Search Results (34)

Conventional forensic DNA profiling predominantly utilizes established core sets of autosomal short tandem repeats (STRs), such as the FBI’s Combined DNA Index System (CODIS) and the European Standard Set (ESS). While these panels are effective for standard forensic casework, they may be inadequate in more demanding scenarios, including severely degraded samples, complex multi-contributor mixtures, and kinship cases with deficiencies, where enhanced discriminatory capability is crucial. Additional non-core STR loci address these challenges while maintaining the non-coding, phenotypically uninformative nature that ensures the legal and ethical acceptability of forensic genetic evidence in court. This review assesses the forensic applications, population genetic parameters, validation requirements, and ethical considerations associated with non-core STR loci. A representative supplementary STR panel is presented as a case study to illustrate both the forensic value and the analytical requirements associated with the implementation of extended non-core STR systems. Challenges in implementation were identified in areas such as nomenclature standardization, backward compatibility with existing national databases, and geographic gaps in population reference data. The review concludes that a hybrid strategy, which retains core capillary electrophoresis (CE)-based profiling for routine casework and employs extended non-core panels for complex cases, represents the most practical path for the field. Full article

Background/Objectives: The expansion of direct-to-consumer (DTC) genetic testing has generated civilian genomic databases containing tens of millions of profiles, some of which may be available, under specific conditions, for criminal investigations. Meanwhile, artificial intelligence (AI) is reshaping forensic genetics through applications such as kinship inference, DNA mixture deconvolution, probabilistic phenotyping, and the prioritization of investigative leads. This review examines the scientific, legal, and ethical implications of the convergence between DTC genetic databases, forensic investigative genetic genealogy (FIGG), and AI-assisted forensic analysis. Methods: This article presents a multidisciplinary narrative review at the intersection of forensic genomics, FIGG, artificial intelligence, genomic data governance, and bioethics, with particular attention to French, European, and international regulatory frameworks. Results: Six major dimensions structure the field: (i) the current state of forensic genomic technologies, including STRs, SNPs, and next-generation sequencing; (ii) the contribution of AI to forensic genetics and FIGG; (iii) the governance of large-scale genomic data; (iv) regulatory fragmentation across jurisdictions; (v) the principal bioethical tensions raised by the forensic use of DTC genetic databases; and (vi) future governance needs and operational recommendations. Across these dimensions, three findings emerge. First, genealogical matches and AI-supported outputs should be understood primarily as investigative leads rather than autonomous judicial evidence. Second, the relational nature of genomic data exposes non-consenting relatives to potential forensic scrutiny, thereby challenging traditional models of individual consent and privacy. Third, the absence of harmonized standards for validation, transparency, and oversight remains a major obstacle to legal certainty, judicial admissibility, and public legitimacy. Conclusions: The forensic use of DTC genetic databases should not be understood as a purely technical extension of conventional DNA profiling. It reflects a broader transformation in the relationship between genomic knowledge, criminal investigation, and fundamental rights. Its long-term legitimacy and operational viability will depend on the combined strength of scientific reliability, legal proportionality, ethical safeguards, and meaningful democratic oversight. Full article

The following narrative review discusses the use of deep learning and 3D modeling in facial reconstruction from skeletal remains, focusing on accuracy, algorithmic bias, and evidential reliability. Forensic facial reconstruction (FFR) is a multidisciplinary field combining anthropology, medicine, and visual sciences to approximate the facial appearance of unidentified individuals from skeletal remains. Traditional manual methods, based on anatomical knowledge and facial soft tissue thickness (FSTT) measurements, are limited by subjectivity, labor intensity, and inter-expert variability. This narrative review summarizes contemporary AI-assisted approaches, with emphasis on convolutional neural networks (CNNs), generative adversarial networks (GANs), variational autoencoders (VAEs), and diffusion models, which enable probabilistic prediction of facial morphology while accounting for demographic variables such as sex, age, and population ancestry. Key challenges affecting reconstruction accuracy—including dataset limitations, population-specific variability, and algorithmic bias—are discussed, alongside quantitative validation methods and concerns regarding model transparency. Legal and ethical considerations, such as privacy, biometric data protection, and the need for explainable AI (XAI) frameworks, are highlighted. Future perspectives include hybrid expert–AI workflows, the development of globally representative datasets, and the integration of multimodal data sources, including DNA phenotyping, 3D morphometrics, and biomechanical modeling. These advances aim to create standardized, interpretable, and biologically informed frameworks that enable AI to support expert judgment and enhance the reliability of forensic facial reconstructions. 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

