Forensic Science International: Genetics

The formal assessment of a genetic match between a suspect and some biological trace material is one of the key tasks of forensic genetics, particularly in cases of sexual offence. The analysis of Y-chromosomal short tandem repeats (Y-STRs) has proven especially useful in this context. For a long time, however, calculating the probability of a perfect Y-STR profile match under the defense hypothesis that the suspect was not the trace donor posed a great challenge. This was due to the inherent uncertainty about the population of alternative donors, the so-called suspect population. We recently proposed to resolve this controversy by systematically favoring the suspect and considering his close male relatives as the suspect population. However, since the mathematical framework developed for this purpose was simulation-based, its practical application turned out increasingly difficult with increasing pedigree size. Here, we present an adaptation of the so-called Elston-Stewart algorithm, originally developed for the linkage analysis of human genetic diseases, to allow calculation of exact match probabilities in a time that scales linearly with pedigree size. The adapted algorithm was implemented in a publicly available software tool, and its correctness was verified by the comparison of its output with the correct, analytical results obtained for selected example pedigrees. The new implementation mostly outperforms the simulation-based solution, albeit with the important exception of Y-STRs present in multiple copies. Given the increasingly prominent role of such multicopy markers in forensic genetics, the complementary use of both approaches appears the most sensible strategy for the time being.

Forensic investigative genetic genealogy (FIGG) is a revolutionary method in forensic genetics, whereby genetic relatives of an unknown target person are detected in direct-to-consumer genomic databases; the family trees of these relatives are then reconstructed to suggest candidates for the target person. Despite recent successes, the full potential of the technology has not yet been systematically evaluated at the scale of an entire country. To estimate the proportion of FIGG cases where a genetic relative is detected in the database (the "match rate"), we used the Israeli population register, covering all past and present citizens. After extensive quality control, the register included 12.4 million individuals, among them 10.4 million alive. We simulated genomic databases by randomly selecting subsets of predefined sizes of the live adult population. With a database covering 1% of the population, we estimate that FIGG would detect at least one relative of fifth degree (e.g., a second cousin) or closer for about 25% of the population, and at least two relatives for 9% of the population. A database covering 5% of the population would find at least one relative of third degree (e.g., a first cousin) or closer for half the population. More distant relatives are rarely identified in the register, likely due to its limited time depth. Our results provide the first country-wide direct estimates for the utility of FIGG in generating investigative leads.

DNA findings on clothing are often evaluated at sub-source level to address whether a person contributed DNA to a sample. In many cases, however, the disputed issue is not whose DNA is present, but how the DNA was transferred. This paper applies the HaloGen framework to evaluate DNA findings on stockings under activity-level propositions. The data derive from controlled experiments, reported in a companion paper, comparing active contact, in which a person of interest pulled down a pair of stockings, with social contact, in which the person of interest and wearer used the same bathroom. Contributor-specific DNA quantities were estimated for the person of interest and for observed unknown contributors across two sampled stains. Compatibility diagnostics indicated that the stockings dataset was broadly compatible with the observed Pop20 reference range. Pop20 was therefore used as regularising prior information in the Lab-Bayes model, rather than as a stand-alone Group model. Because the stockings dataset was generated in a single laboratory, transfer data from 20 laboratories were used as regularising prior information for a laboratory-specific Lab-Bayes model. The local stockings data then updated the direct- and secondary-transfer parameter distributions. Compatibility diagnostics indicated that the stockings dataset was broadly compatible with the observed Pop20 reference range. Pop20 was therefore used as regularising prior information in the Lab-Bayes model, rather than as a stand-alone Group model. In addition, prior-sensitivity and leave-one-case-out analyses indicated that the case-level likelihood ratios were not materially affected by the choice of prior specification or by data reuse. HaloGen likelihood ratios were assessed using Tippett plots and compared with simplified contributor-based comparator approaches. These approaches represent simplified forms of activity-level reasoning in which the DNA result is reduced to binary or categorical states. They comprise a binary source-support approach, a discrete Mx component-size approach, and a background approach based on the ReAct I Experiment 3 formulation. These approaches were used to examine the effect of reducing continuous contributor-specific DNA quantities to binary or categorical states, and to assess how the likelihood ratio is affected when observed unknown contributors are represented through a background/direct-unknown term rather than evaluated explicitly as possible alternative direct actors. HaloGen showed clear discrimination between active-contact and social-contact ground-truth cases. The simplified comparator methods illustrated the information loss caused by thresholding or categorising continuous DNA quantities. The ReAct background approach tended to shift direct-transfer likelihood ratios upward relative to the HaloGen calculation, showing that the treatment of observed unknown contributors can materially affect activity-level inference. The results support the importance of preserving contributor-level symmetry: an observed unknown contributor should not automatically be demoted to background when that contributor may represent an alternative direct actor under the defence proposition.

