DNA-based eye colour prediction across Europe with the IrisPlex system

Exploring Eye, Hair, and Skin Pigmentation in a Spanish Population: Insights from Hirisplex-S Predictions

BACKGROUND/OBJECTIVES

Understanding and predicting human pigmentation traits is crucial for individual identification. Genome-wide association studies have revealed numerous pigmentation-associated SNPs, indicating genetic overlap among pigmentation traits and offering the potential to develop predictive models without the need for analyzing large numbers of SNPs.

METHODS

In this study, we assessed the performance of the HIrisPlex-S system, which predicts eye, hair, and skin color, on 412 individuals from the Spanish population. Model performance was calculated using metrics including accuracy, area under the curve, sensitivity, specificity, and positive and negative predictive value.

RESULTS

Our results showed high prediction accuracies (70% to 97%) for blue and brown eyes, brown hair, and intermediate skin. However, challenges arose with the remaining categories. The model had difficulty distinguishing between intermediate eye colors and similar shades of hair and exhibited a significant percentage of individuals with incorrectly predicted dark and pale skin, emphasizing the importance of careful interpretation of final predictions. Future studies considering quantitative pigmentation may achieve more accurate predictions by not relying on categories. Furthermore, our findings suggested that not all previously established SNPs showed a significant association with pigmentation in our population. For instance, the number of markers used for eye color prediction could be reduced to four while still maintaining reasonable predictive accuracy within our population.

CONCLUSIONS

Overall, our results suggest that it may be possible to reduce the number of SNPs used in some cases without compromising accuracy. However, further validation in larger and more diverse populations is essential to draw firm conclusions and make broader generalizations.

Life history and ancestry of the late Upper Palaeolithic infant from Grotta delle Mura, Italy

The biological aspects of infancy within late Upper Palaeolithic populations and the role of southern refugia at the end of the Last Glacial Maximum are not yet fully understood. This study presents a multidisciplinary, high temporal resolution investigation of an Upper Palaeolithic infant from Grotta delle Mura (Apulia, southern Italy) combining palaeogenomics, dental palaeohistology, spatially-resolved geochemical analyses, direct radiocarbon dating, and traditional anthropological studies. The skeletal remains of the infant - Le Mura 1 - were directly dated to 17,320-16,910 cal BP. The results portray a biological history of the infant's development, early life, health and death (estimated at ~72 weeks). They identify, several phenotypic traits and a potential congenital disease in the infant, the mother's low mobility during gestation, and a high level of endogamy. Furthermore, the genomic data indicates an early spread of the Villabruna-like components along the Italian peninsula, confirming a population turnover around the time of the Last Glacial Maximum, and highlighting a general reduction in genetic variability from northern to southern Italy. Overall, Le Mura 1 contributes to our better understanding of the early stages of life and the genetic puzzle in the Italian peninsula at the end of the Last Glacial Maximum.

Survival in Patients with Uveal Melanoma Is Linked to Genetic Variation at HERC2 Single Nucleotide Polymorphism rs12913832

PURPOSE

Uveal melanoma (UM) is a rare disease, with the highest incidence in people with fair skin and light eyes. Eye color is largely genetically determined and is defined by a set of single nucleotide polymorphisms (SNPs). We set out to determine whether we could identify a SNP related to prognosis.

DESIGN

We sequenced DNA from peripheral blood mononuclear cells of 392 patients with UM and obtained the genotype of 6 common eye color-related SNPs. Clinical and histopathologic tumor characteristics, tumor chromosome status, and patient survival were compared among patients with different genotypes.

PARTICIPANTS

Three hundred ninety-two patients who underwent enucleation for UM at the Leiden University Medical Center, Leiden, The Netherlands.

METHODS

We isolated DNA from peripheral blood leukocytes of 392 patients with UM and performed sequencing, using 6 eye color SNPs from the HIrisPlex-S assay (Erasmus MC, Walsh lab). The genotypes extracted from the sequencing data were uploaded onto the HIrisPlexwebtool (https://hirisplex.erasmusmc.nl/) for eye color prediction. We tested the association of eye color SNPs with tumor characteristics and chromosome aberrations using Pearson's chi-square test and the Mann-Whitney U test and evaluated survival with Kaplan-Meier curves with the log-rank test and Cox regression.

MAIN OUTCOME MEASURES

Uveal melanoma-related survival.

RESULTS

Of 392 patients with analyzable genotype data, 307 patients (78%) were assigned blue eyes, 74 patients (19%) were assigned brown eyes, and 11 patients (3%) could not be assigned to either blue or brown. Patients with a genetically blue eye color showed worse survival (P = 0.04). This was related to 1 genotype: patients with the G/G genotype of rs12913832 (HERC2), which codes for blue eye color showed a worse prognosis (P = 0.017) and more often had high-risk tumors (monosomy of chromosome 3; P = 0.04) than in patients with an A/G or A/A genotype.

CONCLUSIONS

The G/G genotype of rs12913832 (HERC2), which is related to blue eye color, not only is a genetic factor related to the risk of UM develop, but also is linked to a worse prognosis because of an association with a higher risk of a high-risk UM developing (carrying monosomy of chromosome 3).

FINANCIAL DISCLOSURE(S)

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Predictive accuracy of genetic variants for eye color in a Kazakh population using the IrisPlex system

OBJECTIVE

This study assesses the accuracy of the IrisPlex system, a genetic eye color prediction tool for forensic analysis, in the Kazakh population. The study compares previously published genotypes of 515 Kazakh individuals from varied geographical and ethnohistorical contexts with phenotypic data on their eye color, introduced for the first time in this research.

RESULTS

The IrisPlex panel's effectiveness in predicting eye color in the Kazakh population was validated. It exhibited slightly lower accuracy than in Western European populations but was higher than in Siberian populations. The sensitivity was notably high for brown-eyed individuals (0.99), but further research is needed for blue and intermediate eye colors. This study establishes IrisPlex as a useful predictive tool in the Kazakh population and provides a basis for future investigations into the genetic basis of phenotypic variations in this diverse population.