Background: Phenotype prediction for eye, hair and skin color is used in a variety of forensic applications, such as trace analysis, the identification of unknown individuals, and analysis of historical DNA traces. The aim of this study was to evaluate the predictive accuracy of the HIrisPlex-S system in a homogeneous North German population. Methods: A cohort of 155 individuals from this population was sampled, and the 41 HIrisPlex-S SNPs were genotyped using the SNaPshot workflow. In addition, the participants assessed their own eye, hair, and skin color using a standardized questionnaire. The statistical analysis included the calculation of diagnostic indicators such as sensitivity (Sens), specificity (Spec), positive and negative predictive values, and accuracy (Acc). In addition, ROC analyses were performed. Results: The results indicated that predictions of skin and hair color were less accurate, whereas eye color could be determined more reliably. Brown and blue eye colors in particular were predicted accurately (brown: Sens = 94.7%, Spec = 87.7%, Acc = 89.5%; blue: Sens = 98.5%, Spec = 57.7%, Acc = 75.7%), while intermediate eye color (Sens = 0.0%, Spec = 100.0%, Acc = 69.1%), hair color and skin color were difficult to differentiate (e.g., blond hair color: Sens = 80.8%, Spec = 56.0%, Acc = 68.2% and pale skin color: Sens = 73.8%, Spec = 44.8%, Acc = 57.2%). Conclusions: In our study, the HIrisPlex-S system primarily provided rough directional information and could distinguish between very different phenotypes but reached its limits when it comes to similar characteristics. Full article

Background: Forensic DNA phenotyping (FDP) enables the inference of externally visible characteristics (EVCs) and biogeographic ancestry when conventional STR profiling is inconclusive. The ForenSeq™ Imagen kit (107 SNPs) integrates phenotype-, ancestry-, and Y-SNPs markers; however, its performance under partial genotyping conditions has not been systematically evaluated. Methods: Ninety-four samples from a Mexican mestizo population were analyzed using the ForenSeq™ Imagen kit on the MiSeq FGx™ platform. Due to incomplete genotype recovery, 41 samples with >60% locus detection were selected for downstream analyses. Phenotype prediction was performed using the HIrisPlex-S model, and ancestry inference was assessed through principal component analysis. In silico simulations were conducted to evaluate locus-specific dropout effects. Results: Eye color prediction showed both reduced feasibility (68.3%) and lower overall accuracy (56.1%), primarily driven by systematic prediction failure when rs12913832 (HERC2) was absent, although accuracy among successfully predicted samples remained high (82.1%). In contrast, hair and skin color inference remained feasible in >97% and 100% of evaluable samples, respectively; however, classification accuracy was moderate (70% for hair and 61% for skin), improving substantially when allowing adjacent-category concordance (90.2% for skin). Ancestry inference was robust when at least 27 aiSNPs were detected, and Y-SNPs reliably distinguished male and female samples. In silico analyses confirmed the critical contribution of rs12913832 to eye color model operability. Conclusions: FDP performance under partial genotyping reflects a trade-off between prediction feasibility and accuracy and depends on locus-specific integrity rather than overall genotype completeness. The ForenSeq™ Imagen kit shows robustness for ancestry, sex, hair, and skin prediction, although with variable accuracy, whereas eye color inference remains structurally vulnerable to drop out of high-impact variants. Evaluating FDP systems under realistic non-ideal conditions is essential to define their true operational limits and ensure scientifically robust and responsible implementation. Full article

Background/Objectives: The increasing global trend in nail beautification may lead to analyses of nails with semi-permanent polish for the identification of degraded human remains. This study aimed to evaluate the effects of cosmetic nail treatment on forensic STR DNA profiling and phenotyping of eye, hair, and skin colour characteristics using a massively parallel sequencing (MPS) assay. Methods: Forty-two nail samples obtained from 21 volunteers, classified in “new”, occasional and regular semi-permanent polish users, were submitted to DNA analysis. Results: The use of semi-permanent nail polish, particularly when applied repeatedly, resulted in a significant reduction in DNA recovery, but it did not affect STR typing for personal identification. Mixed STR profiles were observed in 28.6% of the samples, indicating that the nail washing procedure employed before DNA extraction did not completely remove the foreign DNA; however, this could be useful depending on the forensic context. FDP analysis was successfully applied on nails with semi-permanent polish that showed a good quantity of DNA and single-source profiles. Conclusions: The results highlight the evidentiary value of fingernails even if treated with semi-permanent nail polish that should still be regarded as a source of DNA for personal identification and further investigation in the forensic context. Full article