Shotgun sequencing (SGS) enables simultaneous interrogation of a broad range of loci across the human genome, even from low-template and highly degraded DNA samples. While human identification traditionally relies on short tandem repeats (STRs) due to their high polymorphism, standard forensic STRs (100-450 bp) are poorly suited for the short read ([~]150 bp) constraint of SGS. The purpose of this study was to evaluate the analysis limitations of standard forensic STRs in SGS data and to identify a novel panel of STRs optimised for short-read genomic data. First, we benchmarked four STR genotyping software tools (STRait Razor, GangSTR, STRinNGS, and HipSTR) by analysing 53 standard forensic STRs in SGS data. HipSTR showed the best performance but achieved only a call rate of 64.5% and an accuracy of 83.8%, and its performance was strongly affected by STR allele length and read depth. To overcome these constraints, we screened the population-wide 1000 Genomes Project dataset and identified a panel of 265 autosomal ultra-short (< 50 bp) STRs with an effective number of alleles (Ae) ranging from 3.0 to 7.5. As few as seven of these loci were sufficient to achieve a Mean Match Probability (MMP) below 1 x 10-6. To validate these findings, we developed a custom PCR-based amplicon sequencing panel targeting 97 of the most polymorphic ultra-short STRs and evaluated these in 41 blood samples from Danish individuals. The polymorphic nature of the selected loci was confirmed (Aeranged from 2.4 to 7.2). Our results furthermore demonstrated high concordance between the amplicon panel and SGS-derived genotypes, which substantiates that these ultra-short STRs provide a robust and highly polymorphic alternative for human identification in SGS data. Author summaryShotgun sequencing (SGS) methods are increasingly being adopted in fields such as forensic genetics. SGS yields large amounts of genetic information by reading short fragments across the entire genome, enabling a wide range of analyses that may be exploited as leads in a police investigation. Human identification has traditionally been based on STR loci with a PCR amplicon length of 100-450 base pairs. However, these loci are often longer than the reads generated by SGS data, which makes them difficult to analyse in a reliable way. In this study, we evaluated four software tools designed to genotype STRs and confirmed the limited ability to genotype traditional forensic STRs in SGS data. To address this limitation, we identified a new set of highly polymorphic ultra-short STRs (less than 50 base pairs in length) that enable robust human identification using SGS data. Despite their shorter length, these loci retain the multi-allelic nature inherent to traditional STRs. This ensures a low random match probability that is comparable with the standard forensic STR panels. The ultra-short STRs may be genotyped from highly degraded DNA and may provide the possibility for complex mixture analysis and multi-donor deconvolution, which makes the STRs uniquely suited for forensic casework.

