Search Results (241)

Background/Objectives: To identify US military unknowns, the Armed Forces Medical Examiner System’s Armed Forces DNA Identification Laboratory has historically relied upon mitochondrial DNA and Y-chromosomal short tandem repeat testing. Where no appropriate family reference sample (FRS) is available or skeletal samples are degraded, autosomal single nucleotide polymorphism (SNP) testing with next-generation sequencing could assist. Methods: A method utilizing hybridization capture enrichment of a 95,000 (95K) SNP panel, amenable to FRS and extremely challenging samples, was validated. The Parabon Fx Forensic Analysis Platform was used for analysis and extended kinship inference. Skeletal samples (n = 65) and associated FRS (n = 64) were selected for a performance evaluation and case-type sample study. Results: Considering FRS with ≥7 ng DNA input into library preparation, 94% yielded ≥66,320 SNPs at ≥5X coverage. SNP recovery for skeletal samples at ≥1X coverage ranged from 5 to 94,197 SNPs, averaging 40,770 SNPs. When skeletal samples resulted in ≥13,000 SNPs, the most likely relationship category was consistent with the expected relationship. A log10 likelihood ratio of ≥4 and a posterior probability of ≥99.99% were established as thresholds for strong statistical support, and 87% of inferences met these thresholds while 13% were considered inconclusive. Pairwise kinship inference between unrelated individuals yielded an unrelated result in 85% of comparisons, 66% with strong statistical support. There were 170 instances of false positive 4th degree relationship inferences with strong statistical support. All false positives involved skeletal samples from individuals of admixed ancestry. Conclusions: With this approach, autosomal SNP testing can result in reliable kinship inferences between related individuals out to 3rd, and in some cases 4th, degree relationships, increasing the scope of eligible FRS to aid in identifications. Full article

Autosomal short tandem repeat (STR) markers remain the cornerstone of modern forensic genetics, providing exceptional power for individualization, kinship verification, and reconstruction of complex investigative cases. Over the last decade, the field has undergone a major technological transition from length-based capillary electrophoresis (CE) toward sequence-level characterization using massively parallel sequencing (MPS), enabling detection of internal sequence variants (isoalleles) and flanking-region polymorphisms that substantially increase discriminatory power in many forensic contexts. Although MPS is increasingly adopted in forensic laboratories, implementation remains dependent on infrastructure, cost considerations, validation requirements, and jurisdiction-specific legal frameworks. This review synthesizes the molecular mechanisms underlying STR variability, including replication slippage and mutation processes, and critically evaluates the transition to sequencing-based analysis. Particular attention is given to analytical challenges such as stochastic effects in ultra-low-template DNA and PCR inhibition in degraded samples. Special emphasis is placed on identification of skeletal remains from mass graves and historical contexts, where hierarchical analytical strategies—from mini-STR approaches to MPS-based workflows—enable recovery of highly fragmented DNA. The review also examines the evolution of probabilistic genotyping (PG), highlighting the importance of algorithmic transparency and reproducible analytical frameworks for judicial applications. By integrating technological advances with practical forensic challenges, this review outlines a comprehensive framework for implementing high-resolution STR analysis in contemporary genomic casework. As a narrative synthesis, the conclusions reflect currently available published evidence and acknowledge variability in validation status, implementation practices, and regional forensic infrastructures. Full article

Forensic DNA profiling commonly relies on polymerase chain reaction (PCR) amplification followed by capillary electrophoresis (CE) or massively parallel sequencing (MPS), which requires expensive, laboratory-based equipment that depends on a stable power supply and is unsuitable for field applications. Here, we present a proof-of-concept assay that uses recombinase polymerase amplification (RPA) combined with exo probe detection for rapid, isothermal genotyping of insertion–deletion (InDel) markers. To the best of our knowledge, this study represents the first demonstration of forensic DNA typing using RPA coupled with exo probes. The reaction proceeds at 39 °C and combines amplification and detection in a single 20 min step. Thirteen DNA samples were genotyped in triplicate across eight InDel loci using allele-specific fluorescent probes. Genotypes were derived from differential endpoint fluorescence between matched and mismatched probes. Compared with benchmark genotyping, 97.07% of genotypes (n = 307) were correct at 1 ng DNA input. Accurate profiles were reliably obtained for DNA inputs as low as 250 pg, and partial profiles were still detectable at 31 pg. The results demonstrate that RPA-based InDel genotyping is fast, sensitive, and reproducible. With further optimization, such as refined probe design and selection of robust loci, the assay has clear potential to achieve complete accuracy and to be integrated into portable lab-on-a-chip platforms for rapid, field-deployable forensic identification. Full article

