Search Results (1,157)

The diagnosis of enteric fever has become difficult due to the nonspecific and overlapping clinical syndrome of typhoid and paratyphoid infections with other febrile illnesses. Moreover, the rapid emergence of fluoroquinolone-resistant typhoidal Salmonella and the lack of robust diagnostic methods highlight the urgent need for highly sensitive molecular techniques. Here, we evaluated the performance of a rapid, reliable, and cost-effective molecular diagnostic approach for detecting Salmonella Typhi, including the globally dominant haplotype H58 lineage (H58), and Salmonella Paratyphi A. An in-house-built conventional polymerase chain reaction (PCR) was performed on a collection of blood-culture-positive strains, and the sensitivity and specificity were compared with those of the standard blood culture results. H58 and non-H58 Typhi lineages with distinct resistance patterns were confirmed from the previously reported sequencing data. Our PCR result showed that target genes SSPA2308, STY2513, and STY0307 demonstrated 100% sensitivity and specificity for Salmonella Paratyphi A, Salmonella Typhi, and H58 Salmonella Typhi, respectively. The PCR assay reliably detected bacterial DNA at 5.2 × 10⁴ colony-forming units (CFUs), with consistent amplification observed up to 10⁻¹ dilution. This single-nucleotide polymorphism (SNP)-based diagnostic approach has added a new dimension to designing unique markers for multidrug-resistant (MDR)-associated H58 lineage detection and has the potential to inform local treatment algorithms. Full article

Background and Objectives: Psoriasis is a chronic immune-mediated inflammatory disease characterized by heterogeneous clinical presentation and variable response to biologic therapy. Genetic variation within the IL-23/Th17 inflammatory pathway may influence treatment outcomes. This study evaluated the association between IL12B rs3213094 and IL23R rs11209026 single-nucleotide polymorphisms (SNPs) and response to biologic therapy in patients with moderate-to-severe psoriasis. Materials and Methods: We conducted a multicenter observational study including 92 Romanian patients with moderate-to-severe psoriasis vulgaris receiving their first biologic therapy (anti-TNF, anti-IL-17, or anti-IL-23 monoclonal antibodies). Clinical response was assessed using the Psoriasis Area and Severity Index (PASI) at baseline and weeks 12, 24, 36, and 48. Early response was defined as achieving PASI75 at week 12. Patient-reported disease impact was assessed using the Dermatology Life Quality Index (DLQI) at the same time points. Genotyping of IL12B rs3213094 and IL23R rs11209026 was performed using TaqMan assays. Longitudinal PASI dynamics were analyzed using repeated-measures ANOVA, while multivariable logistic regression was used to identify independent predictors of PASI75 at week 12. Results: A significant reduction in PASI scores over time was observed (p < 0.001). The IL12B rs3213094 genotype was associated with differences in early response kinetics, with T-allele carriers showing significantly greater PASI improvement at week 12 compared with CC homozygotes (90.0% vs. 65.7%, p = 0.003). This effect was limited to early treatment and attenuated at later time points. In multivariable analysis, the IL12B rs3213094 CT + TT genotype was independently associated with PASI75 achievement at week 12 (OR = 4.285, 95% CI 1.500–12.239, p = 0.007). Treatment with anti-IL-17 agents was also an independent predictor of early response (OR = 3.946, 95% CI 1.416–10.998, p = 0.009). No significant association was observed between IL23R rs11209026 and treatment response. DLQI scores improved significantly over time (p < 0.001), without genotype-dependent differences. Conclusions: IL12B rs3213094 SNP is significantly associated with early biologic treatment response in psoriasis, supporting its potential role as a pharmacogenetic biomarker of treatment responsiveness. These findings may inform the integration of genetic markers into personalized therapeutic strategies, particularly in underrepresented populations such as those from Eastern Europe. Further studies in larger cohorts are warranted to validate these results. Full article

