erythematosus (JSLE), a complex and complicated illness, is unknown. Genetic, environmental, and dysregulated immune system responses are all thought to contribute to the disease’s etiology. Important immunological molecules that regulate different immune cells and are associated with autoimmune disorders are TNFSF4 and IKZF1. Thus, our purpose was to discover if TNFSF4 and IKZF1 mutations left the Egyptian population genetically predisposed to SLE. Methods: Using real-time polymerase chain reaction (RT-PCR), polymorphism analysis of the TNFSF4 rs1234315 C/T and IKZF1 rs11980379 C/T genes was performed on extracted DNA from JSLE patients and healthy controls. Results: TNFSF4 frequencies (rs1234315 T allele, CT, TT genotypes, dominant and recessive models) were substantially associated with a higher incidence of JSLE (p < 0.05) compared to healthy controls. Conversely, IKZF1 frequencies (rs11980379 T allele, TC, TT genotypes, and dominant model) significantly correlated with a lower incidence of JSLE. Furthermore, the TC + CC rs11980379 genotype was identified as significantly associated with lower kidney biopsy grades and a lower incidence of lupus nephritis. Conclusions: Our findings suggest that TNFSF4 and IKZF1 polymorphisms affect vulnerability to juvenile SLE. Full article

Background: Inherited kidney diseases represent a genetically and clinically heterogeneous group of disorders affecting both pediatric and adult populations. Advances in next-generation sequencing (NGS) have improved diagnostic precision; however, genotype–phenotype correlations and diagnostic yield vary substantially across disease entities. Methods:We retrospectively evaluated 165 patients referred for genetic testing due to suspected inherited kidney disease. Patients were classified into three clinical groups: polycystic kidney disease, Alport syndrome, and other syndromic patients with inherited kidney diseases. Genetic analysis was performed using NGS with Human Phenotype Ontology–based gene filtering and included evaluation of both single-nucleotide variants and copy number variations. Results: Overall diagnostic yield differed markedly between groups. A molecular diagnosis was achieved in 71.4% of Alport patients, 41.0% of PKD patients, and 70.2% of patients in the Other syndromic group. In the Alport group, variants were identified exclusively in COL4A3, COL4A4, and COL4A5, with pathogenicity and gene involvement correlating with disease severity and the presence of extrarenal manifestations. The PKD group showed predominant involvement of PKD1, followed by PKHD1 and PKD2, while a substantial proportion of patients remained genetically negative, reflecting technical and biological complexity. The Other group exhibited pronounced genetic heterogeneity, with variants distributed across multiple genes involved in tubular, glomerular, metabolic, and ciliopathy-related pathways. Computational assessments demonstrated that several variants of uncertain significance (VUS) were located in functionally critical domains and were predicted to disrupt protein stability, intermolecular interactions, or conserved structural motifs, thereby supporting the biological plausibility of their potential pathogenic impact. Conclusions: Phenotype-driven NGS enables effective molecular diagnosis across diverse inherited kidney diseases while revealing disease-specific differences in diagnostic yield and genotype–phenotype correlations. Systematic inclusion of variants of uncertain significance and careful integration of genetic and clinical data are essential for accurate interpretation and long-term patient management. Collectively, this study enhances understanding of inherited kidney diseases and underscores the value of integrating comprehensive genomic and computational approaches into routine nephrogenetic practice. Full article

Background/Objectives: Responses to lifestyle interventions vary widely in obesity, and genetic factors may enhance outcomes. This study evaluated whether a 12-week genotype-informed personalized nutrition education (GEN) program improved weight and overall body composition among adults with obesity. Methods: Adults with a body mass index ≥ 25 kg/m² were randomized to a genotype-informed personalized nutrition education (GEN) group or a control group receiving standard nutrition education. The GEN group received weekly counseling tailored to nine obesity-related genetic traits. Changes were evaluated using paired t-tests and repeated-measures analysis of variance, with significance defined as p < 0.05. Results: Forty-three participants (GEN: n = 19; CON: n = 24) were analyzed. After 12 weeks, the GEN group showed significantly greater reductions than the CON group in body weight (−3.35 ± 0.7 vs. –0.91 ± 0.4 kg, p = 0.004), BMI (–1.17 ± 0.3 vs. –0.32 ± 0.1 kg/m², p = 0.005), and waist circumference (–5.56 ± 0.8 vs. –2.53 ± 0.7 cm, p < 0.001). Energy (–415 kcal, p = 0.003) and carbohydrate intake (–65 g, p = 0.003) also decreased significantly in the GEN group. Exploratory subgroup analyses suggested that participants classified as high genetic risk showed more pronounced improvements when receiving genotype-informed counseling. No serious adverse events were reported. Conclusions: The genotype-informed personalized nutrition program was associated with greater improvements in body composition than general nutrition education. Integrating genetic risk information into structured nutrition education may enhance perceived personal relevance and support effective weight management. Full article