Introduction: Epilepsy syndromes show marked clinical and genetic heterogeneity, with numerous functionally diverse genes involved in their etiology. Next-generation sequencing (NGS) has facilitated the identification of many monogenic epilepsy syndromes and enables earlier, more accurate diagnosis in pediatric patients. Materials and Methods: This study analyzes the molecular profiles of 87 pediatric patients with various forms of epilepsy in whom pathogenic or likely pathogenic variants were identified. Next-generation sequencing (NGS) using multi-gene epilepsy panels or whole-exome sequencing (WES) was performed. Results: A total of 88 pathogenic or likely pathogenic variants were detected in 48 epilepsy-related genes; 30 variants occurred de novo. SCN1A and KCNQ2 were the most frequent contributors (12.6% and 9.2%, respectively). The highest percentage of positive diagnoses (48%) was observed in patients with developmental and epileptic encephalopathy (DEE), with variants identified in genes including ALG13, ATP1A2, CACNA1A, CDKL5, CHD2, GABRG2, ITPA, KCNQ2, PCDH19, SCN1A, SCN2A, SCN3A, SCN8A, SMC1A, SPTAN1, STXBP1, and UBA5. Pathogenic variants in ANKRD11 were found in four patients with KBG syndrome, while other genes appeared sporadically. Conclusions: Targeted massively parallel sequencing is an effective diagnostic tool for pediatric epilepsy. The presence of numerous single-case findings highlights the high genetic heterogeneity of epilepsy. This approach enabled more precise diagnoses that would not have been achieved through clinical evaluation alone, underscoring the importance of genetic testing for prognosis and treatment planning in pediatric patients with unexplained epilepsy. Full article

Background/Objectives: The sequencing of mitochondrial DNA is a valuable tool in forensic genetics, particularly in cases involving degraded samples or those with low nuclear DNA content. In this study, we performed an internal validation for an NGS-based typing of the mitochondrial DNA control region using the Precision ID mtDNA Control Region Panel on the Ion S5^TM sequencer (Thermo Fisher Scientific, Waltham, MA, USA). This validation enhances the scientific robustness, reliability, and judicial admissibility of the results in forensic cases. Methods: Six parameters were evaluated: minimum read depth, sensitivity, repeatability, concordance with Sanger, reproducibility and heteroplasmy detection employing ten negative controls, nine reference samples, a bone sample, and six experimental mixtures. Libraries were prepared using the Ion Chef^TM system, quantified on the Quantstudio^TM 5 Real-Time PCR, sequenced on the Ion GeneStudio^TM S5, and analyzed with Converge^TM software. Results: In this study, we found that a read depth threshold of 100 reads per position, an optimal concentration of 20 pg/µL, and a detection threshold of heteroplasmies of 20% are appropriate to obtain reliable genetic profiles. This supports the application of this method in forensic casework, in which initial concentrations may be around the optimal concentration exposed here due to the provenience of the samples. Conclusions: The results indicate that the NGS platform is suitable for forensic mtDNA analysis, even under low-template conditions, and offers higher sensitivity compared to Sanger sequencing. However, some limitations were observed in the coverage of specific amplicons, the detections of polymorphisms in homopolymeric regions, and in the detection of low-level heteroplasmies. Full article

