Forensic Science International-Genetics最新文献

{"title":"Forensic inference in Africa: Evaluating population structure, databases, and regional assignment accuracy","authors":"Mohaimin Kasu ,&nbsp;Jessica Caroline Anne Morrow ,&nbsp;Mpasi Lesaoana ,&nbsp;Humphrey Brydon ,&nbsp;Maria Eugenia D’Amato","doi":"10.1016/j.fsigen.2026.103441","DOIUrl":"10.1016/j.fsigen.2026.103441","url":null,"abstract":"<div><div>This study reports novel 21 aSTR (autosomal Short Tandem Repeats) allele frequencies from 538 individuals, as well as 11 triallelic profiles, representing seven Bantu-speaking groups in Southern Africa (Ndebele, Pedi, Phuthi, Tsonga, Sotho, Swati, and Xhosa). These data contributed to a comprehensive representation of the Southern Bantu (SB). The defined SB reference database was evaluated for various forensic uses and applications: extant diversity, population structure, adequacy of alternative reference databases, and continental biogeographical ancestry prediction.</div><div>Different analytical methods—including summary statistics, multivariate analyses (Multidimensional Scaling, MDS; Discriminant Analysis of Principal Components, DAPC), and Bayesian clustering—detected continental structure, identifying four major clusters: Southern, Eastern, Western, and Horn of Africa.</div><div>This observation motivated the evaluation of two practical applications of this information: one methodological (alternative reference frequency database) and one predictive (biogeographic assignment). The adequacy of alternative reference databases for representing SB populations—STRidER South Africa, STRidER Africa, African American, and global datasets—was assessed by comparing reciprocal allelic coverage and shifts in random match probabilities (RMPs). Of the databases tested, the STRidER Africa database provided the closest representation of the SB. Population-level analyses evidenced the need for a stratification correction (θ = 0.005 or 0.01) for SB populations.</div><div>Intracontinental biogeographic prediction was assessed using an XGBoost machine learning classification model across four major African regions. The model’s predictive balanced accuracy ranged from 80 % to 94 % across African regions (94 % for the Horn of Africa, 87 % for Southern Africa, 84 % for Western Africa, and 80 % for Eastern Africa).</div><div>The accuracy and limitations of this practice are discussed, along with its ethical implications. The assessment of reference databases can be extended to more general applications across Africa.</div></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103441"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146215276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Salience, legitimacy and credibility of single-cell sperm data and their evaluation","authors":"Catherine M. Grgicak ,&nbsp;Qhawe Bhembe ,&nbsp;Klaas Slooten ,&nbsp;Anu Khandelwal ,&nbsp;Ken R. Duffy ,&nbsp;Desmond S. Lun","doi":"10.1016/j.fsigen.2026.103476","DOIUrl":"10.1016/j.fsigen.2026.103476","url":null,"abstract":"<div><div>It is difficult to determine <em>how many</em> sperm donors contributed to a sample, <em>who</em> they were, or <em>what number</em> of sperm they donated. A model analyzing single-cell electropherograms (scEPG) born of diploid cells was previously introduced in [1]. In this paper we extend the model to handle haploid scEPGs, specifically sperm cells, and consider if single-cell forensics is ready to traverse the research-operations boundary. To do this we use the Salience-Legitimacy-Credibility (SLC) framework. In Salience we identify relevant forensic questions. Legitimacy then has us first describe the logic underpinning our haploid-aware model, and verify it was correctly implemented into EESCIt™. Using 121 individuated scEPGs – i.e., singlets – we show that the mean square error between the prediction and the empirical outcomes given that prediction is no more than 3.1 × 10⁻⁵ at any locus, demonstrating excellent model fidelity. LR-discrepancy analysis confirms the relative (empirical) frequency and magnitude of H₁- and H₂- LRs align with declared values, with the largest discrepancy being 0.3 in WoE – i.e., logLR – interval [1, 2]. Credibility analysis showed that no singlet produced a misdirected WoE and we receive, on average, one WoE for every ∼1200 RFU carried by a haploid. We then evaluate EESCIt™ on 33 sperm mixtures comprising 2–5 donors and find that estimates about