Predicting eye and hair colour in a Norwegian population using Verogen's ForenSeq™ DNA signature prep kit

Development and validation of YARN: A novel SE-400 MPS kit for East Asian paternal lineage analysis

Y-chromosomal short tandem repeat polymorphisms (Y-STRs) and Y-chromosomal single nucleotide polymorphisms (Y-SNPs) are valuable genetic markers used in paternal lineage identification and population genetics. Currently, there is a lack of an effective panel that integrates Y-STRs and Y-SNPs for studying paternal lineages, particularly in East Asian populations. Hence, we developed a novel Y-chromosomal targeted panel called YARN (Y-chromosome Ancestry and Region Network) based on multiplex PCR and a single-end 400 massive parallel sequencing (MPS) strategy, consisting of 44 patrilineage Y-STRs and 260 evolutionary Y-SNPs. A total of 386 reactions were validated for the effectiveness and applicability of YARN according to SWGDAM validation guidelines, including sensitivity (with a minimum input gDNA of 0.125 ng), mixture identification (ranging from 1:1-1:10), PCR inhibitor testing (using substances such as 50 μM hematin, 100 μM hemoglobin, 100 μM humic acid, and 2.5 mM indigo dye), species specificity (successfully distinguishing humans from other animals), repeatability study (achieved 100% accuracy), and concordance study (with 99.91% accuracy for 1121 Y-STR alleles). Furthermore, we conducted a pilot study using YARN in a cohort of 484 Han Chinese males from Huaiji County, Zhaoqing City, Guangdong, China (GDZQHJ cohort). In this cohort, we identified 52 different Y-haplogroups and 73 different surnames. We found weak to moderate correlations between the Y-haplogroups, Chinese surnames, and geographical locations of the GDZQHJ cohort (with λ values ranging from 0.050 to 0.340). However, when we combined two different categories into a new independent variable, we observed stronger correlations (with λ values ranging from 0.617 to 0.754). Overall, the YARN panel, which combines Y-STR and Y-SNP genetic markers, meets forensic DNA quality assurance guidelines and holds potential for East Asian geographical origin inference and paternal lineage analysis.

An overview of autosomal STRs and identity SNPs in a Norwegian population using massively parallel sequencing

In recent years, probabilistic genotyping software has been adapted for the analysis of massively parallel sequencing (MPS) forensic data. Likelihood ratios (LR) are based on allele frequencies selected from populations of interest. This study provides an outline of sequence-based (SB) allele frequencies for autosomal short tandem repeats (aSTRs) and identity single nucleotide polymorphisms (iSNPs) in 371 individuals from Southern Norway. 27 aSTRs and 94 iSNPs were previously analysed with the ForenSeq™ DNA Signature Prep Kit (Verogen). The number of alleles with frequencies less than 0.05 for sequenced-based alleles was 4.6 times higher than for length-based alleles. Consistent with previous studies, it was observed that sequence-based data (both with and without flanks) exhibited higher allele diversity compared to length-based (LB) data; random match probabilities were lower for SB alleles confirming their advantage to discriminate between individuals. Two alleles in markers D22S1045 and Penta D were observed with SNPs in the 3´ flanking region, which have not been reported before. Also, a novel SNP with a minor allele frequency (MAF) of 0.001, was found in marker TH01. The impact of the sample size on minor allele frequency (MAF) values was studied in 88 iSNPs from Southern Norway (n = 371). The findings were then compared to a larger Norwegian population dataset (n = 15,769). The results showed that the smaller Southern Norway dataset provided similar results, and it was a representative sample. Population structure was analyzed for regions within Southern Norway; FST estimates for aSTR and iSNPs did not indicate any genetic structure. Finally, we investigated the genetic differences between Southern Norway and two other populations: Northern Norway and Denmark. Allele frequencies between these populations were compared, and we found no significant frequency differences (p-values > 0.0001). We also calculated the pairwise FST values per marker and comparisons between Southern and Northern Norway showed small differences. In contrast, the comparisons between Southern Norway and Denmark showed higher FST values for some markers, possibly driven by distinct alleles that were present in only one of the populations. In summary, we propose that allele frequencies from each population considered in this study could be used interchangeably to calculate genotype probabilities.

Biogeographical Ancestry Analyses Using the ForenSeqTM DNA Signature Prep Kit and Multiple Prediction Tools

The inference of biogeographical ancestry (BGA) can assist in police investigations of serious crime cases and help to identify missing people and victims of mass disasters. In this study, we evaluated the typing performance of 56 ancestry-informative SNPs in 177 samples using the ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system. Furthermore, we compared the prediction accuracy of the tools Universal Analysis Software v1.2 (UAS), the FROG-kb, and GenoGeographer when inferring the ancestry of 503 Europeans, 22 non-Europeans, and 5 individuals with co-ancestry. The kit was highly sensitive with complete aiSNP profiles in samples with as low as 250pg input DNA. However, in line with others, we observed low read depth and occasional drop-out in some SNPs. Therefore, we suggest not using less than the recommended 1ng of input DNA. FROG-kb and GenoGeographer accurately predicted both Europeans (99.6% and 91.8% correct, respectively) and non-Europeans (95.4% and 90.9% correct, respectively). The UAS was highly accurate when predicting Europeans (96.0% correct) but performed poorer when predicting non-Europeans (40.9% correct). None of the tools were able to correctly predict individuals with co-ancestry. Our study demonstrates that the use of multiple prediction tools will increase the prediction accuracy of BGA inference in forensic casework.