Background: Diabetic retinopathy (DR) and chronic kidney disease (CKD) are among the leading causes of disability in individuals with type 1 diabetes mellitus (T1DM). However, the genetic architecture of these complications remains poorly understood. Genome-wide studies demonstrate significant interpopulation heterogeneity, while candidate gene studies yield conflicting results due to limited power. Independent replication of previously obtained results in separate cohorts, with appropriate intergroup comparisons, is essential for identifying the most significant biomarkers of microvascular complications in T1DM. Purpose: To search for associations of the most significant polymorphic variants rs55703767, rs72831309, rs118124843, rs9344715, rs183937294, rs4293393, rs12917707, rs77924615, rs11864909, rs9622363, rs73885319, rs2523989, rs3825932, rs763361, rs12708716, rs2292239, and rs4948088 with the risk of developing T1DM and its complications—DR and CKD. Methods: The study involved 618 individuals, including 522 patients with T1DM undergoing inpatient treatment at the Endocrinology Research Centre, as well as 96 control individuals without T1DM. Among the T1DM patients, 232 had concurrent CKD and retinopathy, while 80 were free of both microvascular complications. A comparison of allele and genotype frequencies of 17 single-nucleotide polymorphisms (SNPs) was conducted between the T1DM group and the control group, as well as an intergroup comparison between individuals with and without complications. Results: The rs2292239 (ERBB3) locus is associated with an increased risk (p_bonf = 0.001, OR = 2.02), while rs55703767 (COL4A3) is associated with a decreased risk of developing T1DM in general (p = 0.01846, OR = 0.42). rs9344715 (AKIRIN2) is associated with the risk of diabetic nephropathy (p = 0.03996, OR = 1.29), while PDILT variants rs77924615 (OR = 0.57, p_bonf = 0.045) and rs11864909 (OR = 0.41, p_bonf = 0.0105) with DR. Conclusions: The study identified potential genetic markers for the risk of type 1 diabetes and its microvascular complications. The results require further verification in an independent, expanded cohort. Consideration of genetic factors confirmed the independent contribution of the identified variants, supporting their value as promising biomarkers for risk stratification and personalized prevention of T1DM complications. Full article

Body measurement traits are a direct production indicator reflecting growth status and guiding genetic selection. Identifying molecular markers associated with body measurement traits could accelerate animal breeding programs. The Yanqi horse, an important indigenous breed in Xinjiang, is primarily distributed in the Bayingolin Mongol Autonomous Prefecture. However, molecular markers linked to body measurement traits in Yanqi horses remain uncharacterized. In the present study, whole-genome resequencing was performed on 183 Yanqi horses, yielding 13,366,672 single-nucleotide polymorphisms (SNPs) after quality control. A genome-wide association study on withers height, body length, heart girth, and cannon bone circumference was conducted using a mixed linear model implemented in GEMMA, with population structure and relatedness controlled using principal components and a genomic kinship matrix. Bonferroni-adjusted thresholds (p < 1 × 10⁻⁷ for significant associations; p < 1 × 10⁻⁶ for suggestive associations) were applied to minimize false positives. A total of 185 single-nucleotide polymorphisms were significantly associated with body measurement traits and 359 candidate genes were annotated within 200 kb upstream and downstream of the significant loci. Among these, five genes, GABRB1, FIGN, GABRA4, ENSECAG00000051747, and COX7B2, may be implicated in the growth and development of Yanqi horses. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated that these genes are primarily involved in cytoskeletal structures within muscle cells, regulation of the actin cytoskeleton, and neuroactive ligand–receptor interaction pathways. In summary, this study presents novel markers and candidate gene sets associated with body measurement traits in Yanqi horses, offering valuable insights for functional gene investigations and presenting substantial potential for accelerating the breeding of Yanqi horses. Full article

