Identification of the Novel HLA-B*57:212 Allele by Next-Generation Sequencing.
HLA-B*57:212 differs from HLA-B*57:01:01:01 by a single nucleotide substitution in exon 5.
Humans↗
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Characterisation of the Novel HLA-A*23:163 Allele by Next-Generation Sequencing.
HLA-A*23:163 differs from HLA-A*23:01:01:03 by a single nucleotide substitution at position 925 of the cDNA.
Humans↗
The Novel HLA-DQB1*06:03:60 Allele Identified by Next-Generation Sequencing and Confirmed by Nanopore Sequencing.
HLA-DQB1*06:03:60 differs from HLA-DQB1*06:03:01:01 by a single synonymous nucleotide substitution at position 174 in Exon 2.
Humans↗
Discovery of the Novel HLA-DQB1*05:386 Allele in a Brazilian Volunteer Donor.
HLA-DQB1*05:386 differs from HLA-DQB1*05:01:01:01 by a non-synonymous substitution in exon 4.
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Identification of the Novel HLA-DQB1*02:02:41 Allele by Next-Generation Sequencing.
HLA-DQB1*02:02:41 differs from HLA-DQB1*02:02:01:01 by one synonymous nucleotide substitution at Codon 39 in Exon 2.
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Identification of the Novel HLA-A*02:04:03 Allele by Long-Read Sequencing Following a Short-Read Phasing Failure.
The novel allele HLA-A*02:04:03 was detected with long-read sequencing but failed to be detected by short-read sequencing.
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Characterisation of the Novel HLA-A*02:1205 and HLA-A*02:07:27 Alleles by Next-Generation Sequencing.
Compared with HLA-A*02:07:01:01, the alleles HLA-A*02:1205 and HLA-A*02:07:27 each show one nucleotide substitution, respectively.
Humans↗
The Novel HLA-A*02:1229 Allele Was Identified by Next-Generation Sequencing.
HLA-A*02:1229 differs from HLA-A*02:07:01:01 by a single nucleotide substitution at position 1014 T>A.
Humans↗
Characterisation of the Novel HLA-A*03:541 Allele by Next-Generation Sequencing.
HLA-A*03:541 differs from HLA-A*03:01:01:01 by a single nucleotide substitution at position 728 of the cDNA in exon 4.
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Comparative evaluation of probe-capture and conventional metagenomic sequencing across multiple clinical sample types, with analysis of paired bronchoalveolar lavage fluid and blood samples.
Conventional metagenomic next-generation sequencing (mNGS) suffers from host nucleic acid interference and poor performance in low-biomass samples. Probe-capture metagenomic sequencing (PC-mNGS), which enriches microbial targets via hybridization probes, shows superior sensitivity but lacks systematic multi-sample evaluations. This study compared PC-mNGS and mNGS across diverse clinical specimens (bronchoalveolar lavage fluid [BALF], blood, cerebrospinal fluid [CSF]) and assessed the clinical utility of pathogen co-detection in paired BALF-blood samples from sepsis patients. A total of 282 samples (81 BALF, 141 blood, 25 CSF, 35 others) sequenced by both PC-mNGS and mNGS were analyzed. Additionally, 621 paired BALF-blood samples from sepsis patients with pulmonary infections were evaluated. PC-mNGS achieved higher pathogen detection rates (66.67% vs 57.10%, P = 0.000198) than mNGS, particularly in blood (66.67% vs 47.52%, P = 2.5 × 10⁻⁵). PC-mNGS detected more bacteria (19 species exclusive) and fungi (11 species exclusive) than mNGS. Viruses showed comparable detection. BALF and CSF exhibited high overall agreement (OPA: 96.30% and 88%, respectively), while blood had lower concordance (NPA: 54.05%, OPA: 70.92%). A total of 60.55% of BALF-positive samples (PC-mNGS) had co-detected pathogens in blood. Gram-negative bacteria (e.g., Klebsiella pneumoniae) and fungi (e.g., Candida albicans) showed higher blood co-detection rates than viruses. In this study, PC-mNGS detected more pathogens and showed a higher positivity rate than mNGS in blood samples. BALF sequencing data, particularly bacterial reads per million (RPM), may predict bloodstream co-detection, aiding in sepsis management. However, clinical validation and integration with traditional diagnostics are needed to confirm utility. This study highlights PC-mNGS as a promising tool for complex infections but underscores the need for rigorous multi-context validation.IMPORTANCEAccurate and rapid identification of pathogens is critical for effective treatment of severe infectious diseases, such as sepsis. This study demonstrates that probe-capture metagenomic sequencing (PC-mNGS) detected more pathogens in blood samples compared to conventional metagenomic sequencing, especially for bacterial and fungal infections. By analyzing paired lung and blood samples, we show that high pathogen levels in lung fluid may predict bloodstream infection, offering a potential early warning for clinicians. These findings support the use of PC-mNGS as a more sensitive diagnostic tool, which could lead to faster, more targeted therapies and better outcomes for patients with complex infections.