Shotgun sequencing of DNA mixtures has the potential to become an important tool in forensic genetics, particularly for degraded samples or complex mixtures. However, the analysis of shotgun-sequenced mixtures is challenged by several confounding factors, including sequencing errors, population structure, the potential presence of relatives, linkage, and linkage disequilibrium. Additionally, the statistical methods currently available for such data are limited. Here, we develop likelihood ratios that summarize the evidence for the presence of a suspects DNA in a mixture, assuming genotypes of the suspect and the victim are available, while accounting for DNA from unknown contributors modeled either as general population contamination or as a single contaminating individual. We show that these likelihood ratios are not robust to model assumptions and can falsely support the presence of the suspects DNA when the true contributor is even a distant relative. We therefore propose a combined evidence score, {Lambda}: the likelihood ratio minimized over contamination models, reported only when the evidence favors the suspect over a hypothesized sibling by at least a factor of C (default C = 10) under at least one contamination model, and otherwise set to 1 (log {Lambda} = 0). In simulations based on 1000 Genomes data, {Lambda} retains nearly all power to detect true contributors at mixture proportions as low as 5% while eliminating the false positives produced by model mis-specification, population structure, and by untested relatives. The methods are implemented in the open-source program DNAMIXTURE, providing the forensic and population genetics community a resource for robustly identifying small individual contributions to a DNA mixture.

The Teshik-Tash 1 child whose remains were found in Uzbekistan represents the southeastern-most extent of the known Neandertal range, providing an important link with the better studied Caucasus and Altai Mountain ranges. However, due to poor DNA preservation, studying the genetics of Teshik Tash 1 has remained elusive. Here we present analyses of the nuclear DNA from the Teshik-Tash 1, from extracts that are highly contaminated with present-day human DNA. To achieve this, we developed a new computational method, admixslug, that jointly models contamination and population relationships, in order to infer the relationship of a target individual from which only low-quality nuclear DNA is available, to high-quality archaic human genomes. After validating admixslug, we show that Teshik-Tash 1 is genetically more similar to later Neandertals from Western Eurasia than to older Neandertals from the Altai Mountains. We estimate that Teshik-Tash 1 split from the Western Eurasian lineage between 80,000 and 100,000 years ago. Despite the geographical proximity of Teshik-Tash 1 to the Denisovan range, we find no evidence for Denisovan ancestry in his genome. Our results demonstrate that admixslug enables the study of archaic human specimens in cases where DNA preservation was previously considered too poor for population genetic analyses.

High-throughput amplicon sequencing has transformed microsatellite (STR) genotyping by overcoming many of the limitations of fragment-length analysis, enabling more accurate, cost-effective, and standardized genotyping. Yet, protocols specifically designed for high-throughput sequencing (HTS)-based STR genotyping from low-template and degraded DNA remain scarce, despite the prevalence of these challenging sample types in ecological and conservation contexts. We present a methodology for the de novo development of robust STR multiplex panels together with a laboratory protocol for efficient and reliable STR genotyping by sequencing with low quantity and quality DNA samples. The protocol comprises (i) an automated bioinformatic pipeline to design large sets of short tetranucleotide markers optimized for multiplex amplicon sequencing of degraded and low-template DNA; (ii) guidelines for efficient in vitro optimization of multiplex amplification using directly low quantity/quality template DNA; and (iii) a library preparation procedure that improves detection of low-level allele signal while enabling quality assessment of STR amplicon sequencing under limiting DNA conditions. We demonstrate the approach by developing and validating STR panels for non-invasive genotyping of three large carnivore species: a 44-plex for the grey wolf (Canis lupus), a 41-plex for the Eurasian lynx (Lynx lynx), and a 30-plex for the brown bear (Ursus arctos). Multiplex performance was high, with [&ge;]91% of samples successfully genotyped at [&ge;]50% of loci (allele size range 28-110 bp across panels) and correctly assigned to known individuals, negligible levels of noise in the controls, and high discriminatory power (PIDsibs [&le;]2.4 x 1e-12), also owing to sequence variation among same-length alleles at 15-50% of loci. The approach is broadly applicable to animal and plant species, a wide range of sample types, and large-scale analysis such as genetic monitoring. Our study reinforces the value of STR amplicon sequencing for ecological and conservation applications while highlighting the importance of marker design and laboratory workflows tailored to HTS-based genotyping for accurate and efficient implementation.