Cell lineage relationship studies in developmental and regenerative biology have been greatly advanced using techniques such as fluorescent labeling driven by cell-type-specific promoters. Nevertheless, unbiased non-invasive tools for distinguishing cell lineages are inevitably desired. Mitochondrial DNA (mtDNA) exhibits wide-range single-nucleotide polymorphisms (SNPs) among individual cells. Here, we aim to distinguish cell types in organs/tissues of the same individual and in the regenerated liver based on the use of mtDNA SNPs. For this, two approaches—“Mitochondrial Alteration Enrichment and Sequencing” (MAESTER) and “mitochondrial single-cell assay for transposase-accessible chromatin with sequencing” (mtscATAC-seq)—were adopted to facilitate the detection of mtDNA SNPs in single cells. With MAESTER, we show that specific cell types in the liver and spleen of the same individual can be successfully defined using collective individual-specific markers composed of panels of unique mtDNA SNP combinations. For its application, we performed partial hepatectomy (PH) on a Krt19:Dre^ERT2/+;R26:Rox-ZsGreen-Stop-Rox-tdTomato/+ mouse harboring tdTomato-labeled cholangiocytes following tamoxifen injection and demonstrated that utilizing panels of unique mtDNA SNP combinations detected by mtscATAC-seq in the pre-PH cholangiocytes as markers can faithfully trace the cell fate in the post-PH liver samples. Hence, this approach may serve as an unbiased tool for investigating cell lineage relationships in relevant research areas such as liver regeneration. Full article

Recent advances in forensic genetics are rapidly transforming the field from traditional DNA profiling toward integrative and predictive genomic approaches. While short tandem repeat (STR)-based typing remains the gold standard for human identification, emerging technologies such as massively parallel sequencing (MPS), forensic genetic genealogy (FGG), and artificial intelligence (AI)-driven bioinformatics are expanding the scope of forensic investigations, with MPS also widely established in clinical genomics, further supporting its application in complex and unresolved cases. This article presents a structured narrative and conceptual review of next-generation forensic genomics, based on selected peer-reviewed studies, technical guidelines, and recent review articles relevant to MPS-based marker analysis, FGG, DNA phenotyping, ancestry inference, AI-supported bioinformatics, validation, and ethical/legal issues. We discuss the transition from STRs to single nucleotide polymorphisms (SNPs) and microhaplotypes enabled by MPS, emphasizing their applications in mixture deconvolution, kinship analysis, and degraded DNA samples. The role of FGG in cold case resolution is examined, alongside methodological, legal, and ethical considerations related to the use of public genetic databases. Furthermore, we explore recent developments in DNA phenotyping and ancestry inference, focusing on predictive models of externally visible characteristics (EVCs) and their forensic utility. Particular attention is given to the growing impact of AI and machine learning in data interpretation, probabilistic genotyping, and pattern recognition across complex genomic datasets. Finally, we address current limitations, including technical standardization, population biases, data privacy concerns, and the need for robust validation frameworks. Rather than providing a systematic review, this work aims to synthesize current developments into an operational framework for integrated forensic genomics, distinguishing forensic intelligence, probabilistic interpretation, confirmatory testing, and evidentiary use. By integrating technological, analytical, and ethical perspectives, this review proposes a conceptual framework for integrated forensic genomics, in which genomic data are used not only for identification but also for forensic intelligence generation. Full article

Accurate pedigree reconstruction is essential for genetic evaluation, inbreeding control, and family management in aquaculture breeding programs. In sturgeon, extremely high fecundity and communal rearing during early developmental stages often lead to the loss of family information, making reliable full-sib family assignment a critical challenge. In this study, we developed a machine learning-based framework for full-sib family assignment using simulated genotype datasets and whole-genome resequencing data from Russian sturgeon. Simulation analyses across five machine learning algorithms showed that training set size and marker density were the primary determinants of assignment accuracy. When at least 10 individuals per family were included in the training set, mean identification accuracy exceeded 99% across all evaluated scenarios, and exceeded 99.9% for all methods except XGBoost. In contrast, performance declined when the marker number was reduced to 200. At moderate marker densities (500–1000 markers), performance remained stable, with mean identification accuracy around 99% even when only 3–4 individuals per family were included in the training set. Validation using whole-genome resequencing data (sequencing depth ranging from 9.43× to 11.86×) from 582 individuals representing 19 full-sib families of Russian sturgeon confirmed the simulation findings, with several algorithms achieving assignment accuracies exceeding 99%. These results demonstrate that machine learning provides an accurate and robust approach for full-sib family assignment using genome-wide single nucleotide polymorphism (SNP) data. The proposed framework offers an effective solution for pedigree reconstruction and family identification in sturgeon breeding populations lacking reliable pedigree records. Full article