The Antas North mine, located in the southeastern Amazonian Craton within the Carajás Mineral Province, is hosted by mafic and felsic metavolcanic rocks that have undergone extensive hydrothermal alteration. Field and petrographic data reveal a hydrothermal sequence comprising sodic (albite), potassic (biotite + scapolite), calcic (amphibole + apatite), silicification (quartz), and propylitic (chlorite + epidote + calcite) assemblages. Copper–gold mineralization, spatially associated with calcic alteration, occurs as massive sulfide lenses, breccia zones, and vein networks dominated by chalcopyrite, pyrrhotite, and pyrite. The absence of magnetite/hematite and the dominance of sulfides and ilmenite classify Antas North as an Iron Sulfide–Copper–Gold (ISCG) system, representing a reduced endmember within the broader IOCG spectrum. New U–Pb titanite geochronology yields two concordant age populations at ca. 2476.6 ± 15.9 Ma Ga and 2162.9 ± 28.1 Ma Ga, recording a late Archean mineralizing stage and subsequent Paleoproterozoic reactivation during the Transamazonian orogeny. These ages parallel the multistage evolution recognized in other Carajás IOCG deposits, where copper–gold-related mineralization was repeatedly overprinted by later tectono-hydrothermal events. The reduced character of Antas North, marked by ilmenite and sulfide dominance with scarce magnetite, demonstrates that reduced IOCG styles were already established in the Neoarchean–Paleoproterozoic transition and underscores the diversity of mineralizing processes within the Carajás IOCG–IOA spectrum. Full article

This article introduces a diffractive neural network-enabled spectral object detection approach (DNN-SOD) to efficiently process massive sky-based multidimensional light field data. DNN-SOD combines the novel exploitation of target spectral features with the intrinsic parallelism of optical computing to process multidimensional information efficiently. DNN-SOD detects targets by segmenting the spectral data cube and processing it with the DNN. The DNN maps spectral intensity to the designated area of the detector, then reconstructs spectral curves, and differentiates targets by comparing them with reference spectral signatures. Classification results from individual sub-spectral data cubes are compiled in sequence, enabling accurate target detection. Simulation results indicate that the architecture achieved an accuracy of 91.56% on the MNIST multi-spectral dataset and 84.27% on the infrared target multi-spectral dataset, validating its feasibility for target detection. This architecture represents an innovative outcome at the intersection of remote sensing and optical computing, significantly advancing the dissemination and practical adoption of optical computing in the field. Full article

Recommender systems are data-driven tools designed to assist or automate users’ decision-making. With the growing demand of personalized sequential recommendations in business intelligence or e-commerce, effectively capturing temporal information from massive user-sequence data has become a crucial challenge. State-of-the-art attention-based models often struggle to balance performance with computational cost, while traditional convolutional neural networks suffer from limited receptive fields and rigid architectures that inadequately model dynamic user interests. To address these limitations, this paper proposes TimeWeaver, a time-aware dual-stream network for sequential recommendation, whose core innovations comprise three key components. First, it employs a re-parameterized large-kernel convolution to expand the effective receptive field. Second, we design a Time-Aware Augmentation mechanism that integrates inter-event time-interval information into positional encodings of items. This allows it to perceive the temporal dynamics of user behavior. Finally, we propose a dual-stream architecture to jointly capture dependencies across different time scales. The context stream employs a modern Temporal Convolutional Network (TCN) structure to strengthen the memorization of users’ medium- and long-term interests. In parallel, the dynamic stream leverages an Exponential Moving Average (EMA) mechanism to weight recent behaviors for sensitively capturing users’ immediate interests. This dual-stream design allows TimeWeaver to comprehensively extract both long- and short-term sequential features. Extensive experiments on three public e-commerce datasets demonstrate TimeWeaver’s superiority. Compared to the strongest baseline model, TimeWeaver achieves average relative improvements of 4.62%, 9.59%, and 4.59% across all metrics on the Beauty, Sports, and Toys datasets, respectively. Full article

Background/Objectives: Interpretation of mixture profiles generated from crime scene samples is an important element in forensic genetics. Here, a workflow for mixture deconvolution of sequenced microhaplotypes (MHs) and STRs using the probabilistic genotyping software MPSproto v0.9.7 was developed, and the performance of the two types of loci was compared. Methods: Sequencing data from a custom panel of 74 MHs (the MH-74 plex) and a commercial kit with 26 autosomal STRs (the ForenSeq™ DNA Signature Prep Kit) were used. Single-source profiles were computationally combined to create 360 two-person and 336 three-person mixtures using the Python script MixtureSimulator v1.0. Additionally, 72 real mixtures typed with the MH-74 plex and 18 real mixtures typed with the ForenSeq Kit from a previous study were deconvoluted using MPSproto. Results: The deconvoluted MH profiles were more complete and had fewer wrong genotype calls than the deconvoluted STR profiles. The contributor proportion estimates were more accurate for MH profiles than for STR profiles. Wrong genotype calls were mostly caused by locus and heterozygous imbalances, noise reads, or an inaccurate contributor proportion estimation. The latter was especially problematic in STR sequencing data, when two contributors contributed equally to the mixture. A total of 34,800 deconvolutions of the simulated mixtures were performed with two defined hypotheses: H_p, “The sample consists of DNA from one/two unknown contributor(s) and the suspect” and H_d, “The sample consists of DNA from two/three unknown individuals”. All true contributors were identified (LR > 10¹⁵ for MHs and LR > 10⁹ for STRs) and all non-contributors excluded (LR < 10⁻⁶ for MHs and LR < 0.2 for STRs). Conclusions: In simulated and real mixtures, the MHs performed better than STRs. Full article

