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The ability to predict Externally Visible Characteristics (EVCs) from DNA, also referred to as Forensic DNA Phenotyping (FDP), is an exciting new chapter in forensic genetics holding great promise for tracing unknown individuals who are unidentifiable via standard forensic short tandem repeat (STR) profiling. For the purpose of DNA-based eye colour prediction, we previously developed the IrisPlex system consisting of a multiplex genotyping assay and a prediction model based on genotype and phenotype data from 3804 Dutch Europeans. Recently, we performed a forensic developmental validation study of the highly sensitive IrisPlex assay, which currently represents the only validated tool available for DNA-based prediction of eye colour in forensic applications. In the present study, we validate the IrisPlex prediction model by extending our initially described model towards genotype and phenotype data from multiple European populations. We performed IrisPlex analysis on 3840 individuals from seven sites across Europe as part of the European Eye (EUREYE) study for which DNA and high-resolution eye images were available. The accuracy rate of correctly predicting an individual's eye colour as being blue or brown, above the empirically established probability threshold of 0.7, was on average 94% across all seven European populations, ranging from 91% to 98%, despite the large variation in eye colour frequencies between the populations. The overall prediction accuracies expressed by the area under the receiver characteristic operating curves (AUC) were 0.96 for blue and 0.96 for brown eyes, which is considerably higher than those established before. The IrisPlex prediction model parameters generated from this multi-population European dataset, and thus its prediction capabilities, were highly comparable to those previously established. Therefore, the increased information regarding eye colour phenotype and genotype distributions across Europe, and the system's ability to provide eye colour predictions across Europe accurately, both highlight additional evidence for the utility of the IrisPlex system in forensic casework.
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Forensic DNA Phenotyping (FDP), i.e. the prediction of human externally visible traits from DNA, has become a fast growing subfield within forensic genetics due to the intelligence information it can provide from DNA traces. FDP outcomes can help focus police investigations in search of unknown perpetrators, who are generally unidentifiable with standard DNA profiling. Therefore, we previously developed and forensically validated the IrisPlex DNA test system for eye colour prediction and the HIrisPlex system for combined eye and hair colour prediction from DNA traces. Here we introduce and forensically validate the HIrisPlex-S DNA test system (S for skin) for the simultaneous prediction of eye, hair, and skin colour from trace DNA. This FDP system consists of two SNaPshot-based multiplex assays targeting a total of 41 SNPs via a novel multiplex assay for 17 skin colour predictive SNPs and the previous HIrisPlex assay for 24 eye and hair colour predictive SNPs, 19 of which also contribute to skin colour prediction. The HIrisPlex-S system further comprises three statistical prediction models, the previously developed IrisPlex model for eye colour prediction based on 6 SNPs, the previous HIrisPlex model for hair colour prediction based on 22 SNPs, and the recently introduced HIrisPlex-S model for skin colour prediction based on 36 SNPs. In the forensic developmental validation testing, the novel 17-plex assay performed in full agreement with the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, as previously shown for the 24-plex assay. Sensitivity testing of the 17-plex assay revealed complete SNP profiles from as little as 63 pg of input DNA, equalling the previously demonstrated sensitivity threshold of the 24-plex HIrisPlex assay. Testing of simulated forensic casework samples such as blood, semen, saliva stains, of inhibited DNA samples, of low quantity touch (trace) DNA samples, and of artificially degraded DNA samples as well as concordance testing, demonstrated the robustness, efficiency, and forensic suitability of the new 17-plex assay, as previously shown for the 24-plex assay. Finally, we provide an update to the publically available HIrisPlex website , now allowing the estimation of individual probabilities for 3 eye, 4 hair, and 5 skin colour categories from HIrisPlex-S input genotypes. The HIrisPlex-S DNA test represents the first forensically validated tool for skin colour prediction, and reflects the first forensically validated tool for simultaneous eye, hair and skin colour prediction from DNA.
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Human skin colour is highly heritable and externally visible with relevance in medical, forensic, and anthropological genetics. Although eye and hair colour can already be predicted with high accuracies from small sets of carefully selected DNA markers, knowledge about the genetic predictability of skin colour is limited. Here, we investigate the skin colour predictive value of 77 single-nucleotide polymorphisms (SNPs) from 37 genetic loci previously associated with human pigmentation using 2025 individuals from 31 global populations. We identified a minimal set of 36 highly informative skin colour predictive SNPs and developed a statistical prediction model capable of skin colour prediction on a global scale. Average cross-validated prediction accuracies expressed as area under the receiver-operating characteristic curve (AUC) standard deviation were 0.97 0.02 for Light, 0.83 0.11 for Dark, and 0.96 0.03 for Dark-Black. When using a 5-category, this resulted in 0.74 0.05 for Very Pale, 0.72 0.03 for Pale, 0.73 0.03 for Intermediate, 0.870.1 for Dark, and 0.97 0.03 for Dark-Black. A comparative analysis in 194 independent samples from 17 populations demonstrated that our model outperformed a previously proposed 10-SNP-classifier approach with AUCs rising from 0.79 to 0.82 for White, comparable at the intermediate level of 0.63 and 0.62, respectively, and a large increase from 0.64 to 0.92 for Black. Overall, this study demonstrates that the chosen DNA markers and prediction model, particularly the 5-category level; allow skin colour predictions within and between continental regions for the first time, which will serve as a valuable resource for future applications in forensic and anthropologic genetics.
Predicting phenotypes from genotypes is a component of complex genetics that has etched its way into many disciplines including personalized medicine, forensic genetics, anthropological genetics, and consumer genetics, depending on the particular phenotype that is predicted from DNA information. The ability to predict human phenotypes with genetic markers has been of continual interest and significant progress has been made, not only in these applied disciplines, but also to more fundamental genetics researchers as it paves the way to find out why certain DNA markers are found to be associated with certain phenotypic traits.
Skin coloration, however, is a more difficult physical appearance trait to examine genetically and to elucidate how its associated markers can be ranked for prediction, due to its population specific influence (Jablonski and Chaplin 2000, 2013). The maximal skin colour difference between people from different continents, as a result of environmental adaptation and consequence of the out of Africa migration (Liu et al. 2006), leads to a restriction in gene mapping studies. Genome-wide association studies (GWASs) are typically conducted in genetically homogeneous samples to avoid, as much as possible, the false positives that may be produced due to different genetic background between study samples. Therefore, GWASs on skin colour that are performed within continental groups such as Europeans (Han et al. 2008; Liu et al. 2015; Sulem et al. 2008) or South Asians (Edwards et al. 2010; Stokowski et al. 2007) basically identified a list of SNPs explaining subtle skin colour variation within each continental group, but in principle cannot reveal a complete list of skin colour-associated SNPs. Consequently, a previously described prediction model built on exclusively European subjects using SNPs identified in a European skin colour GWAS (Liu et al. 2015) had no power to predict skin colour differences between non-European continents, such as East Asia, Africa, and Native Americans, where considerable skin colour differences exist (Liu et al. 2015). Conversely, previously described skin colour prediction models developed from multi-ethnic data (Maroas et al. 2014; Valenzuela et al. 2010) had no power to predict skin colour differences within continental groups, such as within Europeans. Noteworthy, a model combining many of these associated SNPs, allowing both DNA-based skin colour prediction within and between continents, has not been described thus far. 152ee80cbc
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