Maize is one of the most widely cultivated crops worldwide and is extensively used for animal feed and industrial applications. Plant height (PH) and ear height (EH) are critical determinants of lodging resistance and tolerance to high planting density, and coordinated regulation of these traits is essential for yield improvement. In this study, 479 maize inbred lines from Northeast and North China were genotyped using 7861 single-nucleotide polymorphism (SNP) markers to perform a genome-wide association study (GWAS). After controlling for population structure and relatedness, the mixed linear model (MLM) identified 20 loci significantly associated with PH on chromosomes 2, 4, 5, 6, 7, and 8, and 8 loci associated with EH on chromosomes 2, 3, 4, and 7. A total of 23 candidate genes were identified, including PLATZ8, pectin methylesterase 36, and leucine-rich repeat extensin 14. Gene Ontology (GO) enrichment analysis revealed significant enrichment in biological and molecular functions such as DNA binding, pectinesterase activity, zinc ion binding, ATP binding, and uniporter activity. Bioinformatic characterization of the two most likely candidate genes, Zm00001d002726 and Zm00001d015394, showed that both possess a typical compact four-exon structure. Functional prediction indicated that Zm00001d002726 encodes a pectinesterase/pectinase, potentially regulating cell elongation through pectin degradation and remodeling of the cell wall. Pectinesterase activity may influence PH and EH by mediating pectin demethylation within the cell wall. In contrast, Zm00001d015394 encodes a PLATZ family transcription factor that may regulate downstream gene expression through DNA-binding activity. These findings provide insight into the genetic architecture and potential molecular mechanisms underlying PH and EH in maize and offer a foundation for future breeding efforts. Full article

Background/Objectives: Fall armyworm (FAW) (Spodoptera frugiperda) is a major constraint to maize production in Sub-Saharan Africa, including Mozambique. This study aimed to evaluate maize genotypes for resistance to FAW under greenhouse and field conditions and to assess the association between phenotypic resistance and genomic variation based on single nucleotide polymorphisms (SNPs). Methods: A total of 20 maize genotypes from the Agricultural Research Institute of Mozambique (IIAM) and the International Maize and Wheat Improvement Center (CIMMYT) were evaluated. FAW damage was quantified using the area under the damage progress curve (AUDPC). Phenotypic data were analyzed using ANOVA and mixed models, while molecular analysis was conducted using 10,603 SNP markers located on chromosomes previously associated with FAW resistance. Results: Significant genotypic differences were observed under greenhouse conditions (F = 1.94, p = 0.012) and in the field (p = 0.021), although environmental factors reduced variation in the field. Genotypes such as CML67, CML338, and Kenya amarelo (Acc3550) exhibited consistently lower AUDPC values across environments, indicating stable resistance. However, SNP allele proportion was not significantly associated with phenotypic resistance (r = 0.34, p = 0.147), and regression and ANOVA analyses confirmed the absence of a significant relationship (p > 0.05). Conclusions: FAW resistance in maize is quantitatively inherited and not explained by general genomic variation across candidate regions. Phenotypic screening remains essential, and further studies are required to identify specific loci for effective marker-assisted selection. The identified stable genotypes represent valuable resources for breeding FAW-resistant maize adapted to Mozambique. Full article

A growing body of epidemiological and toxicological evidence indicates that exposure to toxic elements (TEs), including As, Cd, Cr(VI), Pb, and Hg, is associated with a wide range of adverse health outcomes, including cancer, neurological and cardiovascular diseases. Given their widespread presence and toxicity, understanding the factors underlying inter-individual differences in susceptibility is essential, as not all exposed individuals develop the same health effects. Genetic variability, particularly single-nucleotide polymorphisms (SNPs), is increasingly recognized as a key determinant of individual responses to TE exposure. Variants in genes involved in metal transport, detoxification, and DNA repair, including DMT1, GSTP1, MT2A, hOGG1, and XRCC1, may influence internal dose and biological effects and have been proposed as potential susceptibility markers. However, current evidence remains inconsistent due to small sample sizes, heterogeneous exposure assessments, and limited considerations of ethnic diversity and gene–environment interactions. Future research should prioritize large and well-characterized populations integrating detailed exposure and lifestyle data. This review focuses on genetic susceptibility and gene–environment interactions in TE exposure, with particular emphasis on SNPs as key modulators of individual risk. It summarizes major toxic metals, reviews epidemiological evidence of the associated health risks, and highlights the role of genetic background in modulating TE-induced toxicity. Full article