The eye in forensic practice: In the living

Eye examination plays an important role when living individuals are forensically investigated. The iris colour, retinal scans and other biometric features may be used for identification purposes while visual impairments may have legal implications in employment, driving and accidents. Ocular manifestations provide clues regarding substance abuse, poisoning and toxicity, and evidence of trauma, abuse or disease can be revealed along with psychological traits and lifestyle. Thus, the eye is a valuable tool in forensic investigations of living subjects, providing identifying characteristics along with health information. This review focuses on the medico-legal aspects of the eye's contribution when the living are subjected to forensic examination.

Accuracy of Eye and Hair Color Prediction in Mexican Mestizos from Monterrey City Based on ForenSeqTM DNA Signature Prep

Forensic genomic systems allow simultaneously analyzing identity informative (iiSNPs), ancestry informative (aiSNPs), and phenotype informative (piSNPs) genetic markers. Among these kits, the ForenSeq DNA Signature prep (Verogen) analyzes identity STRs and SNPs as well as 24 piSNPs from the HIrisPlex system to predict the hair and eye color. We report herein these 24 piSNPs in 88 samples from Monterrey City (Northeast, Mexico) based on the ForenSeq DNA Signature prep. Phenotypes were predicted by genotype results with both Universal Analysis Software (UAS) and the web tool of the Erasmus Medical Center (EMC). We observed predominantly brown eyes (96.5%) and black hair (75%) phenotypes, whereas blue eyes, and blond and red hair were not observed. Both UAS and EMC showed high performance in eye color prediction (p ≥ 96.6%), but a lower accuracy was observed for hair color prediction. Overall, UAS hair color predictions showed better performance and robustness than those obtained with the EMC web tool (when hair shade is excluded). Although we employed a threshold (p > 70%), we suggest using the EMC enhanced approach to avoid the exclusion of a high number of samples. Finally, although our results are helpful to employ these genomic tools to predict eye color, caution is suggested for hair color prediction in Latin American (admixed) populations such as those studied herein, principally when no black color is predicted.

Association between Variants in the OCA2-HERC2 Region and Blue Eye Colour in HERC2 rs12913832 AA and AG Individuals

The OCA2-HERC2 region is strongly associated with human pigmentation, especially eye colour. The HERC2 SNP rs12913832 is currently the best-known predictor for blue and brown eye colour. However, in a previous study we found that 43 of 166 Norwegians with the brown eye colour genotype rs12913832:AA or AG, did not have the expected brown eye colour. In this study, we carried out massively parallel sequencing of a ~500 kbp HERC2-OCA2 region in 94 rs12913832:AA and AG Norwegians (43 blue-eyed and 51 brown-eyed) to search for novel blue eye colour variants. The new candidate variants were subsequently typed in a Norwegian biobank population (total n = 519) for population specific association analysis. We identified five new variants, rs74409036:A, rs78544415:T, rs72714116:T, rs191109490:C and rs551217952:C, to be the most promising candidates for explaining blue eye colour in individuals with the rs12913832:AA and AG genotype. Additionally, we confirmed the association of the missense variants rs74653330:T and rs121918166:T with blue eye colour, and observed lighter skin colour in rs74653330:T individuals. In total, 37 (86%) of the 43 blue-eyed rs12913832:AA and AG Norwegians could potentially be explained by these seven variants, and we suggest including them in future prediction models.

Predicting Eye and Hair Color in a Turkish Population Using the HIrisPlex System

Forensic DNA Phenotyping (FDP) can reveal the appearance of an unknown individual by predicting the ancestry, phenotype (i.e., hair, eye, skin color), and age from DNA obtained at the crime scene. The HIrisPlex system has been developed to simultaneously predict eye and hair color. However, the prediction accuracy of the system needs to be assessed for the tested population before implementing FDP in casework. In this study, we evaluated the performance of the HIrisPlex system on 149 individuals from the Turkish population. We applied the single-based extension (SNaPshot chemistry) method and used the HIrisPlex online tool to test the prediction of the eye and hair colors. The accuracy of the HIrisPlex system was assessed through the calculation of the area under the receiver characteristic operating curves (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The results showed that the proposed method successfully predicted the eye and hair color, especially for blue (100%) and brown (95.60%) eye and black (95.23) and brown (98.94) hair colors. As observed in previous studies, the system failed to predict intermediate eye color, representing 25% in our cohort. The majority of incorrect predictions were observed for blond hair color (40.7%). Previous HIrisPlex studies have also noted difficulties with these phenotypes. Our study shows that the HIrisPlex system can be applied to forensic casework in Turkey with careful interpretation of the data, particularly intermediate eye color and blond hair color.

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.