Background: Persistent infection with high-risk human papillomavirus (hr-HPV) is the necessary agent of cervical cancer, yet its molecular definition remains heterogeneous. Multiple molecular approaches have been developed to characterize HPV persistence, including repeated detection of viral DNA, assessment of viral oncogene expression, and analysis of HPV-related DNA methylation. These approaches originate from different scientific traditions and reflect distinct conceptualizations of persistence. Objective: To synthesize and compare molecular methods used to detect persistent HPV infection through a narrative review and to clarify how different biomarkers conceptualize HPV persistence and disease progression. Methods: We conducted a narrative review in accordance with the RAMESES guidelines. Medline, Scopus, and the Cochrane Library were searched for original studies published between 2016 and 2025 investigating molecular markers of HPV persistence. An interpretive synthesis was performed to identify research traditions, underlying assumptions, and clinical implications. Results: Three major molecular narratives were identified. Persistent DNA positivity defines persistence as repeated detection of the same HR-HPV genotype over time and reflects an epidemiological–virological perspective with high sensitivity but limited specificity. Persistent oncogene expression, assessed by E6/E7 mRNA detection, conceptualizes persistence as active viral oncogenic activity and shows improved specificity for clinically relevant lesions. Persistent epigenetic imprint, measured by DNA methylation of viral and host genes, captures cumulative biological effects of long-term infection and is strongly associated with high-grade lesions and cervical cancer. These narratives represent complementary stages along a continuum of molecular persistence. Conclusions: Molecular markers of HPV persistence reflect the evolving understanding of cervical carcinogenesis, progressing from repeated viral DNA detection to oncogenic activity and stable epigenetic alterations. These complementary biomarkers represent different biological stages of persistent infection and may improve risk stratification in HPV-based screening and triage strategies. Full article

The common bean (Phaseolus vulgaris L.) cultivar Jalo Vermelho carries the Co-12 gene, which confers resistance to both Andean and Mesoamerican races of Colletotrichum lindemuthianum. Despite its importance for breeding programs, the genomic location and candidate genes underlying this resistance remain poorly defined. The Co-12 locus was fine-mapped using a biparental population derived from the cross Jalo Vermelho × Crioulo 159. A total of 172 F₂ plants were used to generate 172 F_2:3 families, which were phenotyped after inoculation with race 1545 of C. lindemuthianum. Segregation analysis confirmed a 1:2:1 Mendelian ratio, consistent with a single dominant resistance gene. Genotyping of resistant and susceptible plants using the BARBean6K_3 Illumina BeadChip (5398 SNP markers) mapped Co-12 to chromosome Pv04, between 1695 bp (ss715649768) and 9,651,954 bp (ss715646644). Subsequent fine mapping with simple sequence repeat (SSR) markers delimited the locus to a 41 kb genomic interval flanked by BARCPVSSR04557 and BARCPVSSR04570. Within this region, three candidate genes were identified, including one encoding a gamma-glutamyl-GABA enzyme and two encoding lipid transfer proteins (LTP2). Lipid transfer proteins are widely recognized components of plant defense; however, their association with anthracnose resistance in the common bean has not been previously reported. The identification of LTP2 genes within the Co-12 interval suggests a previously unrecognized resistance mechanism and expands the current understanding of host defense pathways in Phaseolus vulgaris. The markers identified here provide valuable tools for marker-assisted selection and will facilitate efficient introgression of Co-12 into common bean cultivars. Full article