Recombinase polymerase amplification (RPA) enables rapid nucleic acid testing in low-resource environments, but poorly characterized byproducts can compromise assay specificity and cause false-positive results. Here, we amplified the thirteen original CODIS core loci and Amelogenin to characterize recurrent RPA artefacts and establish conditions that reduce their formation. First, RPA products were analyzed for two reference samples by Oxford Nanopore Technologies sequencing. This revealed two distinct classes of multimeric products: primer multimers and amplicon multimers, consisting of repeated primer or amplicon sequences, respectively. Individual artefacts contained up to 281 primer copies or 22 amplicon copies, demonstrating the extensive range of these products. Next, we performed an optimization study to evaluate the effects of reaction temperature and reagent concentrations at two representative loci, D3S1358 and D5S818. Among the conditions tested, temperature had the most pronounced effect. Reducing the temperature from 42{degrees}C to 34{degrees}C increased the relative target amplicon fraction from 15% to 83% for D3S1358 and from 84% to 98% for D5S818, while maintaining or increasing absolute target concentration. Lower primer concentrations and higher T4 UvsX concentrations also reduced multimer formation, although lower primer concentrations reduced target yield and caused allelic dropout. Finally, amplification at 34{degrees}C was evaluated across all fourteen loci by sequencing. Relative to 42{degrees}C, the target read fraction increased by more than 5 percentage points for 7/14 loci in one reference sample and 9/14 loci in the other, with the largest improvements at multimer-prone loci. These findings identify multimers as an important class of RPA artefacts and establish reaction temperature and T4 UvsX concentration as promising conditions to improve RPA specificity.

Molecular identification of cetacean bone remains can be limited by DNA degradation and the presence of PCR inhibitors. Here, we present an optimized DNA extraction protocol based on a total demineralization method for environmentally exposed cetacean bones. The protocol uses 100 mg of bone powder, 24 h digestion with EDTA, N-lauroylsarcosine, and proteinase K, followed by a modified silica-column purification. Nine environmentally degraded bone samples representing eight individuals were processed. DNA concentrations ranged from 7.3 to 57.1 ng/uL (mean SD = 25.91- 13.91 ng/uL). The mitochondrial cytochrome b gene was successfully amplified from all samples using conventional PCR, and five samples (55.6%) yielded sequences suitable for downstream analysis. BLASTn identified Balaenoptera physalus as the closest database match for all recovered sequences, and phylogenetic analysis further supported their association with B. physalus reference sequences. These results demonstrate that the proposed protocol provides a practical approach for recovering amplifiable and molecularly informative mitochondrial DNA from environmentally degraded cetacean bone material, facilitating molecular identification from challenging skeletal remains.

BACKGROUND: The protein 4.1a/4.1b ratio is an intrinsic molecular marker of mean red blood cell (RBC) age resulting from progressive deamidation of protein 4.1b during RBC circulation. Despite its potential for estimating mean RBC age from a single blood sample, its application has been limited by labor-intensive RBC membrane preparation, and its interindividual variability has not been characterized in a large human population. METHODS: We developed a low-volume method for direct RBC membrane isolation from whole blood using saponin permeabilization and differential centrifugation without prior RBC washing. Membrane proteins were separated by SDS-PAGE, and protein 4.1a/4.1b ratios were determined by densitometric analysis with Gaussian peak fitting. Assay conditions, sample-volume requirements, membrane protein recovery, and analytical reproducibility were evaluated. The method was subsequently applied to 114 anonymized residual samples from routine diagnostic testing selected for complete blood count parameters within the corresponding laboratory reference intervals. RESULTS: The optimized procedure used 50 uL of whole blood, 0.06% saponin, and centrifugation at 9000 g, although protein 4.1a/4.1b remained measurable from starting volumes as low as 5 uL. Mean within-subject CVs were 3.90% for electrophoretic/densitometric determination and 5.39% for membrane protein recovery; whole-procedure CVs in 3 subjects were 1.40% to 3.50%. In the population analysis, the mean protein 4.1a/4.1b ratio was 1.428 (SD 0.146), with an observed range of 1.052 to1.799 and a central 95% interval of 1.151 to 1.695. Ratios did not differ significantly between females and males (P=0.246) or among females aged 18 to 50 years, females aged >50 years, and males (P=0.151). The ratio showed modest positive correlations with chronological age in females (Spearman p=0.26, P=0.047) and males (p=0.33, P=0.015), while substantial interindividual variability remained across the age range. CONCLUSIONS: Direct isolation of RBC membranes from small volumes of whole blood enables reproducible determination of the protein 4.1a/4.1b ratio using a simplified workflow. Application of the assay to a comparatively large human population revealed substantial interindividual variation in this molecular marker of mean RBC age that was not explained by sex or chronological age alone. The method provides a practical approach for investigating biological variation in mean RBC age and its potential contribution to laboratory measurements influenced by RBC survival.