Phenotype predictions of two-person mixture using single cell analysis

Over a decade after the publication of the first forensic DNA phenotyping (FDP) studies, DNA-based appearance predictions are now becoming a reality in routine crime scene investigations. The significant number of publications dedicated to the subject of FDP clearly demonstrates a sustained interest and a strong need for further method development. However, the implementation of FDP in routine work still encounters obstacles, and one of these challenges is making phenotype predictions from DNA mixtures. In this study, we examined single-cell sequencing as a potential tool to enable reliable phenotyping of contributors within mixtures. Two mock mixtures, each containing two contributors with similar and different physical appearances, were analyzed using two different workflows. In the first workflow, the mixtures were sequenced using the Ion AmpliSeq™ PhenoTrivium Panel, which includes 41 HIrisPlex-S (HPS) markers. Subsequently, the genotypes were analyzed using the HPS Deconvolution Tool to predict the phenotypes of both contributors. The second workflow involved the introduction of single-cell separation and collection using the DEPArray™ PLUS System. Two different PhenoTrivium amplification protocols were tested, and the phenotype predictions from single cells were compared with the results obtained using the HPS Tool. Our results suggest that the approach presented here allows for the obtainment of nearly complete HIrisPlex-S profiles with accurate genotypes and reliable phenotype predictions from single cells. This method proves successful in deconvoluting mixtures submitted to forensic DNA phenotyping.

Worldwide Incidence of Ocular Melanoma and Correlation With Pigmentation-Related Risk Factors

Purpose

The worldwide incidence of ocular melanoma (OM), uveal melanoma (UM), and conjunctival melanoma has last been reported on 15 years ago. Recently, light iris color and four specific single-nucleotide-polymorphisms (SNPs) have been identified as a UM-risk factor. Furthermore, six iris color predicting SNPs have been discovered (IrisPlex). Interestingly, two of these (rs129138329 and rs12203592) are also UM-risk factors. We collected worldwide incidence data of OM and investigated its correlations with iris color, IrisPlex SNPs, and UM-risk SNPs.

Methods

Cases of OM, as defined by the International Classification of Diseases Oncology C69 (eye), 8720/3 to 8790/3 (malignant melanoma), and 8000 to 8005 (malignant neoplasm), between 1988 and 2012, were extracted from the Cancer Incidence in Five Continents. Incidence rates were age-standardized and their trends were analyzed with joinpoint regression and age period cohort modeling. Frequencies for each country of iris color, IrisPlex SNPs, and UM-risk SNPs were collected from the literature.

Results

Incidence rates were generally ≥8.0 cases per million person-years in Northern Europe, Western Europe, and Oceania; 2.0 to 7.9 in North America, Eastern Europe, and Southern Europe; and <2.0 in South America, Asia, and Africa. OM incidence correlated with latitude (r = 0.77, P ≤ 0.001) and is expressed as a north-to-south decreasing gradient in Europe. SNP rs12913832 correlated with OM incidence (r = 0.83, P ≤ 0.001), blue iris color (r = 0.56, P ≤ 0.05), green iris color (r = 0.51, P ≤ 0.05), and brown iris color (r = -0.64, P ≤ 0.01). Trends were stable for most countries (28/35).

Conclusions

OM incidence is highest in populations of European ancestry and lowest in populations of Asian and African ancestry. Overall, trends are stable, and the spatial correlation among OM incidence, iris color, and rs12913832 may support the role of pigmentation-related risk factors in OM development.

Forensic DNA Phenotyping: Genes and Genetic Variants for Eye Color Prediction

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.

Phenotypic Classification of Eye Colour and Developmental Validation of the Irisplex System on Population Living in Malakand Division, Pakistan

The core objective of forensic DNA typing is developing DNA profiles from biological evidence for personal identification. The present study was designed to check the validation of the IrisPlex system and the Prevalence of eye colour in the Pakhtoon population residing within the Malakand Division.

METHODS

Eye colour digital photographs and buccal swab samples of 893 individuals of different age groups were collected. Multiplexed SNaPshot single base extension chemistry was used, and the genotypic results were analysed. Snapshot data were used for eye colour prediction through the IrisPlex and FROG-kb tool.

RESULTS

The results of the present study found brown eye colour to be the most prevalent eye colour in comparison to intermediate and blue coloured. Overall, individuals with brown-coloured eyes possess CT (46.84%) and TT (53.16%) genotypes. Blue eye-coloured individuals are solely of the CC genotype, while individuals of intermediate eye colour carry CT (45.15%) and CC (53.85%) genotypes in rs12913832 SNP in the HERC2 gene. It was also revealed that brown-coloured eyes individuals were dominant among all age groups followed by intermediate and blue. Statistical analysis between particular variables and eye colour showed a significant p-value (<0.05) for rs16891982 SNP in SLC45A2 gene, rs12913832 SNP in HERC2 gene, rs1393350 SNP in SLC45A2, districts and gender. The rest of the SNPs were non-significant with eye colour, respectively. The rs12896399 SNP and SNP rs1800407 were found significant with rs16891982 SNP. The result also demonstrated that the study group differs from the world population based on eye colour. The two eye colour prediction results were compared, and it was discovered that IrisPlex and FROG-Kb had similar higher prediction ratios for Brown and Blue eye colour.

CONCLUSIONS

The results of the current study revealed brown eye colour to be the most prevalent amongst members of the local population of Pakhtoon ethnicity in the Malakand Division of northern Pakistan. A set of contemporary human DNA samples with known phenotypes are used in this research to evaluate the custom panel's prediction accuracy. With the aid of this forensic test, DNA typing can be supplemented with details about the appearance of the person from whom the sample was taken in cases involving missing persons, ancient human remains, and trace samples. This study may be helpful for future population genetics and forensics studies.

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.

A global snapshot of current opinions of next-generation sequencing technologies usage in forensics

The future of forensic DNA testing is being shaped by the research and usage of next-generation systems, which have increased the multiplexing capabilities of the field and the type and amount of genetic data that can be utilized for investigations. The NGS adoption for casework has been slow, albeit the plethora of data that has been published. This study evaluated the current opinions on sequencing in forensics. A 20-question online-survey focusing on NGS knowledge, training, and usage was distributed to 6001 forensic DNA researchers and practitioners worldwide. A total of 367 responses were obtained from all continents (North/South America (69.8%), Europe (21.2%), Asia (5.5%), Oceania (2.5%), and Africa (1%)). The respondents consisted of 50% practitioners, 31% researchers, and 19% both. Of these, 38% already own a next-gen sequencing instrument, and 13% are planning to purchase one. Overall, there exists an extensive knowledge on next-gen sequencing within the forensic community, including among laboratories that have not yet implemented this high-throughput technology in their workflows. Current usage focuses primarily on SNP analysis for investigative leads and mitochondrial DNA analysis while future applications included both STR and SNP testing applied to general casework. The major overall concerns respondents have for implementing a sequencing instrument include limited funding, staffing, lack of time, and the cost-effectiveness of providing this service. Specific technical concerns that the respondents had are the lack of training, statistical applications, bioinformatics support, and of rigorous guidelines and recommendations. Most of the respondents do believe there will be a technology shift from using CE only to the use of NGS on casework in 5-10 years. In addition, around 66% of respondents believe that it is moderately to very likely that the court will accept sequencing analysis. Sixteen percent fell in the middle, and the remaining 15% believe it is more unlikely, with 3% of respondents believing it is very unlikely. In conclusion, this work outlines current analytical challenges experienced by the global forensic DNA community and addresses different strategies for the implementation of next-gen sequencing technologies in casework.