Bacterial stem and root rot (BSRR), caused by Dickeya dadantii, poses a severe threat to global sweetpotato production, yet the genetic architecture underlying resistance remains elusive. To dissect these mechanisms, we conducted a high-resolution genome-wide association study (GWAS) on 135 diverse accessions, integrating two-year field phenotyping with best linear unbiased prediction (BLUP) and 6.8 million single-nucleotide polymorphism (SNP) markers. This approach mapped nine quantitative trait loci (QTLs) exhibiting significant allelic dosage-dependent effects, with the major locus, qBSRR.6.1 was the primary discriminator between resistant and susceptible genotypes. Crucially, transcriptomic profiling within these loci revealed distinct expression patterns: IbTCP5 and IbERF003 (located in qBSRR.5.1 and qBSRR.6.2) were highly expressed in the susceptible cultivar ‘Xinxiang’ but suppressed in the resistant ‘Guangshu87’. Furthermore, BSRR challenge identified IbPUB4, IbKCS5, and IbLig1 as priority candidate genes involved in defense, with expression patterns suggesting roles in ubiquitin-mediated protein turnover, cuticular wax biosynthesis, and DNA repair, respectively. In stark contrast, IbPUB25 was constitutively upregulated in ‘Xinxiang’, potentially acting as a negative regulator of immunity via degradation of target proteins. These findings elucidate the polygenic, dosage-sensitive nature of BSRR resistance and prioritize specific targets for future functional characterization. Pyramiding favorable alleles of positive candidates while silencing potential negative regulators like IbPUB25 offers a promising avenue for developing durable, high-resistance sweetpotato varieties. Full article

Understanding the genetic architecture underlying growth variation is central to improving aquaculture species through genomic selection. Here, we performed a genome-wide association study (GWAS) on 303 individuals from a G₂ breeding population of channel catfish (Ictalurus punctatus) using whole-genome resequencing data. After stringent quality control, 5.64 million high-confidence single nucleotide polymorphisms (SNPs) were retained for association analyses of two key growth traits—monthly weight gain (MWG) and body depth (BH). We identified 15 and 28 loci significantly associated with MWG and BH, respectively, with the majority concentrated on chromosome 20. Two SNPs (Chr20:14,657,971 and Chr20:14,658,012) located in exon 9 of the rrp44 gene were significantly associated with both traits. Functional annotation and enrichment analyses revealed that the rrp44 gene, encoding an exoribonuclease subunit of the RNA exosome complex, participates in mitotic spindle regulation and post-transcriptional RNA decay, processes critical for cellular growth and metabolic homeostasis. We propose that rrp44 may influence growth through the modulation of feeding rhythm and circadian regulation, providing a potential molecular basis for growth heterogeneity in channel catfish. These findings enrich our understanding of growth-related genomic variation and offer valuable molecular markers for precision breeding and genetic improvement of catfish. Full article