Age and sex estimation from dental radiographs supports forensic identification and age-dependent legal assessment. Multi-input models may combine global and regional representations, but when these inputs are derived from the same radiograph, they may repeat anatomical information rather than provide complementary signals. We developed HMA-Net, a hierarchical multi-stream anatomical network, together with a task-specific input audit that evaluates whether each candidate representation improves at least one prediction task without materially degrading the other. The model was developed using a retrospective single-centre cohort of 4,293 panoramic radiographs from individuals aged 3-18 years and combined a panoramic-image stream with graph-linked tooth representations. On the held-out test set, the final panoramic-plus-permanent-tooth model achieved a mean absolute age error of 0.51 years and a sex-classification accuracy of 85.2%; 99.4% of age estimates were within 2 years of chronological age. Across three independent training runs, removing the jaw-region stream reduced mean absolute age error from 0.68 +/- 0.01 to 0.52 +/- 0.01 years and increased sex accuracy from 81.3+/- 1.7% to 85.8 +/- 0.8%. Adding 20 deciduous-tooth classes provided no age benefit and reduced sex accuracy by 7.9% relative to the permanent-only representation. The mandibular first molars received the greatest tooth-level attention, and their occlusion impaired both prediction tasks. These findings show that anatomically plausible inputs do not necessarily provide incremental predictive value. Task-specific input auditing can improve joint model performance, reduce input redundancy and preserve anatomically traceable predictions. More broadly, this framework provides a testable approach for selecting correlated inputs in medical-imaging systems in which regional views re-present anatomy already contained in the whole image. Keywords: Forensic odontology; Dental age estimation; Sex classification; Panoramic radiography; Multi-input learning; Anatomical input auditing

To explore adapting qPCR systems for end-point nucleic acid quantification using dyes such as SYTO-9, we quantified serial dilutions of DNA and RNA standards in the range of 0.75 - 200 ng/{micro}l on 384-well qPCR devices. SYTO-9 fluorescence was successfully measured using standard SYBR Green settings. Blank-subtracted relative SYTO-9 signal showed a logarithmic dependence on DNA/RNA concentration (R2 > 0.95). Measurements were highly stable with different incubation times, temperatures of up to 95{degrees}C, and photobleaching. The described approach is a valuable QC option for high-throughput DNA/RNA isolations and could be adapted to additional fluorometric assays beyond nucleic acids.