Human profiling from STR and SNP analysis of tropical bed bug, Cimex hemipterus, for forensic science

Tropical bed bugs, Cimex hemipterus, which commonly feeds on human blood, may be useful in forensic applications. However, unlike the common bed bug, Cimex lectularius, there is no information regarding tropical bed bug, C. hemipterus, being studied for its applications in forensics. Thus, in this study, lab-reared post-feeding tropical bed bugs were subjected to Short Tandem Repeat (STR) and Single Nucleotide Polymorphism (SNP) analyses to establish the usage of tropical bed bugs in forensics. Several post-feeding times (0, 5, 14, 30, and 45 days) were tested to determine when a complete human DNA profile could still be obtained after the bugs had taken the blood meal. The results showed that complete STR and SNP profiles could only be obtained from the D0 sample. The profile completeness decreased over time, and partial STR and SNP profiles could be obtained up to 45 days post-blood meal. The generated SNP profiles, complete or partial, were also viable for HIrisPlex-S phenotype prediction. In addition, field-collected bed bugs were also used to examine the viability of the tested STR markers, and the STR markers detected mixed profiles. The findings of this study established that the post-blood meal of tropical bed bugs is a suitable source of human DNA for forensic STR and SNP profiling. Human DNA recovered from bed bugs can be used to identify spatial and temporal relations of events.

Advancement in Human Face Prediction Using DNA

The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.

Consistency of Eye Coloration Across Different Relationship Partners

Studies have indicated that people are attracted to partners who resemble themselves or their parents, in terms of physical traits including eye color. We might anticipate this inclination to be relatively stable, giving rise to a sequential selection of similar partners who then represent an individual's "type". We tested this idea by examining whether people's sequential partners resembled each other at the level of eye color. We gathered details of the eye colors of the partners of participants (N = 579) across their adult romantic history (N = 3250 relationships), in three samples, comprising two samples which made use of self-reports from predominantly UK-based participants, and one which made use of publicly available information about celebrity relationship histories. Recorded partner eye colors comprised black (N = 39 partners), dark brown (N = 884), light brown (N = 393), hazel (N = 224), blue (N = 936), blue green (N = 245), grey (N = 34), and green (N = 229). We calculated the proportion of identical eye colors within each participant's relationship history, and compared that to 100,000 random permutations of our dataset, using t-tests to investigate if the eye color of partners across an individual's relationship history was biased relative to chance (i.e., if there was greater consistency, represented by higher calculated proportions of identical eye colors, in the original dataset than in the permutations). To account for possible eye color reporting errors and ethnic group matching, we ran the analyses restricted to White participants and to high-confidence eye color data; we then ran the analyses again in relation to the complete dataset. We found some limited evidence for some consistency of eye color across people's relationship histories in some of the samples only when using the complete dataset. We discuss the issues of small effect sizes, partner-report bias, and ethnic group matching in investigating partner consistency across time.

Applicability of the IrisPlex system for eye color prediction in an admixed population from Argentina

Eye color prediction based on an individual's genetic information is of interest in the field of forensic genetics. In recent years, researchers have studied different genes and markers associated with this externally visible characteristic and have developed methods for its prediction. The IrisPlex represents a validated tool for homogeneous populations, though its applicability in populations of mixed ancestry is limited, mainly regarding the prediction of intermediate eye colors. With the aim of validating the applicability of this system in an admixed population from Argentina (n = 302), we analyzed the six single nucleotide variants used in that multiplex for eye color and four additional SNPs, and evaluated its prediction ability. We also performed a genotype-phenotype association analysis. This system proved to be useful when dealing with the extreme ends of the eye color spectrum (blue and brown) but presented difficulties in determining the intermediate phenotypes (green), which were found in a large proportion of our population. We concluded that these genetic tools should be used with caution in admixed populations and that more studies are required in order to improve the prediction of intermediate phenotypes.

Ocular phenotype related SNP analysis in Southern Han Chinese population from Guangdong province

Ocular phenotype is recognizable among Asians, including eyelid fold, fissure inclination, and canthal index. Here we screened 27 facial phenotype-associated SNPs and reported a preliminary study in 246 Chinese individuals of Han origin in Guangdong province. Results showed that rs17760296 could explain 6.2% of the eyelid fold variation and double eyelids were more likely to appear when one's genotype was TT. With respect to the canthal index, rs4791774 and rs642961 were significantly associated with it. However, no individual SNP was associated with fissure inclination. We further constructed two models to predict eyelid fold and canthal index and evaluated them with receiver operating characteristic (ROC) curves and support vector machine (SVM) regression, respectively. The models showed a moderate-to-high predictive capacity (AUC = 0.75, sensitivity = 76%, and specificity = 72%) for the eyelid fold while a mild performance (R² = 0.1074, MSE = 0.0005, P-value = 0.024) for the canthal index. In conclusion, our study indicates that rs17760296 could be selected into the facial phenotype prediction system for the Southern Han Chinese population. More SNPs are encouraged to improve the prediction accuracy of the canthal index besides rs4791774 and rs642961.

Investigating the genetic architecture of eye colour in a Canadian cohort

Eye color is highly variable in populations with European ancestry, ranging from low to high quantities of melanin in the iris. Polymorphisms in the HERC2/OCA2 locus have the largest effect on eye color in these populations, although other genomic regions also influence eye color. We performed genome-wide association studies of eye color in a Canadian cohort of European ancestry (N = 5,641) and investigated candidate causal variants. We uncovered several candidate causal signals in the HERC2/OCA2 region, whereas other loci likely harbor a single causal signal. We observed colocalization of eye color signals with the expression or methylation profiles of cultured primary melanocytes. Genetic correlations of eye and hair color suggest high genome-wide pleiotropy, but locus-level differences in the genetic architecture of both traits. Overall, we provide a better picture of the polymorphisms underpinning eye color variation, which may be a consequence of specific molecular processes in the iris melanocytes.