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The diagnostic potential of combined quantitative polymerase chain reaction and next-generation sequencing using the same primers for periprosthetic joint infection.
Next-generation sequencing (NGS) enables the detection of specific pathogens unidentifiable by conventional cultures, but its application in orthopedics remains inconsistent due to background contamination and irreproducible findings. This study evaluated the diagnostic performance of a novel workflow combining broad-range 16S rRNA gene quantitative PCR (qPCR) screening with downstream NGS, focusing on bacterial biomass thresholds. The qPCR assay demonstrated excellent intrarater reliability, with an intraclass correlation coefficient (ICC) of 0.961 (95% confidence interval, 0.881 to 0.997). Based on serially diluted positive controls, a quantitative threshold of 10⁵ CFU/mL was established as the minimum concentration required for the consistent detection of fastidious taxa, such as Escherichia coli. When evaluated against conventional cultures using 95 sonicate fluid and 276 pre/intraoperative tissue samples, the qPCR assay achieved a sensitivity of 80% and a specificity of 72%. Subsequent NGS sequencing of 26 clinical samples and 9 controls showed concordance in 4 of 6 culture-positive infected cases with NGS taxonomy, whereas the remaining discrepancies were likely attributable to culture-based phenotypic misidentification. Notably, among the qPCR-positive cases, three were culture-negative, including two hip prosthesis loosening cases exhibiting polymicrobial profiles, and one post-traumatic osteoarthritis case harboring low-level Staphylococcus. Crucially, this post-traumatic patient developed delayed periprosthetic joint infection (PJI) 2 years post-surgery, with cultures identifying Staphylococcus previously detected by the initial NGS analysis. Integrating qPCR screening with targeted NGS effectively refines pathogen identification, filters environmental artifacts, and overcomes the diagnostic limitations of culture-negative infections in orthopedic practice.IMPORTANCENext-generation sequencing (NGS) enables the detection of specific pathogens in clinical samples that are not identifiable by conventional methods. However, NGS applications in orthopedics have not been quantitatively evaluated, and findings have been inconsistent owing to contaminants and the presence of non-credible causative organisms. These factors primarily stem from the failure to evaluate low-biomass samples and the absence of proper controls, such as negative controls or mock community DNA samples. This study demonstrates that interpreting results from low-biomass samples requires careful consideration because NGS relies on relative bacterial abundances; distinguishing likely pathogens from contaminants is particularly challenging when bacterial loads are low. We demonstrated that combining NGS with quantitative PCR (qPCR) and applying a Cq cutoff can reduce false positives.
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Genomic Profiling of Epidermal Growth Factor Receptor Mutation-Positive Non-Small Cell Lung Cancer after Progression on First-line Osimertinib: Phase II ORCHARD Study.