the number of donors, the number of scEPGs by a donor, and the WoE remain legitimate. The system continues to credibly discriminate source hypotheses, often producing WoE of 10 when the PoI-true contributes as few as two haploids and values near 25 when 10 haploids are present. WoEs remain stable across mixture complexity with no dependence on the true number of contributors, <em>n,</em> showing a robustness unique to single cell data. Additionally, computational time is only mildly impacted by <em>n</em>, with the main determiner being the number of cells isolated. With a legitimate, credible haploid model able to address multifarious salient questions, we integrate it into EESCIt™, establishing a single-cell assessment system that is now capable of evaluating haploid single-cell data.</div></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103476"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction notice to “Population data of 17 Y-STR haplotypes in Jining Han population from Shandong province, East China” [Forensic Sci Int. Genet. 19 (2015) 47–49]","authors":"Dan Wang ,&nbsp;Faqin Liu ,&nbsp;Lingxue Kong ,&nbsp;Zhenyu Yuan ,&nbsp;Guang Chen ,&nbsp;Jian Ye","doi":"10.1016/j.fsigen.2026.103454","DOIUrl":"10.1016/j.fsigen.2026.103454","url":null,"abstract":"","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103454"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147461446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction notice to “Population genetics of 17 Y-STR loci in Chinese Manchu population from Liaoning Province, Northeast China” [Forensic Sci. Int.: Genet. 7 (2013) e84-e85]","authors":"Juan He ,&nbsp;Fei Guo","doi":"10.1016/j.fsigen.2026.103471","DOIUrl":"10.1016/j.fsigen.2026.103471","url":null,"abstract":"","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103471"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147461440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Internal validation of the fully continuous model in EuroForMix for its implementation in routine forensic DNA profiling","authors":"J. González-Bao ,&nbsp;A. Mosquera-Miguel ,&nbsp;L. Casanova-Adán ,&nbsp;A. Ambroa-Conde ,&nbsp;A. Freire-Aradas ,&nbsp;A. Cabrejas-Olalla ,&nbsp;M. Boullón-Cassau ,&nbsp;M. Palhares ,&nbsp;J. Ruiz-Ramírez ,&nbsp;A. Rodríguez-López ,&nbsp;C. Phillips ,&nbsp;M.V. Lareu ,&nbsp;M. de la Puente","doi":"10.1016/j.fsigen.2026.103460","DOIUrl":"10.1016/j.fsigen.2026.103460","url":null,"abstract":"<div><div>Despite being increasingly more common in the forensic routine, DNA mixtures still present an important roadblock in the analysis of genetic evidence. The International Society for Forensic Genetics (ISFG) recommends the use of the Likelihood Ratio (LR) in the statistical evaluation of the evidence for the contribution of a certain Person of Interest (POI). Numerous mathematical models have been developed for this purpose, which can be classified according to the information included: i) binary models only use the allelic information, ii) qualitative or semi-continuous models also accommodate drop-out and drop-in probabilities and iii) quantitative or fully continuous models include additionally allelic signal intensity (peak heights or read coverage). Before being implemented in the forensic routine, any software that supports a form of these models must be tested in different scenarios to perform an internal validation.</div><div>In this work we present the results of our internal validation of the fully continuous model present in EuroForMix (EFM) and DNAStatistX (used as control of EFM in this study), comparing its performance to the semi-continuous model in LRmix Studio. To do so, 59 artificial samples were prepared from 8 unrelated contributors in mixtures of 2, 3 and 4 contributors; besides, 19 tests from 7 real cases were run in both software. The following analyses were conducted: i) scrutiny of contributors in single-source serially diluted samples; ii) estimation of the percentage of contribution to the mixture; iii) comparison of results obtained in artificial mixtures for H1-True and H1-False hypotheses; iv) effect of sensitivity analysis in the final result; v) discrimination power of each model; vi) the behaviour of the Automatic Model Search option in EuroForMix and vii) comparison of results obtained in real casework analyses.