Exploring iris colour prediction and ancestry inference in admixed populations of South America

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.

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.

A custom hybridisation enrichment forensic intelligence panel to infer biogeographic ancestry, hair and eye colour, and Y chromosome lineage

Massively parallel sequencing can provide genetic data for hundreds to thousands of loci in a single assay for various types of forensic testing. However, available commercial kits require an initial PCR amplification of short-to-medium sized targets which limits their application for highly degraded DNA. Development and optimisation of large PCR multiplexes also prevents creation of custom panels that target different suites of markers for identity, biogeographic ancestry, phenotype, and lineage markers (Y-chromosome and mtDNA). Hybridisation enrichment, an alternative approach for target enrichment prior to sequencing, uses biotinylated probes to bind to target DNA and has proven successful on degraded and ancient DNA. We developed a customisable hybridisation capture method, that uses individually mixed baits to allow tailored and targeted enrichment to specific forensic questions of interest. To allow collection of forensic intelligence data, we assembled and tested a custom panel of hybridisation baits to infer biogeographic ancestry, hair and eye colour, and paternal lineage (and sex) on modern male and female samples with a range of self-declared ancestries and hair/eye colour combinations. The panel correctly estimated biogeographic ancestry in 9/12 samples (75%) but detected European admixture in three individuals from regions with admixed demographic history. Hair and eye colour were predicted correctly in 83% and 92% of samples respectively, where intermediate eye colour and blond hair were problematic to predict. Analysis of Y-chromosome SNPs correctly assigned sex and paternal haplogroups, the latter complementing and supporting biogeographic ancestry predictions. Overall, we demonstrate the utility of this hybridisation enrichment approach to forensic intelligence testing using a combined suite of biogeographic ancestry, phenotype, and Y-chromosome SNPs for comprehensive biological profiling.

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.

Forensic Features and Genetic Structure Analyses of the Beijing Han Nationality Disclosed by a Self-Developed Panel Containing a Series of Ancestry Informative Deletion/Insertion Polymorphism Loci

The utilization of the ancestry informative markers to disclose the ancestral composition of a certain population and explore the genetic affinities between diverse populations is beneficial to inferring the biogeographic ancestry of unknown individuals and assisting in case detection, as well as avoiding the impacts of population stratification during genome-wide association analysis studies. In the present study, we applied an in-house ancestry informative deletion/insertion polymorphic multiplex amplification system to investigate the ancestral compositions of the Beijing Han population and analyze the genetic relationships between the Beijing Han population and 31 global reference populations. The results demonstrated that 32 loci of this self-developed panel containing 39 loci significantly contributed to the inference of genetic information for the Beijing Han population. The results of multiple population genetics statistical analyses indicated that the ancestral component and genetic architecture of the Beijing Han population were analogous to the reference East Asian populations, and that the Beijing Han population was genetically close to the reference East Asian populations.

Further insight into the global variability of the OCA2-HERC2 locus for human pigmentation from multiallelic markers

The OCA2-HERC2 locus is responsible for the greatest proportion of eye color variation in humans. Numerous studies extensively described both functional SNPs and associated patterns of variation over this region. The goal of our study is to examine how these haplotype structures and allelic associations vary when highly variable markers such as microsatellites are used. Eleven microsatellites spanning 357 Kb of OCA2-HERC2 genes are analyzed in 3029 individuals from worldwide populations. We found that several markers display large differences in allele frequency (10% to 35% difference) among Europeans, East Asians and Africans. In Europe, the alleles showing increased frequency can also discriminate individuals with (IrisPlex) predicted blue and brown eyes. Distinct haplotypes are identified around the variants C and T of the functional SNP rs12913832 (associated to blue eyes), with linkage disequilibrium r² values significant up to 237 Kb. The haplotype carrying the allele rs12913832 C has high frequency (76%) in blue eye predicted individuals (30% in brown eye predicted individuals), while the haplotype associated to the allele rs12913832 T is restricted to brown eye predicted individuals. Finally, homozygosity values reach levels of 91% near rs12913832. Odds ratios show values of 4.2, 7.4 and 10.4 for four markers around rs12913832 and 7.1 for their core haplotype. Hence, this study provides an example on the informativeness of multiallelic markers that, despite their current limited potential contribution to forensic eye color prediction, supports the use of microsatellites for identifying causing variants showing similar genetic features and history.

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.