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Genome-wide association studies of eye color in 5,641 participants

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Multiple independent candidate causal variants were identified across HERC2/OCA2

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Single candidate causal variants observed on or near IRF4, SLC24A4, TYR, and TYRP1

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Colocalization of eye color signals with expression and methylation profiles

Unveiling forensically relevant biogeographic, phenotype and Y-chromosome SNP variation in Pakistani ethnic groups using a customized hybridisation enrichment forensic intelligence panel

Massively parallel sequencing following hybridisation enrichment provides new opportunities to obtain genetic data for various types of forensic testing and has proven successful on modern as well as degraded and ancient DNA. A customisable forensic intelligence panel that targeted 124 SNP markers (67 ancestry informative markers, 23 phenotype markers from the HIrisplex panel, and 35 Y-chromosome SNPs) was used to examine biogeographic ancestry, phenotype and sex and Y-lineage in samples from different ethnic populations of Pakistan including Pothwari, Gilgit, Baloach, Pathan, Kashmiri and Siraiki. Targeted sequencing and computational data analysis pipeline allowed filtering of variants across the targeted loci. Study samples showed an admixture between East Asian and European ancestry. Eye colour was predicted accurately based on the highest p-value giving overall prediction accuracy of 92.8%. Predictions were consistent with reported hair colour for all samples, using the combined highest p-value approach and step-wise model incorporating probability thresholds for light or dark shade. Y-SNPs were successfully recovered only from male samples which indicates the ability of this method to identify biological sex and allow inference of Y-haplogroup. Our results demonstrate practicality of using hybridisation enrichment and MPS to aid in human intelligence gathering and will open many insights into forensic research in South Asia.

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

Prediction of eye and hair colour from DNA can be an important investigative tool in forensic cases if conventional DNA profiling fails to match DNA from any known suspects or cannot obtain a hit in a DNA database. The HIrisPlex model for simultaneous eye and hair colour predictions was developed for forensic usage. To genotype a DNA sample, massively parallel sequencing (MPS) has brought new possibilities to the analysis of forensic DNA samples. As part of an in-house validation, this study presents the genotyping and predictive performance of the HIrisPlex SNPs in a Norwegian study population, using Verogen's ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system and the HIrisPlex webtool. DNA-profiles were successfully typed with DNA input down to 125 pg. In samples with DNA input < 125 pg, false homozygotes were observed with as many as 92 reads. Prediction accuracies in terms of AUC were high for red (0.97) and black (0.93) hair colours, as well as blue (0.85) and brown (0.94) eye colours. The AUCs for blond (0.72) and brown (0.70) hair colour were considerably lower. None of the individuals was predicted to have intermediate eye colour. Therefore, the error rates of the overall eye colour predictions were 37% with no predictive probability threshold (pmax) and 26% with a probability threshold of 0.7. We also observed that more than half of the incorrect predictions were for individuals carrying the rs12913832 GG genotype. For hair colour, 65% of the individuals were correctly predicted when using the highest probability category approach. The main error was observed for individuals with brown hair colour that were predicted to have blond hair. Utilising the prediction guide approach increased the correct predictions to 75%. Assessment of phenotype-genotype associations of eye colours using a quantitative eye colour score (PIE-score), revealed that rs12913832 AA individuals of Norwegian descent had statistically significantly higher PIE-score (less brown eye colour) than individuals of non-northern European descent. To our knowledge, this has not been reported in other studies. Our study suggests that careful assessment of the target population prior to the implementation of forensic DNA phenotyping to case work is beneficial.

Reliability of phenotype estimation and extended classification of ancestry using decedent samples

The Illumina® MiSeq FGx™, in conjunction with the ForenSeq™ DNA Signature Prep kit, produces genotypes of the CODIS-required short tandem repeats and provides phenotype and biogeographical ancestry estimations via phenotype-informative and ancestry-informative markers, respectively. Although both markers have been validated for use in forensic biology, there is little data to determine the practical utility of these estimations to assist in identifying missing persons using decedent casework samples. The accuracy and utility of phenotypic and ancestral estimations were investigated for 300 samples received by the Los Angeles County Department of Medical Examiner-Coroner. piSNP genotypes were translated into hair and eye colors using the Forenseq™ Universal Analysis Software (UAS) on the MiSeq FGx™ and the HIrisPlex System, and statistical accuracy was evaluated in context with the reported decedent characteristics. Similarly, estimates of each decedent's biogeographical ancestry were compared to assess the efficacy of these markers to predict ancestry correctly. The average UAS and the HIrisPlex system prediction accuracy for brown and blue eyes were 95.3% and 96.2%, respectively. Intermediate eye color could not be predicted with high accuracy using either system. Other than the black hair phenotype reporting an accuracy that exceeded 90% using either system, hair color was also too variable to be predicted with high accuracy. The FROG-kb database distinguishes decedents adequately beyond the Asian, African, European, and Admixed American global ancestries provided by the MiSeq FGx™ UAS PCA plots. FROG-kb correctly identified Middle Eastern, Pacific Islander, Latin American, or Jewish ancestries with accuracies of 70.0%, 81.8%, 73.8%, and 86.7%, respectively.

Searching for improvements in predicting human eye colour from DNA

Increasing understanding of human genome variability allows for better use of the predictive potential of DNA. An obvious direct application is the prediction of the physical phenotypes. Significant success has been achieved, especially in predicting pigmentation characteristics, but the inference of some phenotypes is still challenging. In search of further improvements in predicting human eye colour, we conducted whole-exome (enriched in regulome) sequencing of 150 Polish samples to discover new markers. For this, we adopted quantitative characterization of eye colour phenotypes using high-resolution photographic images of the iris in combination with DIAT software analysis. An independent set of 849 samples was used for subsequent predictive modelling. Newly identified candidates and 114 additional literature-based selected SNPs, previously associated with pigmentation, and advanced machine learning algorithms were used. Whole-exome sequencing analysis found 27 previously unreported candidate SNP markers for eye colour. The highest overall prediction accuracies were achieved with LASSO-regularized and BIC-based selected regression models. A new candidate variant, rs2253104, located in the ARFIP2 gene and identified with the HyperLasso method, revealed predictive potential and was included in the best-performing regression models. Advanced machine learning approaches showed a significant increase in sensitivity of intermediate eye colour prediction (up to 39%) compared to 0% obtained for the original IrisPlex model. We identified a new potential predictor of eye colour and evaluated several widely used advanced machine learning algorithms in predictive analysis of this trait. Our results provide useful hints for developing future predictive models for eye colour in forensic and anthropological studies.

