Blue Eye Colour Research Articles

Perception of blue and brown eye colours for forensic DNA phenotyping

Eye colour is a prominent visible trait in Europeans and is of significance in forensic genetics. Eye colour is most commonly categorised in a three-category system comprising brown, intermediate, and blue eye colours. However, the general perception of eye colour categories has not been explored. Here, we categorised eye colour based on the subjective evaluation of 442 digital close-up photos of eyes assessed by 30 Danish volunteers. The participants were asked to categorise each eye in a three-category (brown, intermediate, blue) and a two-category (brown, blue) system. We found that the two-category system corresponded best with the perception of eye colour. Disagreements in the eye colour categorisation by at least 10% of the participants were observed for 33% of the eye pictures using the three-category system. In comparison, only 10% of the pictures were categorised differently by at least 10% of participants when using the two-category system. The genetic basis for distinction between blue and brown eye colour primarily depends on a single SNP, rs12913832. Likelihood ratios based on the genotype of rs12913832 and the two-category system were: LR = P(rs12913832:GG|brown)/P(rs12913832:GG|blue) = 0.1, LR = P(rs12913832:AA|brown)/P(rs12913832:AA|blue) = 54, and LR = P(rs12913832:GA|brown)/P(rs12913832:GA|blue) = 19. This SNP is included in the Precision ID Ancestry panel used for ancestry inference, which enables genetic ancestry profiles to be accompanied by prediction of blue or brown eye colour.

Genetic Landscape of Slovenians: Past Admixture and Natural Selection Pattern.

The Slovenian territory played a crucial role in the past serving as gateway for several human migrations. Previous studies used Slovenians as a source population to interpret different demographic events happened in Europe but not much is known about the genetic background and the demographic history of this population. Here, we analyzed genome-wide data from 96 individuals to shed light on the genetic role and history of the Slovenian population. Y chromosome diversity splits into two major haplogroups R1b and R1a with the latter suggesting a genetic contribution from the steppe. Slovenian individuals are more closely related to Northern and Eastern European populations than Southern European populations even though they are geographically closer. This pattern is confirmed by an admixture and clustering analysis. We also identified a single stream of admixture events between the Slovenians with Sardinians and Russians around ∼2630 BCE (2149-3112). Using ancient samples, we found a significant admixture in Slovenians using Yamnaya and the early Neolithic Hungarians as sources, dated around ∼1762 BCE (1099-2426) suggesting a strong contribution from the steppe to the foundation of the observed modern genetic diversity. Finally, we looked for signals of selection in candidate variants and we found significant hits in HERC2 and FADS responsible for blue eye color and synthesis of long-chain unsaturated fatty acids, respectively, when Slovenians were compared to Southern Europeans. While the comparison was done with Eastern Europeans, we identified significant signals in PKD2L1 and IL6R which are genes associated with taste and coronary artery disease, respectively.

Investigating the impact of age-depended hair colour darkening during childhood on DNA-based hair colour prediction with the HIrisPlex system

Predictive DNA analysis of externally visible characteristics exerts an increasing influence on contemporary forensic and anthropological investigations, with pigmentation traits currently being the most advanced for predictive modelling. Since pigmentation prediction error in some cases may be due to the result of age-related hair colour darkening, and sex influence in eye colour, this study aims to investigate these less explored phenomena on a group of juvenile individuals. Pigmentation phenotypes of children between the age of 6–13 years old were evaluated, in addition to data about their hair colour during early childhood from a select number of these individuals. The HIrisPlex models for DNA-based eye and hair colour prediction were used with input from SNP genotyping using massive parallel sequencing. Analysis of the total group of 476 children showed high accuracy in blue (AUC = 0.89) and brown (AUC = 0.91) eye colour prediction, while hair colour was predicted with AUC = 0.64 for blond, AUC = 0.64 for brown and AUC = 0.97 for red. 70.8% (n = 143) of the total number of children phenotypically blond for hair colour during early childhood progressed to brown during advanced childhood. In 70.6% (n = 101) of those cases, an incorrect blond hair prediction was made during the time of analysis. A noticeable decline in AUC values for blond (from 0.76 to 0.65) and brown (from 0.72 to 0.64) were observed when comparing hair colour prediction outcomes for the phenotypes recorded for the two different time points (at the age of 2–3 and 6–13). The number of incorrect blond hair colour predictions was significantly higher in children with brown hair at age 6–13 who were blond at early childhood (n = 47, 32.9%), relative to children who had brown hair at both time points (n = 6, 9.4%). However, in 28.0% (n = 40) of children who did experience hair colour darkening, HIrisPlex provided the correct prediction for the darkened hair colour phenotype, despite them being blond in early childhood. Our study implies that HIrisPlex can correctly predict adult hair colour in some individuals who experience age-related hair colour darkening during adolescence. However, in most instances prediction seems to default to the pre-adolescent hair colour for individuals with this phenomenon. In the future, the full adolescent age range in which hair colour darkening can occur should be considered in the study samples used for training hair colour prediction models to obtain a more complete picture of the phenomenon and its impact on DNA-based hair colour prediction in adults.