Prediction of eye and hair pigmentation phenotypes using the HIrisPlex system in a Brazilian admixed population sample

Human pigmentation is a complex trait, probably involving more than 100 genes. Predicting phenotypes using SNPs present in those genes is important for forensic purpose. For this, the HIrisPlex tool was developed for eye and hair color prediction, with both models achieving high accuracy among Europeans. Its evaluation in admixed populations is important, since they present a higher frequency of intermediate phenotypes, and HIrisPlex has demonstrated limitations in such predictions; therefore, the performance of this tool may be impaired in such populations. Here, we evaluate the set of 24 markers from the HIrisPlex system in 328 individuals from Ribeirão Preto (SP) region, predicting eye and hair color and comparing the predictions with their real phenotypes. We used the HaloPlex Target Enrichment System and MiSeq Personal Sequencer platform for massively parallel sequencing. The prediction of eye and hair color was accomplished by the HIrisPlex online tool, using the default prediction settings. Ancestry was estimated using the SNPforID 34-plex to observe if and how an individual's ancestry background would affect predictions in this admixed sample. Our sample presented major European ancestry (70.5%), followed by African (21.1%) and Native American/East Asian (8.4%). HIrisPlex presented an overall sensitivity of 0.691 for hair color prediction, with sensitivities ranging from 0.547 to 0.782. The lowest sensitivity was observed for individuals with black hair, who present a reduced European contribution (48.4%). For eye color prediction, the overall sensitivity was 0.741, with sensitivities higher than 0.85 for blue and brown eyes, although it failed in predicting intermediate eye color. Such struggle in predicting this phenotype category is in accordance with what has been seen in previous studies involving HIrisPlex. Individuals with brown eye color are more admixed, with European ancestry decreasing to 62.6%; notwithstanding that, sensitivity for brown eyes was almost 100%. Overall sensitivity increases to 0.791 when a 0.7 threshold is set, though 12.5% of the individuals become undefined. When combining eye and hair prediction, hit rates between 51.3 and 68.9% were achieved. Despite the difficulties with intermediate phenotypes, we have shown that HIrisPlex results can be very helpful when interpreted with caution.

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.

Skin pigmentation polymorphisms associated with increased risk of melanoma in a case-control sample from southern Brazil

BACKGROUND

Melanoma is the most aggressive type of skin cancer and is associated with environmental and genetic risk factors. It originates in melanocytes, the pigment-producing cells. Single nucleotide polymorphisms (SNPs) in pigmentation genes have been described in melanoma risk modulation, but knowledge in the field is still limited.

METHODS

In a case-control approach (107 cases and 119 controls), we investigated the effect of four pigmentation gene SNPs (TYR rs1126809, HERC2 rs1129038, SLC24A5 rs1426654, and SLC45A2 rs16891982) on melanoma risk in individuals from southern Brazil using a multivariate logistic regression model and multifactor dimensionality reduction (MDR) analysis.

RESULTS

Two SNPs were associated with an increased risk of melanoma in a dominant model: rs1129038AA and rs1426654AA [OR = 2.094 (95% CI: 1.106-3.966), P = 2.3 10^- 2 and OR = 7.126 (95% CI: 1.873-27.110), P = 4.0 10^- 3, respectively]. SNP rs16891982CC was associated with a lower risk to melanoma development in a log-additive model when the allele C was inherited [OR = 0.081 (95% CI: 0.008-0.782), P = 3 10^- 2]. In addition, MDR analysis showed that the combination of the rs1426654AA and rs16891982GG genotypes was associated with a higher risk for melanoma (P = 3 10^- 3), with a redundant effect.

CONCLUSIONS

These results contribute to the current knowledge and indicate that epistatic interaction of these SNPs, with an additive or correlational effect, may be involved in modulating the risk of melanoma in individuals from a geographic region with a high incidence of the disease.

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.

Insights on hair, skin and eye color of ancient and contemporary Native Americans

Over the past few years, tools capable of predicting pigmentation phenotypes have been developed aiming to contribute for criminal and anthropological investigations. In this study, we used eight genetic systems to infer eye, hair, and skin color of ancient and contemporary Native Americans. To achieve this goal, we retrieved 61 SNPs from 42 samples available in free online repositories of DNA sequences. We performed pigmentation predictions using two freely available tools, HIrisPlex-S and Snipper, in addition to two other published models. This workflow made possible to predict all three phenotypes with at least one tool for 29 out of the 42 samples. Considering these 29 individuals, predictions for eye, hair, and skin color were obtained with HIrisPlex-S for 27, 28 and 27 individuals, respectively, while 24, 25 and 25 individuals had such predictions with Snipper. In general, ancient and contemporary Native Americans were predicted to have intermediate/brown eyes, black hair, and intermediate/darker skin pigmentation.