Investigative DNA analysis of two-person mixed crime scene trace in a murder case

It has been advocated before that appearance prediction of unknown suspects from crime scene DNA, in the context of Forensic DNA Phenotyping (FDP), is mostly suitable for single source DNA samples, whereas FDP from DNA mixtures to which more than one person contributed, is viewed challenging. With this report on a murder case, we practically demonstrate the feasibility of appearance DNA prediction of an unknown suspect from a mixed crime scene trace, to which the unknown suspect and the known victim had contributed. From this two-person DNA mixture, we successfully predicted eye, hair and skin color of the unknown suspect with the HIrisPlex-S system by applying targeted massively parallel sequencing (MPS). We argue that at least three factors benefit appearance DNA prediction of unknown suspects from mixed crime scene traces, which were met in this murder case: i) SNP genotype knowledge from reference DNA analysis for one of the two persons in the mixture (here the known victim), ii) about equal DNA contributions by both donors to the mixed crime scene stain, and iii) the use of MPS allowing quantitative SNP analysis. Moreover, we show that additionally analyzing animal DNA in this mixed crime scene trace provides further investigative information. We envision that the investigative DNA strategy that we applied here for analyzing a two-person mixed crime scene trace in a murder case, will be applied in the future to more criminal cases with two-person DNA mixtures, for instance sexual assault cases.

How a Paleogenomic Approach Can Provide Details on Bioarchaeological Reconstruction: A Case Study from the Globular Amphorae Culture

Ancient human remains have the potential to explain a great deal about the prehistory of humankind. Due to recent technological and bioinformatics advances, their study, at the palaeogenomic level, can provide important information about population dynamics, culture changes, and the lifestyles of our ancestors. In this study, mitochondrial and nuclear genome data obtained from human bone remains associated with the Neolithic Globular Amphorae culture, which were recovered in the Megalithic barrow of Kierzkowo (Poland), were reanalysed to gain insight into the social organisation and use of the archaeological site and to provide information at the individual level. We were able to successfully estimate the minimum number of individuals, sex, kin relationships, and phenotypic traits of the buried individuals, despite the low level of preservation of the bone samples and the intricate taphonomic conditions. In addition, the evaluation of damage patterns allowed us to highlight the presence of “intruders”—that is, of more recent skeletal remains that did not belong to the original burial. Due to its characteristics, the study of the Kierzkowo barrow represented a challenge for the reconstruction of the biological profile of the human community who exploited it and an excellent example of the contribution that ancient genomic analysis can provide to archaeological reconstruction.

Prediction of Eye Colour in Scandinavians Using the EyeColour 11 (EC11) SNP Set

Description of a perpetrator's eye colour can be an important investigative lead in a forensic case with no apparent suspects. Herein, we present 11 SNPs (Eye Colour 11-EC11) that are important for eye colour prediction and eye colour prediction models for a two-category reporting system (blue and brown) and a three-category system (blue, intermediate, and brown). The EC11 SNPs were carefully selected from 44 pigmentary variants in seven genes previously found to be associated with eye colours in 757 Europeans (Danes, Swedes, and Italians). Mathematical models using three different reporting systems: a quantitative system (PIE-score), a two-category system (blue and brown), and a three-category system (blue, intermediate, brown) were used to rank the variants. SNPs with a sufficient mean variable importance (above 0.3%) were selected for EC11. Eye colour prediction models using the EC11 SNPs were developed using leave-one-out cross-validation (LOOCV) in an independent data set of 523 Norwegian individuals. Performance of the EC11 models for the two- and three-category system was compared with models based on the IrisPlex SNPs and the most important eye colour locus, rs12913832. We also compared model performances with the IrisPlex online tool (IrisPlex Web). The EC11 eye colour prediction models performed slightly better than the IrisPlex and rs12913832 models in all reporting systems and better than the IrisPlex Web in the three-category system. Three important points to consider prior to the implementation of eye colour prediction in a forensic genetic setting are discussed: (1) the reference population, (2) the SNP set, and (3) the reporting strategy.

Validation of the Verogen ForenSeq™ DNA Signature Prep kit/Primer Mix B for phenotypic and biogeographical ancestry predictions using the Micro MiSeq® Flow Cells

In anticipation of offering phenotypic and biogeographical ancestry predictions to help resolve cases, the Verogen ForenSeq™ DNA Signature Prep kit/Primer Mix B was evaluated in the context of Micro MiSeq® Flow Cells. These flow cells were determined as the best format for a quick turnaround time response and cost effective approach compared to standard flow cells. The phenotype informative SNPs (piSNPs) and ancestry informative SNPs (aiSNPs) were thoroughly examined through sensitivity, reproducibility and repeatability, concordance, robustness (mock casework) and low level DNA mixture studies purposely selecting individuals with different phenotypes (hair and eye color) when possible and different biogeographical ancestry. SNP locus-specific interpretation thresholds were established for the Universal Analysis Software (UAS) based on surviving alleles and SNP predictor rank to minimize false homozygous genotypes and maximize the information that can be derived from an unknown sample. Dropin alleles' intensity determined an appropriate threshold to minimize false heterozygous SNP genotypes. The selection of inappropriate interpretation thresholds was shown to have major consequences on phenotypic predictions. A 3.2% and 4.8% minor DNA component contribution to a DNA mixture had no impact on ancestry predictions whereas a 9.1% contribution did. The multi-locus SNP genotypes generated using the ForenSeq™ DNA Signature Prep kit/Primer Mix B were shown to be reliable, reproducible, concordant and resulted in predictions that were also reliable, reproducible and concordant based on the limited number of donors (N = 19) used in this study.

DNA-based eyelid trait prediction in Chinese Han population

The eyelid folding represents one of the most distinguishing features of East Asian faces, involving the absence or presence of the eyelid crease, i.e., single vs. double eyelid. Recently, a genome-wide association study (GWAS) identified two SNPs (rs12570134 and rs1415425) showing genome-wide significant association with the double eyelid phenotype in Japanese. Here we report a confirmatory study in 697 Chinese individuals of exclusively Han origin. Only rs1415425 was statistically significant (P-value = 0.011), and the allele effect was on the same direction with that reported in Japanese. This SNP combined with gender and age explained 10.0% of the total variation in eyelid folding. DNA-based prediction model for the eyelid trait was developed and evaluated using logistic regression. The model showed mild to moderate predictive capacity (AUC = 0.69, sensitivity = 63%, and specificity = 70%). We further selected six additional SNPs by massive parallel sequencing of 19 candidate genes in 24 samples, and one SNP rs2761882 was statistically significant (P-value = 0.027). All predictors including these two SNPs (rs1415425 and rs2761882), gender, and age explained 11.2% of the total variation. The combined prediction model obtained an improved predictive capacity (AUC = 0.72, sensitivity = 62%, and specificity = 66%). Our study thus provided a confirmation of previous GWAS findings and a DNA-based prediction of the eyelid trait in Chinese Han individuals. This model may add value to forensic DNA phenotyping applications considering gender and age can be separately inferred from genetic and epigenetic markers. To further improve the prediction accuracy, future studies should focus on identifying more informative SNPs by large GWASs in East Asian populations.