Background/Objectives: To evaluate the diagnostic yield of phenotype-guided cytogenetic and targeted molecular genetic testing in patients referred for infertility and reproductive disorders within a tertiary medical genetics referral pathway. Methods: This retrospective study included 900 consecutive patients (473 males, 427 females) referred to a tertiary medical genetics center between January 2020 and December 2024. Conventional karyotyping was performed in all patients. Additional targeted molecular tests were applied based on clinical indication: Y chromosome microdeletion analysis in azoospermia or oligospermia, CFTR sequencing in suspected congenital bilateral absence of the vas deferens, and F2/F5 genotyping in recurrent pregnancy loss (RPL). Diagnostic yield was analyzed in a predefined subgroup of 566 patients with RPL, unexplained infertility, azoospermia, or oligospermia; remaining referrals were included in descriptive cytogenetic analyses only. Results: Chromosomal abnormalities were identified in 3.22% (29/900) of the total cohort and in 5.12% (29/566) of the diagnostic-yield cohort. Targeted testing yields were 3.75% (6/160) for Y chromosome microdeletions, 9.38% (3/32) for CFTR variants, and 3.31% (4/121) for F2/F5 variants. Diagnostic yield varied markedly by phenotype, being highest in azoospermia (33.3%), followed by oligospermia (6.6%), RPL (5.3%), and unexplained infertility (3.1%). In unexplained infertility, all chromosomal abnormalities were detected in female patients. Conclusions: In a tertiary referral setting, phenotype-guided genetic testing provides the greatest diagnostic value in well-defined infertility phenotypes, particularly azoospermia. Lower yields in other referral groups support a targeted, indication-based approach to genetic evaluation and highlight the need for advanced genomic strategies in persistently unexplained cases. Full article

Cryptosporidium spp. and Giardia duodenalis are globally important intestinal protozoa causing diarrheal disease in humans and animals, with significant zoonotic potential. This study aimed to investigate the prevalence, molecular diversity, and potential transmission dynamics of these parasites in humans, livestock, and environmental samples from a rural community in Türkiye using a One Health approach, and to assess their associations with gut microbiome composition. Faecal samples were collected from 124 humans, 305 livestock (cattle, sheep, and goats), and 40 environmental samples (water and mud). Parasites were detected using qPCR and nested PCR, with positive samples genotyped by sequencing. Microbiome profiling was performed using 16S rRNA gene amplicon sequencing. Giardia duodenalis was detected in 12.1% of humans, 17.5% of livestock, and 2.5% of environmental samples, with assemblages A, B, and E identified, including the first detection of assemblage E in a human in Türkiye. Cryptosporidium spp. were found in 8.9% of humans, 19.3% of livestock, and 55% of environmental samples, with C. parvum as the dominant zoonotic species. Microbiome analysis revealed no significant differences in overall diversity. This study provides the first One Health assessment of Cryptosporidium spp. and Giardia duodenalis in Türkiye, emphasizing zoonotic transmission risks linked to livestock and the environment. Full article

Background: Cervical cancer remains a major global health burden, with squamous cell carcinoma (SCC) and adenocarcinoma (ADC) representing the two predominant histological subtypes. Comparative clinicopathological patterns between SCC and ADC in contemporary cohorts remain of interest, but inference is often limited by small single-center datasets. Methods: We conducted a retrospective single-center cohort analysis of cervical cancer patients treated between 2020 and 2024. Demographic, clinical, and pathological variables, including p16 immunohistochemistry, histological subtype, differentiation grade, FIGO stage, and survival status, were analyzed. Comparative analyses were performed using appropriate exact tests, and survival was assessed using Kaplan–Meier methods. Results: The cohort included 85 patients: 69 with squamous cell carcinoma and 16 with adenocarcinoma. Both subtypes demonstrated similarly high p16 positive rates (89.9% vs. 93.8%, p = 1.00). Menopausal status emerged as a distinguishing factor (p = 0.0047), with SCC patients more likely to be postmenopausal. SCC patients were older on average (52.16 vs. 48.2 years: p = 0.0131). Analyses involving p16 status were interpreted descriptively due to the very small number of p16-negative cases. Kaplan–Meier analysis revealed significant survival differences by clinical stage (log-rank p = 0.03), with high-stage patients showing progressive decline from 95% to 73% survival over five years, while low-stage patients maintained 100% survival. Conclusions: In this retrospective single-center cohort, SCC and ADC showed similar p16 positivity rates and clinical stage remained the most informative prognostic variable. Apparent subtype-related demographic differences and multivariable associations should be considered hypothesis-generating rather than definitive. Larger multicenter studies with standardized pathology and p16 assessment, direct HPV testing/genotyping, and more complete clinical and prevention-related data are needed before prognostic or clinical conclusions are drawn. Full article

Broccoli is rich in glucosinolates (GSLs), secondary metabolites that contribute to both plant defense and human health. Optimizing the composition of major aliphatic GSLs is an important breeding objective, yet robust molecular markers for marker-assisted selection (MAS) remain limited. In this study, candidate gene-based kompetitive allele-specific PCR (KASP) markers were developed from conserved GSL biosynthesis genes, focusing on AOP2 and GSL-OH selected from 19 GSL-related genes. Marker–trait associations were evaluated in a natural broccoli population and further validated in an independent F₂ population. Among the tested markers, S101, located in AOP2, exhibited consistent genotype-dependent effects on GNA and PRO across both populations, supporting its stable predictive value. Receiver operating characteristic (ROC) analysis further confirmed strong classification performance of S101 for distinguishing high- and low-content genotypes of these traits in the F₂ population. In contrast, S074 and S035 showed population-dependent effects, with significant associations detected only in the natural population. Although association signals were reduced under mixed linear model (MLM) analysis with false discovery rate (FDR) correction, major loci identified under the general linear model (GLM) framework remained detectable. Overall, these results demonstrate the potential of candidate gene-based KASP markers for improving aliphatic GSL composition in broccoli through marker-assisted selection. Full article