</div><div>Our results show that EFM returns higher values than LRmix Studio both in single-source and mixed scenarios. The fully continuous model has demonstrated a neutral behaviour, returning inconclusive results when genetic evidence is scarce. If a reporting threshold is applied EFM is especially affected, with a higher proportion of negative log(LR) results turning inconclusive in comparison to LRmix Studio. Overall, EuroForMix has shown a correct performance, returning reliable results and reducing the subjectivity of the analysis.</div></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103460"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147357952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large-scale analysis of DNA quantification metrics and SNP sequencing performance in unidentified human remains","authors":"Steven A. Bates ,&nbsp;Bruce Budowle ,&nbsp;Morgan Johnson ,&nbsp;Jianye Ge ,&nbsp;Kristen Mittelman ,&nbsp;David Mittelman","doi":"10.1016/j.fsigen.2026.103470","DOIUrl":"10.1016/j.fsigen.2026.103470","url":null,"abstract":"<div><div>Massively parallel sequencing (MPS)–based single nucleotide polymorphism (SNP) profiling is being increasingly used in forensic DNA testing, yet the informative value of common pre-sequencing DNA metrics to predict SNP profile completeness remains unclear. In this study, 500 anonymized skeletal samples submitted for forensic genome sequencing were analyzed to assess the relationships between bone type, DNA quantitation metrics, and SNP call rate (the latter used as a measure of profile completeness). Human-specific DNA quantity was measured using short and long autosomal quantitative PCR targets, and total DNA content was assessed fluorometrically. Of the 500 samples, 399 met a minimum human DNA threshold (short autosomal target ≥0.005 ng/µl) and were sequenced. Among these samples, SNP call rates ranged from 8% to 91%, with 95.7% achieving call rates greater than 50%. Call rate was most strongly associated with features reflecting the ratio between endogenous human DNA and total DNA, which includes exogenous background DNA. The total:short DNA ratio (log₁₀ r = −0.48) and estimated human DNA input into library preparation (log₁₀ r = 0.41) showed the strongest correlations, while degradation index showed only a modest association. Bone type influenced the likelihood that samples progressed to sequencing, but among sequenced samples, call rate distributions were similar across major bone type categories. Machine-learning models achieved moderate predictive performance (best validation R² = 0.47), indicating that current quantification metrics are correlated with, but not sufficient to reliably predict, SNP profile completeness. Overall, these results demonstrate that MPS-based SNP profiling of UHRs is highly effective and support forensic genetic genealogy as the preferred approach for generating actionable genetic data for identification of human remains. However, due to varying degrees of DNA quality and quantity in bones samples, the common pre-sequencing metrics, while providing some actionable workflow decisions in this study, are insufficient predictors for the range of samples encountered in unidentified human remains.</div></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103470"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147313636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MitoMetrics: Incorporation of mtDNA profile discrepancies in likelihood ratio calculations","authors":"Floor Claessens ,&nbsp;Mikkel Meyer Andersen ,&nbsp;Christina Amory ,&nbsp;Cristina Arévalo ,&nbsp;Stijn Desmyter ,&nbsp;Sophie Dognaux ,&nbsp;Kristiaan J. van der Gaag ,&nbsp;Tomasz Grzybowski ,&nbsp;Gabriela Huber ,&nbsp;Filomena Melchionda ,&nbsp;Hiroaki Nakanishi ,&nbsp;Tóra Olsen ,&nbsp;Cristina Pie ,&nbsp;Lourdes Prieto ,&nbsp;Katarzyna Skonieczna ,&nbsp;Chiara Turchi ,&nbsp;Walther Parson ,&nbsp;Vania Pereira","doi":"10.1016/j.fsigen.2026.103477","DOIUrl":"10.1016/j.fsigen.2026.103477","url":null,"abstract":"<div><div>Interpretation of mitochondrial DNA (mtDNA) evidence in a forensic context faces challenges, particularly when evaluating mtDNA profiles from different tissues. In hair, for example, the segregation of mtDNA shows tight bottlenecks that can result in different mtDNA profiles between and along hair shafts, and between hair and other reference tissues of the same donor. Current forensic interpretation guidelines for mtDNA are based on conventions on the number of discrepant positions observed between the