Differentiation of Hispanic biogeographic ancestry with 80 ancestry informative markers

Ancestry informative single nucleotide polymorphisms (SNPs) can identify biogeographic ancestry (BGA); however, population substructure and relatively recent admixture can make differentiation difficult in heterogeneous Hispanic populations. Utilizing unrelated individuals from the Genomic Origins and Admixture in Latinos dataset (GOAL, n = 160), we designed an 80 SNP panel (Setser80) that accurately depicts BGA through STRUCTURE and PCA. We compared our Setser80 to the Seldin and Kidd panels via resampling simulations, which models data based on allele frequencies. We incorporated Admixed American 1000 Genomes populations (1000 G, n = 347), into a combined populations dataset to determine robustness. Using multinomial logistic regression (MLR), we compared the 3 panels on the combined dataset and found overall MLR classification accuracies: 93.2% Setser80, 87.9% Seldin panel, 71.4% Kidd panel. Naïve Bayesian classification had similar results on the combined dataset: 91.5% Setser80, 84.7% Seldin panel, 71.1% Kidd panel. Although Peru and Mexico were absent from panel design, we achieved high classification accuracy on the combined populations for Peru (MLR = 100%, naïve Bayes = 98%), and Mexico (MLR = 90%, naïve Bayes = 83.4%) as evidence of the portability of the Setser80. Our results indicate the Setser80 SNP panel can reliably classify BGA for individuals of presumed Hispanic origin.

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.

Off-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: A resource

With recent advances in DNA sequencing technologies it has become feasible and cost effective to genotype larger marker sets for forensic purposes. Two technologies that make use of the larger marker sets have come into focus in forensic research and applications; inference of biogeographic ancestry (BGA) and forensic DNA phenotyping (FDP). These methods hold the promise to reveal information about a yet unknown perpetrator from a DNA sample. In contrast, DNA-profiling, that is a standard practice in case work, relies on matching DNA-profiles between crime scene material and suspects on a database of DNA-profiles. Markers for DNA-profiling were developed under the premise to reveal as little additional information about the human source of the profile as possible, the rationale being that personal privacy rights have to be balanced against the public interest in solving a crime. The same argument holds for markers used in BGA and FDP; these markers might also reveal information on off-target phenotypes (OTPs), that go beyond BGA and the phenotypes targeted in FDP. In particular, health related OTPs might shift the balance between privacy protection and public interest. However, to our knowledge, there is currently no convenient resource available to incorporate knowledge on OTPs in BGA and FDP assay design and application. In order to provide such a resource, we performed a systematic search for OTPs associated with a comprehensive set of markers (1766 SNPs) used or suggested to be used for BGA inference and FDP. In this set, we identified a relatively small number of 27 SNPs (1.53%) that convey information on diverse health related OTPs such as cancer risk, induced asthma, or risk of alcoholism. Some of these SNPs are commonly used for FDP and BGA across different marker sets. We conclude that the effects of SNP markers used in FDP and BGA on OTPs are currently limited, with few exceptions that should be considered in a balanced decision on assay design and application.

Eye color prediction using single nucleotide polymorphisms in Saudi population

Background

DNA prediction of eye color represent one application of the externally visible characteristics (EVC), which attained growing interest in the field of DNA forensic phenotyping. This is mainly due to its ability to narrow the pool of suspects without the need to compare any retrieved DNA material from the crime scene to a reference DNA. Several methods and multiplex genetic panel were proposed with variable prediction accuracy between different populations. However, such panel was not previously tested in the Saudi population, nor any populations of the Middle East and North Africa origin.

Method

A panel of eleven single nucleotide polymorphisms (SNPs) was tested for their association with three eye colors (brown, hazel, and intermediate) in 80 volunteer Saudi individuals. SNPs and haplotype association test with eye colors were performed to identify the top significant SNPs with the three eye colors. Also, multinomial logistic regression was used to construct the prediction model using a training set of 60 subjects, and a validation set of 20 subjects. The goodness of fit parameter of the model to correctly predicts each eye color as compared to the other was performed.

Results

Eye color was significantly associated with rs12913832, rs7170852, and rs916977 that are located within HERC2. SNP rs12913832 was the top significant SNP (p-value = 1.78E−15) that accounted for the association in this region, as the other SNPs were not significant after adjusting for rs12913832. A prediction model containing five SNPs showed high prediction accuracy with Area Under the receiver operating characteristic Curves (AUC) equals to 0.95 and 0.83 for brown and intermediate eye colors, respectively. However, the model’s performance was very low for predicting the hazel eye color with AUC equals 0.75.

Discussion

Despite the small sample size of our study, we reported very significant SNP associations with eye color. Our model to predict eye colors based on DNA material showed high accuracy for brown and intermediate eye colors. The eye color prediction-model underperformed for the hazel eye colors, suggesting that larger sample size, as well as more comprehensive set of SNPs, could improve the model-prediction accuracy.