BackgroundNon-invasive embryo quality assessment is a critical unmet need in assisted reproductive technology (ART). Preimplantation genetic testing for aneuploidy (PGT-A) is effective but requires invasive biopsy that may compromise embryo viability. Metabolomics of spent embryo culture media (SECM) offers a non-invasive alternative, yet analytical challenges--limited sample volume, high salt content, and abundant proteins--have hindered standardization and clinical translation. ResultsWe systematically optimized sample preparation for untargeted LC-MS metabolomics of SECM using human serum as a reference. Optimal conditions were highly matrix-dependent: SECM required 7x volume of 50% acetonitrile for extraction and 40% acetonitrile for reconstitution, whereas serum required 10x volume of 100% methanol and 100% water--reflecting that SECM contains more non-polar species than serum. Applying the optimized workflow to 120 clinical SECM samples (72 euploid, 48 aneuploid), we identified 102 differential metabolites between euploid and aneuploid embryos, with prominent enrichment of lipid pathways (fatty acid metabolism, {beta}-oxidation, sphingolipid metabolism) and involvement of amino acid (methionine, tryptophan) and TCA cycle metabolism. A weighted ensemble machine learning model discriminated aneuploid from euploid embryos with an AUC of 0.977, 100.0% specificity, and 89.6% sensitivity. Among 72 euploid embryos stratified by morphological grading (good, fair, poor), metabolic alterations progressed from mitochondrial energy deficiency (good vs. fair) to broader lipid dysregulation (fair vs. poor), with the ensemble model achieving AUCs of 0.944, 0.889, and 0.943, respectively. ConclusionsThis study establishes a rigorously optimized and validated SECM metabolomics workflow that overcomes key analytical barriers in this challenging matrix. Our findings demonstrate that metabolic signatures--particularly in lipid and energy metabolism--are strongly associated with both embryo ploidy and morphological quality, providing biological insights into the metabolic underpinnings of embryo developmental competence. The high predictive performance of the ensemble model supports the feasibility of non-invasive embryo assessment as a complementary tool to existing methods, with potential to reduce reliance on invasive biopsy in ART. External validation in prospective multi-center cohorts is warranted to further assess clinical utility and generalizability. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/741666v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@1be208aorg.highwire.dtl.DTLVardef@14a61a3org.highwire.dtl.DTLVardef@504e70org.highwire.dtl.DTLVardef@4dc12d_HPS_FORMAT_FIGEXP M_FIG C_FIG

In response to the growing need to recycle E-waste, specifically that of lithium-ion batteries (LIBs), the development of sustainable recycling methodologies will be vital. As one of the most sustainable and low-cost options, biohydrometallurgy (BioHM) uses biological organisms to facilitate the recovery of critical metals from spent LIBs. Despite the advantages of BioHM, its slow kinetics, due to the reliance on the metabolic activity of microorganisms, limit its large-scale application for the closed-loop recycling of LIBs. In this work, we investigate the correlation between the incubation time of Acidithiobacillus ferrooxidans (Atf) and its leaching efficiency of four common elements in LIBs: Li, Ni, Mn, and Co. We assess how specific incubation times along the biological growth curve affect the leaching efficiency of Li[Ni0.6Mn0.2Co0.2]O2 (NMC622), a model electrode material. Our results show that pH alone is not an accurate descriptor of the leaching efficiency of Atf cultures used at different growth stages. The addition of NMC622 during the bacterial lag phase reaches similar or even improved extraction compared to cultures used after reaching the exponential or stationary phases. A simple model of leaching dynamics shows predictions consistent with our experimental observations under the condition that the inhibition of bacterial growth by NMC is not severe. Our findings indicate that early-stage cultures can alleviate the kinetic bottleneck and improve the throughput of recovering critical materials from spent batteries.