PURPOSE: Osimertinib is the standard of care for first-line treatment for epidermal growth factor receptor-mutated (EGFRm) non-small cell lung cancer (NSCLC). Understanding the tumor molecular profile of patients following progression on osimertinib could help inform optimal second-line treatment. PATIENTS AND METHODS: ORCHARD (NCT03944772), a phase II biomarker-directed study, enrolled patients with EGFRm NSCLC who progressed on first-line osimertinib to receive treatment based on their tumor molecular profile after progression. The study comprised three groups into which patients were allocated based on the molecular profile of their tumor, determined via next-generation sequencing (NGS) of a tumor biopsy. We report results from a prespecified, exploratory analysis of baseline tumor tissue and plasma samples to evaluate mechanisms of resistance to first-line osimertinib identified by tissue and plasma NGS. Agreement between tissue and plasma NGS data was also assessed. RESULTS: This study provided a comprehensive dataset exploring tissue (n = 400) and plasma (n = 191) genomics, enabling characterization of the histogenomic landscape after first-line osimertinib treatment. TP53 and MDM2/4 alterations were mutually exclusive and occurred in 86% of tumors. When combining tissue and plasma genomics, resistance alterations were detected in 87% of samples, with multiple resistance alterations in 46%. Alterations in the PI3K pathway, SOX2, and MYC were frequently detected in histologically transformed tumors. Additionally, differential patterns of co-occurring EGFR mutations in tumors with L858R versus exon 19 deletion were observed. CONCLUSIONS: This comprehensive analysis highlights potential heterogeneous resistance to first-line osimertinib treatment, providing a rationale for combining treatments with broad activity to improve patient outcomes. See related commentary by Gupta et al., p. 3718.
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Characteristics of p53 and Smad4 immunohistochemistry in pancreatic ductal adenocarcinoma and validation by next-generation sequencing.
BACKGROUND: Mutations in four major driver genes -KRAS, CDKN2A, TP53, and SMAD4- are central to the pathogenesis of pancreatic ductal adenocarcinoma (PDAC) and critically inform diagnosis, therapeutic decision-making, and prognostic assessment. Although next-generation sequencing (NGS) is widely regarded as the gold standard for detecting these mutations, its clinical application is often limited by suboptimal analytical efficiency and substantial economic cost. Among these genes, immunohistochemical (IHC) staining for the proteins encoded by TP53 and SMAD4 has been extensively adopted in routine pathology practice. However, standardized IHC pattern classification schemes and rigorous validation of their predictive accuracy for underlying genomic alterations remain lacking in PDAC. METHODS: We retrospectively enrolled 63 PDAC patients and systematically characterized the typical IHC expression patterns of p53 and Smad4. Targeted NGS was subsequently performed on all available tumor specimens, and the resulting mutational profiles were correlated with corresponding IHC findings. Diagnostic performance including sensitivity, specificity and accuracy of p53 IHC for predicting TP53 mutations and of Smad4 IHC for predicting SMAD4 mutations was rigorously evaluated. RESULTS: Among the four canonical driver genes, co-occurring double- or triple-gene mutations were prevalent; within TP53 and SMAD4, missense mutations constituted the most frequent variant type. Using NGS as the reference standard, we validated the diagnostic utility of a three-tiered p53 IHC classification system, particularly in fine-needle biopsy (FNB) specimens. Furthermore, we proposed a novel, refined Smad4 IHC pattern classification that incorporates an "intermediate" category, thereby expanding upon conventional binary interpretation. This new scheme achieved markedly improved mutation prediction accuracy (0.76) compared with traditional approaches (0.57). CONCLUSION: Our study highlights the complementary diagnostic value of p53 and Smad4 IHC relative to molecular testing in PDAC, especially when tissue is limited, as commonly encountered in FNB specimens. The newly established Smad4 IHC classification system, which integrates an intermediate expression category into the conventional two-tier framework, demonstrates superior clinical utility and enhances predictive accuracy for SMAD4 genomic alterations.
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Tumor Mutational Landscape and Its Correlation With Histopathological Characteristics in Breast Cancer.