Eye-color and Type-2 diabetes phenotype prediction from genotype data using deep learning methods

Background

Genotype–phenotype predictions are of great importance in genetics. These predictions can help to find genetic mutations causing variations in human beings. There are many approaches for finding the association which can be broadly categorized into two classes, statistical techniques, and machine learning. Statistical techniques are good for finding the actual SNPs causing variation where Machine Learning techniques are good where we just want to classify the people into different categories. In this article, we examined the Eye-color and Type-2 diabetes phenotype. The proposed technique is a hybrid approach consisting of some parts from statistical techniques and remaining from Machine learning.

Results

The main dataset for Eye-color phenotype consists of 806 people. 404 people have Blue-Green eyes where 402 people have Brown eyes. After preprocessing we generated 8 different datasets, containing different numbers of SNPs, using the mutation difference and thresholding at individual SNP. We calculated three types of mutation at each SNP no mutation, partial mutation, and full mutation. After that data is transformed for machine learning algorithms. We used about 9 classifiers, RandomForest, Extreme Gradient boosting, ANN, LSTM, GRU, BILSTM, 1DCNN, ensembles of ANN, and ensembles of LSTM which gave the best accuracy of 0.91, 0.9286, 0.945, 0.94, 0.94, 0.92, 0.95, and 0.96% respectively. Stacked ensembles of LSTM outperformed other algorithms for 1560 SNPs with an overall accuracy of 0.96, AUC = 0.98 for brown eyes, and AUC = 0.97 for Blue-Green eyes. The main dataset for Type-2 diabetes consists of 107 people where 30 people are classified as cases and 74 people as controls. We used different linear threshold to find the optimal number of SNPs for classification. The final model gave an accuracy of 0.97%.

Conclusion

Genotype–phenotype predictions are very useful especially in forensic. These predictions can help to identify SNP variant association with traits and diseases. Given more datasets, machine learning model predictions can be increased. Moreover, the non-linearity in the Machine learning model and the combination of SNPs Mutations while training the model increases the prediction. We considered binary classification problems but the proposed approach can be extended to multi-class classification.

Prediction of eye, hair and skin colour in Latin Americans

Here we evaluate the accuracy of prediction for eye, hair and skin pigmentation in a dataset of > 6500 individuals from Mexico, Colombia, Peru, Chile and Brazil (including genome-wide SNP data and quantitative/categorical pigmentation phenotypes - the CANDELA dataset CAN). We evaluated accuracy in relation to different analytical methods and various phenotypic predictors. As expected from statistical principles, we observe that quantitative traits are more sensitive to changes in the prediction models than categorical traits. We find that Random Forest or Linear Regression are generally the best performing methods. We also compare the prediction accuracy of SNP sets defined in the CAN dataset (including 56, 101 and 120 SNPs for eye, hair and skin colour prediction, respectively) to the well-established HIrisPlex-S SNP set (including 6, 22 and 36 SNPs for eye, hair and skin colour prediction respectively). When training prediction models on the CAN data, we observe remarkably similar performances for HIrisPlex-S and the larger CAN SNP sets for the prediction of hair (categorical) and eye (both categorical and quantitative), while the CAN sets outperform HIrisPlex-S for quantitative, but not for categorical skin pigmentation prediction. The performance of HIrisPlex-S, when models are trained in a world-wide sample (although consisting of 80% Europeans, https://hirisplex.erasmusmc.nl), is lower relative to training in the CAN data (particularly for hair and skin colour). Altogether, our observations are consistent with common variation of eye and hair colour having a relatively simple genetic architecture, which is well captured by HIrisPlex-S, even in admixed Latin Americans (with partial European ancestry). By contrast, since skin pigmentation is a more polygenic trait, accuracy is more sensitive to prediction SNP set size, although here this effect was only apparent for a quantitative measure of skin pigmentation. Our results support the use of HIrisPlex-S in the prediction of categorical pigmentation traits for forensic purposes in Latin America, while illustrating the impact of training datasets on its accuracy.

Evaluation of supervised machine-learning methods for predicting appearance traits from DNA

The prediction of human externally visible characteristics (EVCs) based solely on DNA information has become an established approach in forensic and anthropological genetics in recent years. While for a large set of EVCs, predictive models have already been established using multinomial logistic regression (MLR), the prediction performances of other possible classification methods have not been thoroughly investigated thus far. Motivated by the question to identify a potential classifier that outperforms these specific trait models, we conducted a systematic comparison between the widely used MLR and three popular machine learning (ML) classifiers, namely support vector machines (SVM), random forest (RF) and artificial neural networks (ANN), that have shown good performance outside EVC prediction. As examples, we used eye, hair and skin color categories as phenotypes and genotypes based on the previously established IrisPlex, HIrisPlex, and HIrisPlex-S DNA markers. We compared and assessed the performances of each of the four methods, complemented by detailed hyperparameter tuning that was applied to some of the methods in order to maximize their performance. Overall, we observed that all four classification methods showed rather similar performance, with no method being substantially superior to the others for any of the traits, although performances varied slightly across the different traits and more so across the trait categories. Hence, based on our findings, none of the ML methods applied here provide any advantage on appearance prediction, at least when it comes to the categorical pigmentation traits and the selected DNA markers used here.