High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of ovarian cancer, accounting for approximately 70% of cases. This study investigates genetic mutations and their associations with overall survival (OS), complete cytoreduction (R0), and platinum response in patients undergoing either primary debulking surgery followed by adjuvant chemotherapy (PDS) or neoadjuvant chemotherapy followed by interval debulking surgery (NACT). Genetic analysis was performed on 43 primary HGSOC tumor samples using targeted massive parallel sequencing via next-generation sequencing (NGS). Clinical and molecular data were evaluated collectively and through subgroup comparisons between PDS and NACT cohorts. All analyzed samples harbored genetic alterations. Univariate survival analysis revealed that the total number of mutations (p = 0.0035), as well as mutations in HRAS (p = 0.044), FLT3 (p = 0.023), TP53 (p = 0.03), and ERBB4 (p = 0.007), were significantly associated with poorer OS. Multivariate Cox regression integrating clinical and molecular data confirmed that ERBB4 mutations are independently associated with adverse outcomes. These findings reveal a distinctive mutational landscape between the PDS and NACT groups and suggest that ERBB4 alterations may define a particularly aggressive tumor phenotype. This study contributes to a deeper understanding of HGSOC biology and may support the development of novel therapeutic targets and personalized treatment strategies in the context of precision oncology. Full article

Massively parallel or next-generation sequencing (NGS) has enabled the genetic characterization of cancer patients, allowing the identification of somatic and germline variants associated with their diagnosis, tumor classification, and therapy response. Despite its benefits, NGS testing is not yet available in the Chilean public health system, rendering it both costly and time-consuming for patients and clinicians. Using a retrospective cohort of 67 formalin-fixed, paraffin-embedded (FFPE) colorectal cancer (CRC) samples, we aimed to implement the identification, annotation, and prioritization of relevant actionable tumor somatic variants in our laboratory, as part of the public health system. We compared two different library preparation methodologies (amplicon-based and capture-based) and different bioinformatics pipelines for sequencing analysis to assess advantages and disadvantages of each one. We obtained 80.5% concordance between actionable variants detected in our analysis and those obtained in the Cancer Genomics Laboratory from the Universidad de Chile (62 out of 77 variants), a validated laboratory for this methodology. Notably, 98.4% (61 out of 62) of variants detected previously by the validated laboratory were also identified in our analysis. Then, comparing the hybridization capture-based library preparation methodology with the amplicon-based strategy, we found ~94% concordance between identified actionable variants across the 15 shared genes, analyzed by the TumorSec^TM bioinformatics pipeline, developed by the Cancer Genomics Laboratory. Our results demonstrate that it is entirely viable to implement an NGS-based analysis of actionable variant identification and prioritization in cancer samples in our laboratory, being part of the Chilean public health system and paving the way to improve the access to such analyses. Considering the economic realities of most Latin American countries, using a small NGS panel, such as TumorSec^TM, focused on relevant variants of the Chilean and Latin American population is a cost-effective approach to extensive global NGS panels. Furthermore, the incorporation of automated bioinformatics analysis in this streamlined assay holds the potential of facilitating the implementation of precision medicine in this geographic region, which aims to greatly support personalized treatment of cancer patients in Chile. Full article