Iris pigmented lesions as a marker of cutaneous melanoma risk: an Australian case-control study.

Iris naevi and iris freckles have a frequency of 4% and 50% in the European population, respectively. They are associated with dysplastic naevi, but few studies have examined their link to cutaneous melanoma. To assess whether iris pigmented lesions are a predictive indicator for cutaneous melanoma. This is a melanoma case-control study of 1254 European-background Australians. Sun exposure and melanoma history, a saliva sample for DNA analysis and eye photographs taken with a digital camera were collected from 1117 participants. Iris images were assessed by up to four trained observers for the number of iris pigmented lesions. The data were analysed for correlations between iris pigmented lesions and melanoma history. Case participants over the age of 40 had similar numbers of iris pigmented lesions to age matched controls (mean 5·7 vs. 5·2, P = 0·02), but in younger case and control participants there was a greater difference (mean 3·96 vs. 2·19, P = 0·004). A logistic regression adjusted for age, sex, skin, hair and eye colour, skin freckling and naevus count found that the presence of three or more iris pigmented lesions increases the melanoma risk 1·45-fold [95% confidence interval (CI) 1·07-1·95]. HERC2/OCA2 rs12913832 and IRF4 rs12203592 influenced both eye colour and the number of iris pigmented lesions. On the HERC2/OCA2 A/A and A/G genotype background there was an increasing proportion of blue eye colour when carrying the IRF4 T allele (P = 3 × 10-4 ) and a higher number of iris pigmented lesions with the IRF4 T/T homozygote (P = 3 × 10-9 ). Iris pigmented lesion count provides additional predictive information for melanoma risk above that from conventional risk factors.

Further evidence for population specific differences in the effect of DNA markers and gender on eye colour prediction in forensics.

The genetics of eye colour has been extensively studied over the past few years, and the identified polymorphisms have been applied with marked success in the field of Forensic DNA Phenotyping. A picture that arises from evaluation of the currently available eye colour prediction markers shows that only the analysis of HERC2-OCA2 complex has similar effectiveness in different populations, while the predictive potential of other loci may vary significantly. Moreover, the role of gender in the explanation of human eye colour variation should not be neglected in some populations. In the present study, we re-investigated the data for 1020 Polish individuals and using neural networks and logistic regression methods explored predictive capacity of IrisPlex SNPs and gender in this population sample. In general, neural networks provided higher prediction accuracy comparing to logistic regression (AUC increase by 0.02–0.06). Four out of six IrisPlex SNPs were associated with eye colour in the studied population. HERC2 rs12913832, OCA2 rs1800407 and SLC24A4 rs12896399 were found to be the most important eye colour predictors (p < 0.007) while the effect of rs16891982 in SLC45A2 was less significant. Gender was found to be significantly associated with eye colour with males having ~1.5 higher odds for blue eye colour comparing to females (p = 0.002) and was ranked as the third most important factor in blue/non-blue eye colour determination. However, the implementation of gender into the developed prediction models had marginal and ambiguous impact on the overall accuracy of prediction confirming that the effect of gender on eye colour in this population is small. Our study indicated the advantage of neural networks in prediction modeling in forensics and provided additional evidence for population specific differences in the predictive importance of the IrisPlex SNPs and gender.

Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genome

The Neolithic and Bronze Age transitions were profound cultural shifts catalyzed in parts of Europe by migrations, first of early farmers from the Near East and then Bronze Age herders from the Pontic Steppe. However, a decades-long, unresolved controversy is whether population change or cultural adoption occurred at the Atlantic edge, within the British Isles. We address this issue by using the first whole genome data from prehistoric Irish individuals. A Neolithic woman (3343-3020 cal BC) from a megalithic burial (10.3× coverage) possessed a genome of predominantly Near Eastern origin. She had some hunter-gatherer ancestry but belonged to a population of large effective size, suggesting a substantial influx of early farmers to the island. Three Bronze Age individuals from Rathlin Island (2026-1534 cal BC), including one high coverage (10.5×) genome, showed substantial Steppe genetic heritage indicating that the European population upheavals of the third millennium manifested all of the way from southern Siberia to the western ocean. This turnover invites the possibility of accompanying introduction of Indo-European, perhaps early Celtic, language. Irish Bronze Age haplotypic similarity is strongest within modern Irish, Scottish, and Welsh populations, and several important genetic variants that today show maximal or very high frequencies in Ireland appear at this horizon. These include those coding for lactase persistence, blue eye color, Y chromosome R1b haplotypes, and the hemochromatosis C282Y allele; to our knowledge, the first detection of a known Mendelian disease variant in prehistory. These findings together suggest the establishment of central attributes of the Irish genome 4,000 y ago.