BACKGROUND/AIM: In breast cancer, knowledge of the associations between clinicopathologic characteristics, genetic changes, and subtype-specific patterns is expanding. This study investigated how pathological and clinical variables affect the actionability of Next Generation Sequencing (NGS)-based tumor molecular data. MATERIALS AND METHODS: 227 breast cancer patients referred to Genekor's laboratory for tumor molecular profile analysis were included in the study. Pathology records were used to assess critical clinicopathological features, including HER2, ER, PR, Ki67, grade, metastatic site, and age. A 1021-gene NGS-based multigene panel was utilized to assess tumor biology alongside tumor mutational burden (TMB) and microsatellite instability (MSI). RESULTS: Comprehensive genomic profiling revealed that 95.6% of the patients harbored at least one oncogenic or likely oncogenic alteration, highlighting the high diagnostic yield of NGS-based testing. Distinct subtype-specific patterns were observed: HR+/HER2- tumors were enriched for PIK3CA and ESR1 gene alterations, whereas triple-negative breast cancer (TNBC) was dominated by TP53 alterations. Clinically actionable alterations were most common in HR+/HER2- tumors (~60% on-label), whereas TNBC more often harbored off-label or trial-associated targets. The inclusion of tumor-agnostic biomarkers (TMB/MSI) increased on-label actionability up to 64.5% in HR+/HER2- tumors, primarily driven by TMB-high cases. Median TMB values were low, and age was the only independent predictor. Furthermore, the presence of actionable alterations was significantly higher in metastatic tumors, and TP53 alterations were associated with aggressive tumor characteristics. CONCLUSION: Comprehensive NGS-based genomic profiling identifies clinically actionable alterations in over half of breast cancer patients, with substantial variability across molecular subtypes. The HR+/HER2- subtype demonstrates the highest prevalence of on-label actionable biomarkers. These findings support the routine implementation of comprehensive genomic profiling, especially in metastatic HER2-negative breast cancer, to guide precision oncology strategies and enable enrollment in biomarker-driven clinical trials.
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Genomic characterization of avian metapneumovirus subtypes A and B in United States poultry by targeted amplicon sequencing.
Avian metapneumovirus (aMPV) subtypes A and B emerged in United States poultry in late 2023 and early 2024, prompting genome-scale surveillance from clinical samples. Here, we developed and optimized targeted amplicon sequencing (TAS) assays for both subtypes and applied them to 104 subtype-positive clinical samples collected from chicken and turkey farms across nine US states between early 2024 and early 2026. TAS recovered 91 genomes suitable for comparative analysis, including 44 aMPV-A and 47 aMPV-B sequences, with successful recovery extending to Ct values of 34.6 for aMPV-A and 31.2 for aMPV-B. Recovered genomes showed near-complete breadth and high mapping efficiency. Phylogenetic analyses of both G-gene and whole-genome datasets showed that US aMPV-A field strains formed a distinct monophyletic lineage within group IV and resolved into three closely related clusters. Cluster 2, first recognized in North Carolina and later detected in Ohio, spread across 30 turkey and chicken farms. Cluster 2 genomes were defined by a concentrated G-protein hotspot within residues 209-275, and most North Carolina Cluster 2 genomes carried 10-11 nonsynonymous substitutions in this region, including multiple proline substitutions suggestive of local structural change. Missouri Cluster 3 remained cohesive but distinct from both Cluster 1 and Cluster 2 in the G-gene and whole-genome trees. In contrast, US aMPV-B field strains remained highly homogeneous across hosts and states, with more than 99% nucleotide identity by both G-gene and WGS analyses. We also identified 12 vaccine-derived genomes on both vaccinated and nonvaccinated farms. These included six genomes related to aMPV-A vaccine and six related to aMPV-B vaccines (VCO3/50 and 1062), all of which retained vaccine-defining markers together with additional substitutions consistent with continued circulation after vaccine use in the field. Selection analyses showed that the G gene had the highest gene-wise dN/dS ratio in both subtypes. Additional elevated signal was observed in SH and M2, and candidate positively or episodically selected codons were concentrated in the subtype A Cluster 2 G-gene hotspot. These findings show that TAS supports direct-from-sample aMPV genomic surveillance and provides genomic context for field clusters, vaccine-derived lineages, and continued adaptive change in aMPV in US poultry.
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Integrating metagenomic next-generation sequencing into a multimodal diagnostic framework for spinal infection: enhancing etiological identification and clinical prediction.