Postmortem computed tomography (PMCT) is increasingly used in forensic medicine, yet image interpretation remains largely manual and time-consuming, and supervised deep learning is constrained by the scarcity of annotated forensic datasets. This study investigated whether diffusion-based generative models can detect fatal cerebral haemorrhage on PMCT through reconstruction-based anomaly detection, using solely image-level labels derived from the documented cause of death. Postmortem brain CT examinations acquired at a single forensic institute between 2011 and 2025 were retrospectively analyzed, comprising 265 healthy subjects and 33 cases of fatal intracranial haemorrhage. After automated brain extraction, slice selection and intensity normalization, two diffusion frameworks were trained: an unsupervised denoising diffusion probabilistic model (AnoDDPM) trained on healthy anatomy alone, and a weakly supervised classifier-guided diffusion model exploiting image-level labels. Anomaly scores were derived from the reconstruction error between each slice and its pseudo-healthy reconstruction, and detection was assessed at the image level using 95% bootstrap confidence intervals. AnoDDPM achieved an AUROC of 0.928 (95% CI 0.812-0.989) and an AUPRC of 0.794 (95% CI 0.429-0.946), whereas the classifier-guided model reached an AUROC of 0.991 (95% CI 0.984-0.997) with an AUPRC of 0.960 (95% CI 0.855-0.994). These results demonstrate excellent feasibility of diffusion-based anomaly detection for forensic PMCT and indicate that weak, image-level supervision substantially improves detection, thereby supporting the future development of automated triage tools for postmortem brain imaging.

Formalin-fixed, paraffin-embedded (FFPE) tissues remain an essential resource for molecular studies, yet formalin-induced cytosine deamination introduces characteristic C>T/G>A artifacts that compromise the accuracy of next-generation sequencing (NGS) analyses. Numerous computational methods and enzymatic DNA repair strategies have been proposed to reduce these artifacts, but no systematic comparison across tools and experimental conditions exists. Here, we evaluate the performance of seven computational approaches (SOBDetector, Ideafix, MicroSEC, FFPolish, DeepOmics FFPE/FFPE-PLUS, FFPErase) together with the NEBNext(R) FFPE DNA Repair Mix v2, a multi-enzyme repair system applied during DNA preparation. Using three independent datasets, one based on whole genome sequencing (CGCI-BL) and two on whole exome sequencing (TCGA-PC and SUT-LUAD, the latter containing enzymatically repaired samples), and matched fresh-frozen samples as the gold standard, we assess precision, sensitivity, and artifact reduction efficiency across all methods. We further examine the potential synergy between enzymatic repair and post-sequencing computational filtering. Our results provide practical guidelines for FFPE artifact correction and demonstrate that enzymatic treatment provides the best results, while among the computational methods, FFPErase offers the most robust reduction of cytosine deamination artifacts while maximizing the retention of true somatic variants. KEY MESSAGESO_LIFormalin fixation in FFPE samples introduces artifacts that can significantly affect the accuracy of NGS analyses. C_LIO_LIAmong the evaluated approaches, enzymatic repair using NEBNext(R) FFPE DNA Repair Mix v2 achieves the most effective reduction of sequencing artifacts. C_LIO_LIComputational methods vary in performance, with FFPErase showing the most robust balance between artifact removal and retention of true somatic variants. C_LIO_LICombining enzymatic repair with computational filtering did not lead to consistent improvements in performance across datasets. C_LI

This study aims to quantify the genetic similarity of different species (from fish to humans) to the human reference genome (pp6, Homo sapiens.GRCh38) based on the allele presence/absence patterns of 33 language/cognition related gene SNV loci, identify key breakpoints during evolution, and evaluate the enrichment of language and cognition genes at these breakpoints. We designed a similarity calculation method relying on binary features (four columns for A/T/C/G), adopted five difference/distance measures (Sorensen, Rogers, Nei, Reynolds, and Hellinger), and converted them into similarity values (1/(1+distance)). For each method, samples were independently ranked, the first derivative of similarity was computed, and the top 12 peaks were selected as candidate breakpoints. Results show that the similarity curves from the five methods are highly consistent (correlation coefficients >0.9), with major peaks concentrated at positions 355, 363, 381, 382, 390, 400, etc., where the corresponding samples are predominantly ancient hominins and primates. Furthermore, we defined 13 peak groups (starting positions 355-401). For each peak within a group, pairwise SNV differences between the peak apex sample and its immediate left neighbor were compared, and the intersection F_INTERSECTION (shared differential loci) was obtained. For each F_INTERSECTION, we calculated the proportions of language genes and cognition genes. In addition, we computed the differential sets between adjacent groups' F_INTERSECTION to trace the gradual emergence of new loci. In F_INTERSECTION, language genes accounted for an average of 59.5%, and cognition genes for an average of 62.9%. The proportion of language genes reached a peak at position 383 (61.2%), while cognition genes peaked at position 386 (64.9%). High frequency peak samples include c25, c27, and ja2, suggesting that language cognition genes may have undergone independent intensification during Eurasian evolution. Differential analysis between adjacent F_INTERSECTION revealed a stepwise acquisition of new loci from position 355 to 401, with three bursts of newly added loci along the entire evolutionary axis. This study provides a quantitative framework based on similarity curves, offers a novel molecular perspective for understanding the evolution of language and cognitive abilities, and highlights the potential importance of East Asian archaic hominins in the evolution of language cognition genes.