Assessment of IrisPlex-based multiplex for eye and skin color prediction with application to a Portuguese population.

DNA phenotyping research is one of the most emergent areas of forensic genetics. Predictions of externally visible characteristics are possible through analysis of single nucleotide polymorphisms. These tools can provide police with "intelligence" in cases where there are no obvious suspects and unknown biological samples found at the crime scene do not result in any criminal DNA database hits. IrisPlex, an eye color prediction assay, revealed high prediction rates for blue and brown eye color in European populations. However, this is less predictive in some non-European populations, probably due to admixing. When compared to other European countries, Portugal has a relatively admixed population, resulting from a genetic influx derived from its proximity to and historical relations with numerous African territories. The aim of this work was to evaluate the utility of IrisPlex in the Portuguese population. Furthermore, the possibility of supplementing this multiplex with additional markers to also achieve skin color prediction within this population was evaluated. For that, IrisPlex was augmented with additional SNP loci. Eye and skin color prediction was estimated using the multinomial logistic regression and binomial logistic regression models, respectively. The results demonstrated eye color prediction accuracies of the IrisPlex system of 90 and 60% for brown and blue eye color, respectively, and 77% for intermediate eye color, after allele frequency adjustment. With regard to skin color, it was possible to achieve a prediction accuracy of 93%. In the future, phenotypic determination multiplexes must include additional loci to permit skin color prediction as presented in this study as this can be an advantageous tool for forensic investigation.

The more the merrier? How a few SNPs predict pigmentation phenotypes in the Northern German population.

Human pigmentation traits are of great interest to many research areas, from ancient DNA analysis to forensic science. We developed a gene-based predictive model for pigmentation phenotypes in a realistic target population for forensic case work from Northern Germany and compared our model with those brought forth by previous studies of genetically more heterogeneous populations. In doing so, we aimed at answering the following research questions: (1) do existing models allow good prediction of high-quality phenotypes in a genetically similar albeit more homogeneous population? (2) Would a model specifically set up for the more homogeneous population perform notably better than existing models? (3) Can the number of markers included in existing models be reduced without compromising their predictive capability in the more homogenous population? We investigated the association between eye, hair and skin colour and 12 candidate single-nucleotide polymorphisms (SNPs) from six genes. Our study comprised two samples of 300 and 100 individuals from Northern Germany. SNP rs12913832 in HERC2 was found to be strongly associated with blue eye colour (odds ratio=40.0, P<1.2 × 10(-4)) and to yield moderate predictive power (AUC: 77%; sensitivity: 90%, specificity: 63%, both at a 0.5 threshold for blue eye colour probability). SNP associations with hair and skin colour were weaker and genotypes less predictive. A comparison with two recently published sets of markers to predict eye and hair colour revealed that the consideration of additional SNPs with weak-to-moderate effect increased the predictive power for eye colour, but not for hair colour.

Eye color: A potential indicator of alcohol dependence risk in European Americans

In archival samples of European-ancestry subjects, light-eyed individuals have been found to consume more alcohol than dark-eyed individuals. No published population-based studies have directly tested the association between alcohol dependence (AD) and eye color. We hypothesized that light-eyed individuals have a higher prevalence of AD than dark-eyed individuals. A mixture model was used to select a homogeneous sample of 1,263 European-Americans and control for population stratification. After quality control, we conducted an association study using logistic regression, adjusting for confounders (age, sex, and genetic ancestry). We found evidence of association between AD and blue eye color (P = 0.0005 and odds ratio = 1.83 (1.31-2.57)), supporting light eye color as a risk factor relative to brown eye color. Network-based analyses revealed a statistically significant (P = 0.02) number of genetic interactions between eye color genes and AD-associated genes. We found evidence of linkage disequilibrium between an AD-associated GABA receptor gene cluster, GABRB3/GABRG3, and eye color genes, OCA2/HERC2, as well as between AD-associated GRM5 and pigmentation-associated TYR. Our population-phenotype, network, and linkage disequilibrium analyses support association between blue eye color and AD. Although we controlled for stratification we cannot exclude underlying occult stratification as a contributor to this observation. Although replication is needed, our findings suggest that eye pigmentation information may be useful in research on AD. Further characterization of this association may unravel new AD etiological factors. © 2015 Wiley Periodicals, Inc.

Interactions between ultraviolet light and MC1R and OCA2 variants are determinants of childhood nevus and freckle phenotypes.