Grain yield establishment is a complex progress and the genetic basis of one of the most important yield components, 100-kernel weight, remains largely unknown. Here, we employed a double haploid (DH) population containing 477 lines which was developed from a cross of two maize elite inbred lines, PHBA6 and Chang7-2, to identify quantitative trait loci (QTL) that related to 100-kernel weight. The phenotypes of the DH population were acquired over three years in two different locations, while the DH lines were genotyped by next-generation sequencing technology of massively parallel 3ʹ end RNA sequencing (MP3RNA-seq). Eventually, 28,874 SNPs from 436 DH lines were preserved after SNP calling and filtering and a genetic map with a length of 837 cM was constructed. Then, single environment QTL analysis was performed using the R/qtl program, and it was found that a total of 17 QTLs related to 100-kernel weight were identified and distributed across the whole genome except chromosomes 5 and 6. The total phenotypic variation explained by QTLs detected in three different environments (BJ2016, BJ2107, and HN2018) was 22.2%, 32.9%, and 51.38%, respectively. Among these QTLs, three of them were identified across different environments as environmentally stable QTLs and explained more than 10% of the phenotypic variance each. Together, the results provided in this study preliminarily revealed the genetic basis of 100-kernel weight and will enhance molecular breeding for key agronomic kernel-related traits in maize. Full article

In this study, 172 Single-Nucleotide Polymorphisms (SNPs) (94 identity-informative SNPs, 56 ancestry-informative SNPs, and 22 phenotypic-informative SNPs) included in the ForenSeq™ DNA Signature Prep kit/DNA Primer Mix B (Verogen) were used for genotyping DNA samples from a population of twenty-one unrelated subjects, native to Northeast Italy. SNP sequencing was performed with the MiSeq FGx™ Forensic Genomics System (Illumina-Verogen), and data were analyzed using the Universal Analysis Software (UAS) v1.2. Raw data underwent further examination with STRait Razor v3 (SRv3) to compare the target SNPs’ genotype calls made with UAS and to identify the presence of microhaplotypes (MHs) due to SNPs associated with the same target SNP’s amplicon. The allele (haplotype) frequencies, Hardy–Weinberg equilibrium, linkage disequilibrium, number of effective alleles (A_e), and relevant forensic statistic parameters were calculated. Among the 172 SNPs evaluated, 45 unique microhaplotypes were found, comprising a novel sequence variant never previously described. The presence of MHs resulted in an 8.00% rise in the typologies of unique sequences, leading to changes in A_e. Notably, for 12 out of the 94 iiSNPs, the values of A_e exceeded 2.00, which is generally associated with a higher expected heterozygosity and increased power of discrimination. Full article

Forensic genetics has experienced remarkable advancements over the past decades, evolving from the analysis of a limited number of DNA segments to comprehensive genome-wide investigations. This progression has significantly improved the ability to establish genetic profiles under diverse conditions and scenarios. Beyond individual identification, forensic genetics now enables the inference of physical traits (e.g., eye, hair, and skin color, as well as body composition), biogeographic ancestry, lifestyle habits such as alcohol and tobacco use, and even the transfer of genital microbiomes post-coitus, among other characteristics. Emerging trends point to a future shaped by the integration of cutting-edge technologies, including CRISPR-Cas systems, artificial intelligence, and machine learning, which promise to further revolutionize the field. This review provides a thorough exploration of forensic genetics, tracing its evolution from its foundational methods (past) to its diverse modern applications (present) and offering insights into its potential future directions. Full article

Noninvasive prenatal paternity testing (NIPPT) is a crucial tool in forensic contexts, particularly in cases involving post-rape pregnancies. It enables judicial authorities and victims to promptly address these situations by determining the paternity of the fetus within a few weeks of pregnancy. NIPPT relies on the analysis of cell-free fetal DNA (cffDNA) found in the maternal bloodstream. However, the abundance of maternal DNA presents a significant challenge in detecting fetal DNA. As a result, research has focused on improving methods for isolating or enriching fetal DNA and, specifically in the context of forensic genetics, on the development of suitable genetic markers. The use of Single Nucleotide Polymorphisms (SNPs) along with novel compound markers or composite multiplexes, has shown promising results. Despite significant advances, partly driven by the increased use of Massive Parallel Sequencing (MPS), challenges remain in validating markers-based NIPPT assays for forensic casework. Further studies are required to enhance the sensitivity of these tests, particularly during the early stages of pregnancy, such as the first trimester. Additionally, improving and standardizing statistical frameworks for result evaluation and interpretation is essential to ensure compatibility with forensic standards. Full article