two compared profiles. Most legislations consider two discrepancies between samples as an exclusion, and one discrepancy as an inclusion or as an inconclusive result. More data are needed to understand the variation and occurrence of discrepancies in samples from the same donor, to be able to incorporate this knowledge into a mathematical approach that effectively quantifies the probability of these events. This study reports the first project of the MitoMetrics collaborative initiative. In this study, data were generated from several participating laboratories, and previously published data, along with data generated from casework. mtDNA profiles from blood/buccal reference samples were compared to those from hair shafts from the same individuals. Results report the levels of heteroplasmy detected in the different tissues, the number of differences observed between the tissue comparisons, and the number of discrepant positions observed. We suggest a preliminary model for calculating the evidential value of mtDNA-based evidence using a likelihood ratio approach, that takes into consideration the occurrence of discrepancies between profiles from the same donor. This work represents the first attempt to quantify the probability of finding discrepant events between tissues and to incorporate these when reporting mtDNA in a forensic context.</div></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103477"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shotgun DNA sequencing evidence: Sample-specific and unknown genotyping error probabilities","authors":"Mikkel Meyer Andersen","doi":"10.1016/j.fsigen.2026.103474","DOIUrl":"10.1016/j.fsigen.2026.103474","url":null,"abstract":"<div><div>Many forensic genetic trace samples are of too low quality to obtain short tandem repeat (STR) DNA profiles as the nuclear DNA they contain is highly degraded (e.g., telogen hairs). Instead, performing shotgun DNA sequencing of such samples can provide valuable information on, e.g., single nucleotide polymorphism (SNP) markers. As a result, shotgun sequencing is starting to gain more attention in forensic genetics and statistical models to correctly interpret such evidence, including properly accounting for sequencing errors, are needed. One such model is the <span>wgsLR</span> model by Andersen et. al. (2025) that enabled evaluating the evidential strength of a comparison between the genotypes in the trace sample and reference sample assuming a single-source contribution to both samples. This paper extends the <span>wgsLR</span> model to allow for different (asymmetric) genotyping error probabilities (e.g., from a low quality trace sample and a high quality reference sample). The model was also extended to handle unknown genotyping error probabilities via both maximising profile likelihood and using a prior distribution. It was found that an unknown genotyping error probability of the trace sample could be handled with these methods when having a sufficient number of independent markers and that the results were was robust to different specifications of the prior distribution. The sensitivity of the <span>wgsLR</span> model against overdispersion was also investigated and it was found robust against it. The extensions of the model are implemented in the <span>R</span> package <span>wgsLR</span>.</div></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103474"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction notice to “Genetic profile of 17 Y chromosome STRs in the Guizhou Han population of southwestern China” [Forensic Sci. Int.: Genet. 25 (2016) e6–e7]","authors":"Hao Zhou,&nbsp;Zheng Ren,&nbsp;Hongling Zhang,&nbsp;Jie Wang,&nbsp;Jiang Huang","doi":"10.1016/j.fsigen.2026.103457","DOIUrl":"10.1016/j.fsigen.2026.103457","url":null,"abstract":"","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103457"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147461383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum to “Age prediction using DNA methylation of Y-chromosomal CpGs in semen samples” [Forensic Sci. Int.: Genet. 69 (2024) 103007]","authors":"Ji Eun Lee ,&nbsp;Hwan Young Lee","doi":"10.1016/j.fsigen.2026.103503","DOIUrl":"10.1016/j.fsigen.2026.103503","url":null,"abstract":"","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"84 ","pages":"Article 103503"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147792875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}