Background/Objectives: Forensic DNA phenotyping (FDP) enables the prediction of externally visible characteristics (EVCs) such as eye, hair, and skin color, ancestry, and age from biological traces. However, low template DNA (LT-DNA), often derived from degraded or trace samples, poses significant challenges due to allelic dropout, contamination, and incomplete profiles. This review evaluates recent advances in FDP from LT-DNA, focusing on the integration of machine learning (ML) models to improve predictive accuracy and operational readiness, while addressing ethical and population-related considerations. Methods: A comprehensive literature review was conducted on FDP and ML applications in forensic genomics. Key areas examined include SNP-based trait modeling, genotype imputation, epigenetic age estimation, and probabilistic inference. Comparative performance of ML algorithms (Random Forests, Support Vector Machines, Gradient Boosting, and deep learning) was assessed using datasets such as the 1000 Genomes Project, UK Biobank, and forensic casework samples. Ethical frameworks and validation standards were also analyzed. Results: ML approaches significantly enhance phenotype prediction from LT-DNA, achieving AUC > 0.9 for eye color and improving SNP recovery by up to 15% through imputation. Tools like HIrisPlex-S and VISAGE panels remain robust for eye and hair color, with moderate accuracy for skin tone and emerging capabilities for age and facial morphology. Limitations persist in admixed populations and traits with polygenic complexity. Interpretability and bias mitigation remain critical for forensic admissibility. Conclusions: L integration strengthens FDP from LT-DNA, offering valuable investigative leads in challenging scenarios. Future directions include multi-omics integration, portable sequencing platforms, inclusive reference datasets, and explainable AI to ensure accuracy, transparency, and ethical compliance in forensic applications. Full article

Forensic DNA phenotyping (FDP) is an important innovation approach in forensics sciences, especially when traditional DNA profiling results are limited, mostly due to the absence of reference samples. FDP is based on the detection of genetic variants in specific genes whose function is related to pigmentation mechanisms and uses the genotypes found in the sample to determine the externally visible traits (EVT) such as the iris, hair, and skin tone or color of the individual; this prediction would help and expedite human identification processes and solve criminal cases. Several technologies have been developed to facilitate EVT prediction; however, most of them have been validated only in European populations. Implementing techniques for FDP in Latin American countries is essential given the problems of disappearance and human identification that have persisted for years. Nonetheless, scientists have a great challenge due to the admixed genetic structure of the population. This review explores the current application of FDP, emphasizing its significance, practical uses, and limitations within Latin American populations. 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

Background/Objectives: Identification of human remains is of utmost importance for criminal investigations and providing closure to the families. The reconstruction of a biological profile of the individual will narrow down the list of candidates for identification. From another perspective, facial approximations performed by a forensic artist can provide investigative leads, with the identity being confirmed by primary or secondary methods of identification. In recent years, DNA analysis has evolved, trying to create a portrait of the perpetrator/victim based on External Visible Characteristics (EVCs), the color of the eyes, hair, and skin and Biogeographical ancestry (BGA), called DNA phenotyping. Despite these advances, currently, there are no studies integrating the biological profile performed by forensic anthropologists, the facial approximation created by forensic artists and EVCs determined by DNA. The goal of this work was to integrate these three investigative leads to enhance the possibility of human identification. Methods: Five donated remains from Mercyhurst were studied through these approaches: reconstruction of biological profile, facial approximation and estimation of EVCs based on previous studies. Results: Our results indicated the feasibility of integrating this biological profile and EVCs data into the facial approximation developed by the forensic artist, aiming to an enhance portrait of the remains. In a second phase of this project, the accuracy of the integrated facial approximation will be assessed. Conclusions: This study pointed out the importance of an interdisciplinary approach towards the identification of human remains, as well as the combination of current methods with new technologies. Full article