Globally, 5.94 million accessions are conserved across 867 genebanks, of which 41.5% (2.47 million) are cereal crop accessions. Only a small portion of global germplasm diversity has been marker-genotyped or genome-sequenced. Accurate identification of genebank accessions is essential to improve the efficiency and effectiveness of global genebanking. It is crucial for preserving the legacy knowledge associated with the germplasm and for maintaining its value to current plant science and breeding efforts. Existing practices generally fall into two categories: either expensive and complex, or inefficient, labour-intensive, and inaccurate. The first relies on high-resolution genomic sequences or saturated markers, while the second relies on morphological comparisons of regenerated plants with historical records. We propose a genotyping method based on a minimal set of Single Nucleotide Polymorphism (SNP) markers and exemplify its use on a genebank scale. We identified a small, effective set of SNPs that can differentiate between the global diversity of genebank accessions of barley (Hordeum vulgare and Hordeum spontaneum) and tetraploid wheat collections (Triticum turgidum) maintained at the Germplasm Resources National Capability at the John Innes Centre, UK. This approach offers a straightforward, automatable, and inexpensive alternative to traditional genebank crop descriptors used during seed regeneration and distribution. By establishing the minimal genomic resolution needed to distinguish genetically distinct accessions, we show that as few as 24 and 25 carefully chosen SNP markers for barley and durum wheat, respectively, can effectively differentiate individual accessions. Unlike morphology-based identification, which can detect mislabelling or contamination but often cannot prevent or correct such errors, our SNP-based molecular labelling enables error correction and the retrieval of lost germplasm identity. This study highlights how accuracy and reliability in germplasm management can be improved without costly whole-genome sequencing or resource-intensive analysis. We discuss the impact of this method on enhancing quality assurance in genebanks and its broader usefulness for the user community. Full article

Southwest China harbors the world’s richest germplasm resources of Tartary buckwheat (Fagopyrum tataricum). However, their effective utilization is severely constrained by poor management and narrow genetic diversity. Developing a core collection is a key strategy for overcoming these bottlenecks and facilitates the efficient conservation and utilization of germplasm resources. Therefore, we aimed to assess the genetic diversity and population structure of a Tartary buckwheat germplasm collection from Yunnan Province and adjacent regions to establish a core collection. Whole-genome resequencing and phenotyping of four key agronomic traits were performed on 313 Tartary buckwheat accessions. Population genetic structure, differentiation, and diversity parameters were analyzed using single-nucleotide polymorphism (SNP) data. We obtained 3,433,676 high-quality SNP markers. The 313 accessions were classified into four ancestral populations and three phylogenetic groups, which revealed the complex patterns of genetic differentiation and gene flow. Phenotypic traits exhibited high genetic diversity, with wide variation ranges in key agronomic traits such as plant height, stem diameter, and branching characteristics, highlighting the richness of the germplasm resources. By integrating the phenotypic and SNP data, we constructed a core collection (Core-Merge) comprising 105 accessions (33.55% of the original collection). Core-Merge showed no significant differences in phenotypic traits compared to the original collection, exhibited a similar distribution in principal coordinate analysis, and demonstrated low kinship among individuals. The collection established in this study, Core-Merge, captures the maximum phenotypic and genotypic variability present in the original germplasm. The core germplasm collection provides a valuable foundation for the efficient conservation of, genetic research on, and molecular breeding of Tartary buckwheat. Full article

Reliable identification of seafood species is critical for fisheries management and product authentication, especially when morphological characteristics are lost during processing. In this study, a multiplex PCR system was developed to distinguish seven cuttlefish species (six Sepia spp. and Sepiella inermis) commercially distributed in the Korean seafood market. Species identity was first confirmed by amplifying a mitochondrial cytochrome c oxidase subunit I (COI) fragment (~658 bp) using universal primers (LCO1490/HCO2198), showing 99–100% sequence similarity to corresponding GenBank reference sequences. Analysis of genetic variation based on a 530 bp aligned region demonstrated complete interspecific differentiation without shared haplotypes among species. The number of haplotypes per species ranged from 5 to 21, with haplotype diversity values between 0.667 and 1.000. An extended COI fragment (~1200 bp) was further analyzed to identify diagnostic interspecific variation for marker development. Seven diagnostic single-nucleotide polymorphism (SNP) sites were identified and used to design species-specific forward primers with diagnostic nucleotides positioned at the 3′ termini. Distinct amplicons (220–1099 bp) were generated and clearly resolved by agarose gel electrophoresis. Because simultaneous amplification of all seven primer pairs reduced amplification efficiency, the assay was divided into two multiplex sets. Under optimized conditions (56 °C), each species produced a single expected band without cross-amplification. This multiplex PCR system provides a rapid and sequencing-free approach for reliable species discrimination and can be effectively applied to fisheries monitoring and seafood authentication in commercial supply chains. Full article