Although greenhouse vegetable production is rapidly shifting toward innovative soilless systems, soil-based conventional cultivation still dominates globally. This production system faces growing pressure to transition to sustainable practices. However, introducing biofertilisers into intensive systems often yields inconsistent results. Specifically, their effects on different lettuce traits vary due to complex relationships between genotype, biofertiliser, environmental conditions, and market demands. Single-parameter evaluations fail to balance conflicting criteria, necessitating multi-criteria decision-making (MCDM) methods for selecting optimal choices. This study aims to overcome these inconsistencies through an integrated fuzzy MCDM-based optimisation model. Three lettuce cultivars (‘Carmesi’, ‘Aquino’, and ‘Gaugin’) were grown in an unheated Surčin (Serbia) greenhouse during a 58-day autumn experiment using a complete block design. Four treatments were applied: a control (without fertilisation), effective microorganisms, a Trichoderma-based fertiliser, and their combination. Biofertilisers were applied before transplanting and four times foliarly during the vegetation period via battery sprayer. This defined 12 production models (cultivar–fertiliser pairs), evaluated across 10 criteria: agronomic (core ratio, number of leaves), quality (nitrate content, total antioxidant capacity, total soluble solids, and chlorogenic acid), sensory (overall taste, overall quality), and economic (total variable costs, total income). Four decision-making experts from the Faculty of Agriculture and the ready-to-eat salad industry assessed weighting coefficients using the fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method. The fuzzy MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution) method was used to rank the alternatives. To confirm the stability of the obtained ranking with the fuzzy MARCOS method, we performed sensitivity analysis through 20 different scenarios. Applied fuzzy methods identified alternative A11—‘Aquino’ cultivar with combined biofertilisers—as the best-ranked option, followed by A6 and A7. This study validates fuzzy PIPRECIA and fuzzy MARCOS as effective tools for optimising lettuce production models. They support farmers in selecting the most favourable solution based on multiple criteria, aiding the shift from mineral fertilisers to sustainable biofertiliser-based systems in intensive production—especially helpful for producers making this transition. Full article

(1) Background: Swine hepatitis E (SHE) is an emerging zoonotic disease caused by the swine hepatitis E virus (SHEV). The open reading frame 3 (ORF3) protein is a recognized virulence factor of SHEV. Jaundice, the typical clinical sign of SHE, primarily results from disruptions in bile production, secretion, and excretion. However, the mechanism by which SHEV ORF3 influences bile metabolism remains unclear. (2) Methods: Building on our previous work involving adenovirus-mediated overexpression of genotype IV SHEV ORF3 in HepG2 cells and subsequent high-throughput lncRNA/transcriptome sequencing, this study performed KEGG enrichment analysis on differentially expressed lncRNAs. Candidate lncRNAs were validated via qRT-PCR. Cis-regulated target genes were predicted by integrating differentially expressed mRNA data. Furthermore, AlphaFold 3.0 was employed to analyze the molecular binding sites between lncRNA UBC (MSTRG.6881.4) and its target, UBC protein. (3) Results: We identified three lncRNAs associated with the bile secretion pathway (ko 04976) in HepG2 cells expressing genotype IV SHEV ORF3, which were further confirmed by qRT-PCR: lncRNA UBC (MSTRG.6881.4), lncRNA UBC (MSTRG.6881.9), and lncRNA UBC (MSTRG.6881.12). Bioinformatics prediction suggested six lncRNA-mRNA regulatory networks involved these lncRNAs and two downregulated UBC mRNA transcripts (ENST00000540700 and ENST00000536769). Molecular docking indicated that nucleotides 395U and 41C of lncRNA UBC (MSTRG.6881.4) could potentially bind to residues 82Lys, 88Thr, and 90Thr of the UBC protein, with predicted binding energies ranging from −4.73 to −0.75 kcal/mol. (4) Conclusions: The successful identification of bile secretion-related lncRNAs, coupled with the prediction of their regulatory networks and molecular interaction sites, has advanced our understanding of SHEV ORF3 function and the pathogenesis of SHEV infection. Full article