Summary/AbstractTelomere length has a significant impact on human health. Short telomeres cause age-related diseases, including pulmonary fibrosis, immunodeficiency, and bone marrow failure, while long telomeres predispose to cancer. Given the impact on human health, accurately measuring telomere length is important. A variety of methods have been developed over the past 40 years to measure telomere length. Many of these methods report only on the mean length of all of the telomere in the cell. Here, we describe the Telomere Profiling protocol using Oxford Nanopore Technologies (ONT) based on long read sequencing that can accurately measure chromosome specific telomere length.

During biogeographical ancestry (BGA) analysis, an unknown individual for whom ancestry informative markers (AIMs) were analyzed is often assigned to one of a few reference populations. For some individuals, such an assignment is not meaningful: the two parents of the individual may come from different populations, or the individual may come from a population not included in the reference database. In this study, we examined classification methods in combination with 104 AIMs from the VISAGE Enhanced Tool to provide one of the following three possible outcomes: (i) in-reference (IR), with an assignment to one of the reference populations; (ii) admixed (AD), with parents from two in-reference populations; and (iii) out-of-reference (OR), where the individual's ancestry is not sufficiently represented by the reference populations. We therefore compared seven classifiers in combination with class-specific acceptance thresholds for the OR decision. The best-performing method according to our selection criterion was a naive Bayes classifier over pairs of populations, which we call the recent naive Bayes (RNB) classifier. Populations held out of the reference panel were correctly rejected in $84.9\%$ of cases. We further tested the method on $800$ individuals from seven additional groups not included in the reference panel. Only $29.4\%$ of individuals from four non-admixed populations were rejected, resembling joint ancestry with reference populations. In addition, we investigated the prediction accuracy in a newly collected dataset of 28 individuals with self-reported ancestry by analyzing AIMs using massively parallel sequencing.

Grecia Salentina (GS) is the label assigned to a geographic area in Southern Italy where a Greek dialect has historically been spoken. The origins of this Greek-speaking community, whether dating from ancient or Medieval settlement, are a controversial and essentially unsolved issue. To evaluate which historical-linguistic scenario is best supported on genomic grounds, we used whole genome sequencing of 27 GS natives and 21 controls, embedding them in a 799 modern samples dataset in which Greece and Anatolia were evenly represented, an uncommon feature in the genomic literature on the area. We considered different aspects of the genetic structuring, at different spatial and temporal scales. Analyses also included 4021 ancient samples from the literature. All analyses pointed to the same conclusion: the GS genomic profile displays the same characteristic features of the rest of Southern Italy, with no definite evidence for a single source population from outside Italy. Correspondingly, we detected strong genetic connectivity among GS municipalities and between GS and the rest of Italy. Only a subset of our analyses suggested a slightly increased affinity of GS with Greece, or with the Anatolian peninsula. These results indicate that GS has been all but a genetically closed community, and that the Greek language did not act as a barrier to gene flow. By endorsing a ''transient mobility model'' we support the most recent linguistic hypothesis: the prolonged resilience of the Greek language in GS, maintained in situ and periodically rejuvenated through recurrent external inputs from the Greek and Byzantine worlds.