From Identification to Intelligence: An Assessment of the Suitability of Forensic DNA Phenotyping Service Providers for Use in Australian Law Enforcement Casework

Forensic DNA Phenotyping (FDP) is an established but evolving field of DNA testing. It provides intelligence regarding the appearance (externally visible characteristics), biogeographical ancestry and age of an unknown donor and, although not necessarily a requirement for its casework application, has been previously used as a method of last resort in New South Wales (NSW) Police Force investigations. FDP can further assist law enforcement agencies by re-prioritising an existing pool of suspects or generating a new pool of suspects. In recent years, this capability has become ubiquitous with a wide range of service providers offering their expertise to law enforcement and the public. With the increase in the number of providers offering FDP and its potential to direct and target law enforcement resources, a thorough assessment of the applicability of these services was undertaken. Six service providers of FDP were assessed for suitability for NSW Police Force casework based on prediction accuracy, clarity of reporting, limitations of testing, cost and turnaround times. From these assessment criteria, a service provider for the prediction of biogeographical ancestry, hair and eye colour was deemed suitable for use in NSW Police Force casework. Importantly, the study highlighted the need for standardisation of terminology and reporting in this evolving field, and the requirement for interpretation by biologists with specialist expertise to translate the scientific data to intelligence for police investigators.

Evaluation of the Ion AmpliSeq™ PhenoTrivium Panel: MPS-Based Assay for Ancestry and Phenotype Predictions Challenged by Casework Samples

As the field of forensic DNA analysis has started to transition from genetics to genomics, new methods to aid in crime scene investigations have arisen. The development of informative single nucleotide polymorphism (SNP) markers has led the forensic community to question if DNA can be a reliable "eye-witness" and whether the data it provides can shed light on unknown perpetrators. We have developed an assay called the Ion AmpliSeq™ PhenoTrivium Panel, which combines three groups of markers: 41 phenotype- and 163 ancestry-informative autosomal SNPs together with 120 lineage-specific Y-SNPs. Here, we report the results of testing the assay's sensitivity and the predictions obtained for known reference samples. Moreover, we present the outcome of a blind study performed on real casework samples in order to understand the value and reliability of the information that would be provided to police investigators. Furthermore, we evaluated the accuracy of admixture prediction in Converge™ Software. The results show the panel to be a robust and sensitive assay which can be used to analyze casework samples. We conclude that the combination of the obtained predictions of phenotype, biogeographical ancestry, and male lineage can serve as a potential lead in challenging police investigations such as cold cases or cases with no suspect.

Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits

The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction performance in Bayesian models for eye, hair and skin color as well as hair structure and freckles in comparison to the respective prior-free models. Those prior-free models were either similarly defined either very close to the already established ones by using a reduced predictive marker set. However, these differences in the number of the predictive markers should not affect significantly our main outcomes. We observed that such priors often had a strong effect on the prediction performance, but to varying degrees between different traits and also different trait categories, with some categories barely showing an effect. While we found potential for improving the prediction accuracy of many of the appearance trait categories tested by using priors, our analyses also showed that misspecification of those prior values often severely diminished the accuracy compared to the respective prior-free approach. This emphasizes the importance of accurate specification of prevalence-informed priors in Bayesian prediction modeling of appearance traits. However, the existing literature knowledge on spatial prevalence is sparse for most appearance traits, including those investigated here. Due to the limitations in appearance trait prevalence knowledge, our results render the use of trait prevalence-informed priors in DNA-based appearance trait prediction currently infeasible.

The distinctive geographic patterns of common pigmentation variants at the OCA2 gene

Oculocutaneous Albinism type 2 (OCA2) is a gene of great interest because of genetic variation affecting normal pigmentation variation in humans. The diverse geographic patterns for variant frequencies at OCA2 have been evident but have not been systematically investigated, especially outside of Europe. Here we examine population genetic variation in and near the OCA2 gene from a worldwide perspective. The very different patterns of genetic variation found across world regions suggest strong selection effects may have been at work over time. For example, analyses involving the variants that affect pigmentation of the iris argue that the derived allele of the rs1800407 single nucleotide polymorphism, which produces a hypomorphic protein, may have contributed to the previously demonstrated positive selection in Europe for the enhancer variant responsible for light eye color. More study is needed on the relationships of the genetic variation at OCA2 to variation in pigmentation in areas beyond Europe.

Eye color prediction using the IrisPlex system: a limited pilot study in the Iraqi population

Background

Forensic DNA phenotyping has gained momentum in the recent past due to the prediction of externally visible characters (EVCs) from the biological sample. The most common phenotypes like eye, hair, and skin color are predicted from the biological samples using a web-based system called IrisPlex. Based on six genetic SNPs, the IrisPlex system is developed and validated for its prediction accuracy in diverse ethnic groups worldwide. In previous studies, this system proved to have significant prediction accuracy. The EVCs vary substantially based on different geographical locations. Hence, the objective of this study was to validate the accuracy of the IrisPlex system in predicting the eye colors in the Iraqi population.

Methods

Six genetic single-nucleotide polymorphisms SNPs (HERC2-rs12913832, OCA2- rs1800407, SLC24A4-rs12896399, SLC45A2- rs16891982, TYR-rs1393350, and IRF4- rs12203592) in 58 Iraqi subjects were performed using Sequenom MassARRAY Genotyping. According to Liu et al., a predicted probability of 0.7 was considered as the threshold.

Results

Participants in this study of brown color were observed in 44.83%, intermediate in 43.1%, and blue in 12.07%. Completely predictive accuracy is obtained in 1; we observed the AUC at threshold 0.7 was 0.91 for brown, 0.79 for blue, and 0.60 for intermediate eye color. The sensitivity was 42.85% for blue, 0% for intermediate eye color, and 100% for brown-colored eye. Specificity was 100% for blue, 100% for intermediate, and 78.13% for brown eye color.

Conclusion

Hence, it was concluded that the prediction accuracy of the IrisPlex system for blue and brown color eye in the Iraqi population is significant in the studied population size. However, a pivotal study with larger sample size is required to represent the prediction accuracy of the IrisPlex system in the whole Iraqi population.

Perceived attractiveness of Czech faces across 10 cultures: Associations with sexual shape dimorphism, averageness, fluctuating asymmetry, and eye color

Research on the perception of faces typically assumes that there are some universal values of attractiveness which are shared across individuals and cultures. The perception of attractiveness may, however, vary across cultures due to local differences in both facial morphology and standards of beauty. To examine cross-cultural consensus in the ratings of attractiveness, we presented a set of 120 non-manipulated photographs of Czech faces to ten samples of raters from both European (Czech Republic, Estonia, Sweden, Romania, Turkey, Portugal) and non-European countries (Brazil, India, Cameroon, Namibia). We examined the relative contribution of three facial markers (sexual shape dimorphism, averageness, fluctuating asymmetry) to the perception of attractiveness as well as the possible influence of eye color, which is a locally specific trait. In general, we found that both male and female faces which were closer to the average and more feminine in shape were regarded as more attractive, while fluctuating asymmetry had no effect. Despite a high cross-cultural consensus on attractiveness standards, significant differences in the perception of attractiveness seem to be related to the level of socio-economic development (as measured by the Human Development Index, HDI). Attractiveness ratings by raters from low-HDI countries (India, Cameroon, Namibia) converged less with ratings from Czech Republic than ratings from high-HDI countries (European countries and Brazil). With respect to eye color, some local patterns emerged which we discuss as a consequence of negative frequency-dependent selection.

Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches

Predicting phenotypes from DNA has recently become extensively studied field in forensic research and is referred to as Forensic DNA Phenotyping. Systems based on single nucleotide polymorphisms for accurate prediction of iris, hair and skin color in global population, independent of bio-geographical ancestry, have recently been introduced. Here, we analyzed 14 SNPs for distinct skin pigmentation traits in a homogeneous cohort of 222 Polish subjects. We compared three different algorithms: General Linear Model based on logistic regression, Random Forest and Neural Network in 18 developed prediction models. We demonstrate Random Forest to be the most accurate algorithm for 3- and 4-category estimations (total of 58.3% correct calls for skin color prediction, 47.2% for tanning prediction, 50% for freckling prediction). Binomial Logistic Regression was the best approach in 2-category estimations (total of 69.4% correct calls, AUC = 0.673 for tanning prediction; total of 52.8% correct calls, AUC = 0.537 for freckling prediction). Our study confirms the association of rs12913832 (HERC2) with all three skin pigmentation traits, but also variants associated solely with certain pigmentation traits, namely rs6058017 and rs4911414 (ASIP) with skin sensitivity to sun and tanning abilities, rs12203592 (IRF4) with freckling and rs4778241 and rs4778138 (OCA2) with skin color and tanning. Finally, we assessed significant differences in allele frequencies in comparison with CEU data and our study provides a starting point for the development of prediction models for homogeneous populations with less internal differentiation than in the global predictive testing.

Performance of four models for eye color prediction in an Italian population sample

Forensic DNA phenotyping (FDP) has recently provided important advancements in forensic investigations, by predicting the physical appearance of a subject from a biological sample, using SNP markers. The majority of operable prediction models have been developed for iris color; however, replication studies to understand their applicability on a worldwide scale are still limited for many of them. In this work, 4 models for eye color prediction (IrisPlex, Ruiz, Allwood and Hart models) were systematically evaluated in a sample of 296 subjects of Italian origin. Genotypes were determined by a custom NGS-based panel targeting all the predictive SNPs included in the 4 tested models. Overall, 60-69% of the Italian sample could be correctly predicted with the IrisPlex, Ruiz and Allwood models, applying the recommended threshold. The IrisPlex model showed the lowest frequency of errors (17%), but also the highest number of inconclusive results (18%). In the absence of the threshold, the highest proportion of correct predictions was again obtained with the IrisPlex model (76%), followed by the Allwood (73%) and the Ruiz (65%) models. Lastly, the Hart predictive algorithm had the lowest error rate (2%), but the majority of predictions (87%) were restricted to the less informative categories of "not-blue" and "not-brown", and correct color predictions were obtained only for 11% of the sample. As observed in previous studies, the majority of incorrect and undefined predictions were ascribable to the intermediate category, which represented 25% of the Italian sample. An adjustment of the IrisPlex (multinomial logistic regression) and Ruiz models (Snipper Bayesian classifier) with Italian allele frequencies gave only minor improvements in predicting intermediate eye color and no remarkable overall changes in performance. This suggests an incomplete knowledge underlying the intermediate colors. Considering the impact of this phenotype in the Italian sample as well as in other admixed populations, future improvements of eye color prediction methods should include a better genetic and phenotypic characterization of this category.

An overview of the latest developments in facial imaging

Facial imaging is a term used to describe methods that use facial images to assist or facilitate human identification. This pertains to two craniofacial identification procedures that use skulls and faces-facial approximation and photographic superimposition-as well as face-only methods for age progression/regression, the construction of facial graphics from eyewitness memory (including composites and artistic sketches), facial depiction, face mapping and newly emerging methods of molecular photofitting. Given the breadth of these facial imaging techniques, it is not surprising that a broad array of subject-matter experts participate in and/or contribute to the formulation and implementation of these methods (including forensic odontologists, forensic artists, police officers, electrical engineers, anatomists, geneticists, medical image specialists, psychologists, computer graphic programmers and software developers). As they are concerned with the physical characteristics of humans, each of these facial imaging areas also falls in the domain of physical anthropology, although not all of them have been traditionally regarded as such. This too offers useful opportunities to adapt established methods in one domain to others more traditionally held to be disciplines within physical anthropology (e.g. facial approximation, craniofacial superimposition and face photo-comparison). It is important to note that most facial imaging methods are not currently used for identification but serve to assist authorities in narrowing or directing investigations such that other, more potent, methods of identification can be used (e.g. DNA). Few, if any, facial imaging approaches can be considered honed end-stage scientific methods, with major opportunities for physical anthropologists to make meaningful contributions. Some facial imaging methods have considerably stronger scientific underpinnings than others (e.g. facial approximation versus face mapping), some currently lie entirely within the artistic sphere (facial depiction), and yet others are so aspirational that realistic capacity to obtain their aims has strongly been questioned despite highly advanced technical approaches (molecular photofitting). All this makes for a broad-ranging, dynamic and energetic field that is in a constant state of flux. This manuscript provides a theoretical snapshot of the purposes of these methods, the state of science as it pertains to them, and their latest research developments.

Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA

Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.

Genetic and phenotypic variability of iris color in Buenos Aires population

The aim of this work was to describe the phenotypic and genotypic variability related to iris color for the population of Buenos Aires province (Argentina), and to assess the usefulness of current methods of analysis for this country. We studied five Single Nucleotide Polymorphisms (SNPs) included in the IrisPlex kit, in 118 individuals, and we quantified eye color with Digital Iris Analysis Tool. The markers fit Hardy-Weinberg equilibrium for the whole sample, but not for rs12913832 within the group of brown eyes (LR=8.429; p=0.004). We found a remarkable association of HERC2 rs12913832 GG with blue color (p < 0.01) but the other markers did not show any association with iris color. The results for the Buenos Aires population differ from those of other populations of the world for these polymorphisms (p < 0,01). The differences we found might respond to the admixed ethnic composition of Argentina; therefore, methods of analysis used in European populations should be carefully applied when studying the population of Argentina. These findings reaffirm the importance of this investigation in the Argentinian population for people identification based on iris color.

Global skin colour prediction from DNA

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, 0.87±0.1 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.