Background: Clinical outcomes for multiple myeloma are highly variable. Inherited genetic variants of immune regulatory genes can modulate disease susceptibility and clinical outcomes. The germline variant CTLA4 rs231775 polymorphism may alter T-cell function and affect clinical outcomes. Methods: We conducted a retrospective single-center study including 156 consecutive myeloma patients who underwent first-line ASCT. The patients were stratified according to the CTLA4 rs231775 genotype and disease stage (ISS I–III). Results: The CTLA4 rs231775 AA genotype was associated with inferior PFS in ISS I–II and superior PFS in ISS III. In the multivariate analysis, the CTLA4 rs231775 AA genotype emerged as a potential risk factor in ISS I-II and a potential protective factor in ISS III. Conclusions: This germline CTLA4 polymorphism may serve as biomarker to refine post-transplant risk stratification and enable personalized treatment management. Full article

The aim of this work was to develop a model using Artificial Neural Networks (ANN) to predict stem cutting parameters for giant miscanthus. Experimental studies were conducted to determine biometric traits: maximum stem diameter (Dmax), minimum stem diameter (Dmin), stem wall thickness (THwall), and strength parameters (cutting force, cutting work) for two giant miscanthus genotypes, depending on the internode number (NrNod) and water content (MC). A total of 600 measurement results were obtained, which were randomly divided into training (60%), test (20%), and validation (20%) subsets. Two semantic models were adopted: one for predicting stem cutting force (ann1) and one for predicting cutting work (ann2). The independent variables (ANN inputs) were: Gen, MC, NrNod, Dmax, Dmin, and THwall. The ANN creation process was performed using Statistica Neural Networks. For each of the two semantic models (ANN1 and ANN2), 100 neural networks were developed, with the top 10 ANNs retained for further analysis. The criterion for selecting the best neural network was the root mean square error (RMSE) for the test subset. For ANN1, the RMSE values varied from 6.89 N to 8.70 N. For ANN2, the RMSE values varied from 0.086 J to 0.102 J. For the most accurate ANN1-03 (MLP 7-10-1), used to predict grass cutting force, the RMSE values were 6.46 N–6.89 N–4.70 N for the training, test, and validation subsets. For the most accurate ANN2-02 (MLP 7-10-1), used to predict grass cutting work, the RMSE values were 0.0646 J–0.0857 J–0.0596 J for the training, test, and validation subsets. Full article

Screening potato germplasm for low nitrogen (LN) tolerance is essential for improving nitrogen use efficiency and agricultural sustainability. A set of 156 potato genotypes from diverse sources—including the International Potato Center (CIP), the National Potato Germplasm Repository (CAAS), and varieties and lines bred by the Qinghai Academy of Agriculture and Forestry Sciences—was evaluated under optimal (60 mmol·L⁻¹) and low (3 mmol·L⁻¹) nitrogen conditions using tissue culture. Nine traits related to growth, nitrogen accumulation, and nitrogen use efficiency were measured. Under LN stress, nitrogen physiological efficiency (NPE), uptake efficiency (NUpE), and utilization efficiency (NUE) increased, while most growth-related traits declined. Considerable variation was observed in fresh weight (FW), dry weight (DW), nitrogen accumulation (NA), and NUE, with coefficients of variation ranging from 0.38 to 0.40 under LN and 0.17 to 0.42 under ON. Principal component analysis identified NA and NUpE as the primary contributors to phenotypic variation. Based on comprehensive D-values from cluster analysis, the genotypes were classified into five tolerance groups: Type I—(strong low-nitrogen tolerant (13 accessions); Type II—low-nitrogen tolerant (66 accessions); Type III—moderate low-nitrogen tolerant (36 accessions); Type IV—low-nitrogen sensitive (24 accessions); and Type V—highly low-nitrogen sensitive (17 accessions). Physiological validation revealed two distinct adaptive strategies: a nitrogen conservation strategy (Type I), characterized by high NA and nitrogen content (NC) alongside moderate physiological efficiency, and an efficiency-driven compensation strategy (Types II, IV, and V), marked by low NA and NC but high physiological efficiency. The congruence between multivariate clustering and subsequent physiological measurements confirms that this classification effectively captures genotypic differences in low nitrogen tolerance. Thirteen highly LN-tolerant genotypes—including PIMPERNEL, Favorita, and Spunta—were identified as promising genetic resources for breeding nitrogen-efficient potato cultivars. This tissue culture-based screening method provides a practical tool for evaluating nitrogen tolerance in plants and supports sustainable potato production under limited nitrogen availability. Full article