Forensic DNA phenotyping (FDP) has emerged as an essential tool in criminal investigations, enabling the prediction of physical traits based on genetic information. This review explores the genetic factors influencing skin pigmentation, particularly within Asian populations, with a focus on Thailand. Key genes such as Oculocutaneous Albinism II (OCA2), Dopachrome Tautomerase (DCT), KIT Ligand (KITLG), and Solute Carrier Family 24 Member 2 (SLC24A2) are examined for their roles in melanin production and variations that lead to different skin tones. The OCA2 gene is highlighted for its role in transporting ions that help stabilize melanosomes, while specific variants in the DCT gene, including single nucleotide polymorphisms (SNPs) rs2031526 and rs3782974, are discussed for their potential effects on pigmentation in Asian groups. The KITLG gene, crucial for developing melanocytes, includes the SNP rs642742, which is linked to lighter skin in East Asians. Additionally, recent findings on the SLC24A2 gene are presented, emphasizing its connection to pigmentation through calcium regulation in melanin production. Finally, the review addresses the ethical considerations of using FDP in Thailand, where advances in genetic profiling raise concerns about privacy, consent, and discrimination. Establishing clear guidelines is vital to balancing the benefits of forensic DNA applications with the protection of individual rights. Full article

Background/Objectives: Emerging forensic genetic applications, such as forensic investigative genetic genealogy (FIGG), advanced DNA phenotyping, and distant kinship inference, increasingly require dense SNP genotype datasets. However, forensic-grade DNA often contains missing genotypes due to its quality and quantity limitations, potentially hindering these applications. Genotype imputation, a method that predicts missing genotypes, is widely used in population and medical genetics, but its utility in forensic genetics has not been thoroughly explored. This study aims to assess the performance of genotype imputation in forensic contexts and determine the conditions under which it can be effectively applied. Methods: We employed a simulation-based approach to generate realistic forensic SNP genotype datasets with varying numbers, densities, and qualities of observed genotypes. Genotype imputation was performed using Beagle software, and the performance was evaluated based on the call rate and imputation accuracy across different datasets and imputation settings. Results: The results demonstrate that genotype imputation can significantly increase the number of SNP genotypes. However, imputation accuracy was dependent on factors such as the quality of the original genotype data and the characteristics of the reference population. Higher SNP density and fewer genotype errors generally resulted in improved imputation accuracy. Conclusions: This study highlights the potential of genotype imputation to enhance forensic SNP datasets but underscores the importance of optimizing imputation parameters and understanding the limitations of the original data. These findings will inform the future application of imputation in forensic genetics, supporting its integration into forensic workflows. Full article

In recent decades, the use of genetic polymorphisms related to specific phenotypes, such as eye color, has greatly contributed to the development of the research field called forensic DNA phenotyping (FDP), enabling the investigators of crime cases to reduce the number of suspects, making their work faster and more precise. Eye color is a polygenic phenotype, and many genetic variants have been highlighted, with the major contributor being the HERC2-OCA2 locus, where many single nucleotide variations (SNPs) were identified. Interestingly, the HERC2-OCA2 locus, containing the intronic SNP rs12913832, the major eye color determinant, shows a high level of evolutionary conservation across many species of vertebrates. Currently, there are some genetic panels to predict eye color by genomic DNA analysis, even if the exact role of the SNP variants in the formation of eye color is still poorly understood, with a low level of predictivity in the so-called intermediate eye color. Many variants in OCA2, HERC2, and other genes lie in introns or correspond to synonymous variants, highlighting greater complexity in the mechanism of action of such genes than a simple missense variation. Here, we show the main genes involved in oculocutaneous pigmentation and their structural and functional features, as well as which genetic variants show the highest level of eye color predictivity in currently used FDP assays. Despite the great recent advances and impact of FDP in criminal cases, it is necessary to enhance scientific research to better understand the mechanism of action behind each genetic variant involved in eye color, with the goal of obtaining higher levels of prediction. Full article

It is very important to generate phenotypic results that are reliable when processing chronological old skeletal remains for cases involving the identification of missing persons. To improve the success of pigmentation prediction in Second World War victims, three bones from each of the eight skeletons analyzed were included in the study, which makes it possible to generate a consensus profile. The PowerQuant System was used for quantification, the ESI 17 Fast System was used for STR typing, and a customized version of the HIrisPlex panel was used for PCR-MPS. The HID Ion Chef Instrument was used for library preparation and templating. Sequencing was performed with the Ion GeneStudio S5 System. Identical full profiles and identical hair and eye color predictions were achieved from three bones analyzed per skeleton. Blue eye color was predicted in five skeletons and brown in three skeletons. Blond hair color was predicted in one skeleton, blond to dark blond in three skeletons, brown to dark brown in two skeletons, and dark brown to black in two skeletons. The reproducibility and reliability of the results proved the multisample analysis method to be beneficial for phenotyping chronological old skeletons because differences in DNA yields in different bone types provide a greater possibility of obtaining a better-quality consensus profile. Full article