BACKGROUND: Spinal infection (SI) remains diagnostically challenging because of heterogeneous etiologies, nonspecific clinical manifestations, and the limited sensitivity of conventional microbiological approaches, particularly following empirical antimicrobial exposure. Although metagenomic next-generation sequencing (mNGS) enables unbiased pathogen detection, its incremental clinical value beyond pathogen identification and its role within integrated diagnostic strategies remain incompletely established. METHODS: We retrospectively analyzed 208 consecutive patients with suspected SI between August 2022 and August 2025. Final diagnoses were established using a multidisciplinary-adjudicated composite reference standard incorporating clinical, radiological, microbiological, and histopathological evidence. The diagnostic performance of mNGS was compared with conventional culture and histopathology. Furthermore, multimodal predictive models integrating clinical variables and microbiological information were developed using L1-regularized logistic regression. RESULTS: In the comparative cohort, mNGS achieved a significantly higher diagnostic yield than culture (66.5% vs. 27.41%, P < 0.001). Among confirmed SI cases, mNGS demonstrated higher sensitivity than conventional culture (91.67% vs. 40.15%, P < 0.001). mNGS identified a substantially broader pathogen spectrum, ranging from fastidious organisms such as Mycobacterium tuberculosis and Brucella to rare pathogens including Talaromyces marneffei and Coxiella burnetii, and maintained robust sensitivity (98.2%) despite prior antibiotic exposure. While an integrated clinical model achieved an AUC of 0.916, mNGS as a standalone modality provided superior discriminative power (AUC = 0.889) compared to histopathology (AUC = 0.836), the Conventional Biomarker Model (AUC = 0.742), and culture (AUC = 0.693). CONCLUSIONS: mNGS is a high-yield diagnostic tool for spinal infection, particularly in culture-negative and antibiotic-pretreated scenarios. Integrating mNGS into a multimodal clinical framework facilitates etiological clarity and precision antimicrobial therapy.
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Development of a 10K breeder-friendly SNP chip for faba bean.
INTRODUCTION: Faba bean breeding and genomics have seen steady progress in recent years, supported by genome sequences and high-density genotyping platforms. These tools have been valuable for trait mapping, diversity assessment, and genomic research, but they have limited routine use in breeding programs due to their relatively high cost. Recent progress in establishing an optimized, cost-efficient genotyping-by-sequencing protocol tailored to the large and complex faba bean genome has created the foundation for a more accessible genotyping solution. METHODS: Using this approach, we explored the genetic diversity of faba bean germplasm from various panels, providing a comprehensive representation of the crop's genetic landscape. From this dataset, we identified and selected a high-quality set of informative SNP markers that are evenly distributed across the genome. Building on these resources, we designed a breeder-friendly 10K SNP chip. RESULTS: The 10K SNP chip delivers high accuracy, broad genomic coverage, and affordability. The chip was validated across diverse germplasm panels, demonstrating strong clustering performance, high reproducibility, and applicability to breeding-relevant germplasm. DISCUSSION: This platform offers a cost-effective alternative to higher-density arrays, enabling its integration into genomic selection, marker-assisted breeding, and diversity monitoring, ultimately supporting accelerated genetic gain and the delivery of improved varieties to farmers.
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Protocol for Duplex Sequencing of Mitochondrial DNA in Single Human Oocytes.
Oocytes are densely packed with mitochondria, the energy-producing organelles that contain their own genome, mitochondrial DNA (mtDNA). Each cell contains multiple copies of mtDNA, with copy number varying among tissue types. Oocytes possess the highest mtDNA copy number, containing hundreds of thousands of mtDNA molecules per cell. Because mitochondria are inherited exclusively through the maternal lineage, accurate detection of mtDNA variants is essential for studies of inheritance, aging, and disease. The presence of multiple mtDNA copies allows wild-type and mutant molecules to coexist within the same cell, a condition known as heteroplasmy, in which low-frequency and de novo variants may occur at frequencies below 1%. Conventional next-generation sequencing (NGS) lacks sufficient accuracy to reliably distinguish these rare variants from errors introduced during library preparation and sequencing. Here, we present a protocol for enriching mtDNA from single human oocytes using Exonuclease V to remove linear DNA, followed by duplex sequencing library preparation for highly accurate mtDNA analysis. This workflow enables error-corrected sequencing of individual oocytes, facilitating reliable detection of low-frequency mtDNA variants and analysis of heteroplasmy and de novo mutagenesis. The protocol provides a reproducible approach for investigating mitochondrial genome variation in single oocytes using Illumina-compatible sequencing platforms.
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