Melanocytic nevi (moles) and freckles are well known biomarkers of melanoma risk, and they are influenced by similar UV light exposures and genetic susceptibilities to those that increase melanoma risk. Nevertheless, the selective interactions between UV exposures and nevus and freckling genes remain largely undescribed. We conducted a longitudinal study from ages 6 through 10 years in 477 Colorado children who had annual information collected for sun exposure, sun protection behaviors, and full body skin exams. MC1R and HERC2/OCA2 rs12913832 were genotyped and linear mixed models were used to identify main and interaction effects. All measures of sun exposure (chronic, sunburns, and waterside vacations) contributed to total nevus counts, and cumulative chronic exposure acted as the major driver of nevus development. Waterside vacations strongly increased total nevus counts in children with rs12913832 blue eye color alleles and facial freckling scores in those with MC1R red hair color variants. Sunburns increased the numbers of larger nevi (≥2 mm) in subjects with certain MC1R and rs12913832 genotypes. Complex interactions between different UV exposure profiles and genotype combinations determine nevus numbers and size, and the degree of facial freckling. Our findings emphasize the importance of implementing sun-protective behavior in childhood regardless of genetic make-up, although children with particular genetic variants may benefit from specifically targeted preventive measures to counteract their inherent risk of melanoma. Moreover, we demonstrate, for the first time, that longitudinal studies are a highly powered tool to uncover new gene-environment interactions that increase cancer risk.

'Behind blue eyes'†: the association between eye colour and deep infiltrating endometriosis.

Is the prevalence of blue eye colour higher in women with deep endometriosis? Blue eye colour is more common in women with deep endometriosis when compared with both women with ovarian endometriomas and women without a history of endometriosis. Recent and intriguing evidence suggests that women with deep endometriosis may have particular phenotypic characteristics including a higher prevalence of a light-colour iris. Available epidemiological evidence is however weak. Case-control study performed in a large academic department specializing in the study and treatment of endometriosis. Individual iris colour was evaluated in daylight and categorized in three grades, namely blue-grey (blue), hazel-green (green) and brown. One observer assessed iris colour. In addition, the women themselves were invited to indicate the colour of their eyes according to the same classification system. Cases with discordant eye colour determinations between the observer and the woman were excluded from the final analysis. Two hundred and twenty-three women with deep endometriosis (cases), 247 with ovarian endometriomas and 301 without a history of endometriosis were enrolled. After exclusion of 52 discordant cases, the proportions of brown, blue and green eye colours were, respectively, 61, 30 and 9% in the deep endometriosis group, 74, 16 and 10% in the endometrioma group and 75, 15 and 10% in the non-endometriosis group. Women in the deep endometriosis group had a statistically significant excess of blue eyes and a reduced proportion of brown eyes compared with the two control groups (P = 0.002 and P < 0.001, respectively). The proportion of blue eyes was almost identical in the ovarian endometrioma group and the non-endometriosis group, and that of green eyes was substantially similar in all study groups. The OR (95% CI) of having blue eyes in women with deep endometriosis compared with women with ovarian endometriosis and with those without endometriosis was, respectively, 2.2 (1.4-3.6) and 2.5 (1.6-3.9). We cannot exclude that some women without a previous diagnosis of endometriosis indeed had the disease. However, this would have led to a reduction of the observed difference in proportion of blue eyes, thus to a potential underestimation of the real strength of the association. Moreover, under-ascertainment is possible with regard to peritoneal disease, but unlikely with deep endometriotic lesions and ovarian endometriomas. There are two possible explanations for our findings. Both may have intriguing implications for future research on endometriosis. Firstly, genes involved in the control of iris colour transmission may lie in a region with a strong pattern of linkage disequilibrium with genes involved in the invasiveness of endometriosis. Alternatively, blue eye colour could be considered an indicator of a photo-sensitive phenotype resulting in limited exposure to sunlight and UVB radiation. Limited sunlight exposure is associated with reduced circulating 25-hydroxyvitamin D3, an element that has recently been linked to endometriosis development.

Collaborative EDNAP exercise on the IrisPlex system for DNA-based prediction of human eye colour.

The IrisPlex system is a DNA-based test system for the prediction of human eye colour from biological samples and consists of a single forensically validated multiplex genotyping assay together with a statistical prediction model that is based on genotypes and phenotypes from thousands of individuals. IrisPlex predicts blue and brown human eye colour with, on average, >94% precision accuracy using six of the currently most eye colour informative single nucleotide polymorphisms (HERC2 rs12913832, OCA2 rs1800407, SLC24A4 rs12896399, SLC45A2 (MATP) rs16891982, TYR rs1393350, and IRF4 rs12203592) according to a previous study, while the accuracy in predicting non-blue and non-brown eye colours is considerably lower. In an effort to vigorously assess the IrisPlex system at the international level, testing was performed by 21 laboratories in the context of a collaborative exercise divided into three tasks and organised by the European DNA Profiling (EDNAP) Group of the International Society of Forensic Genetics (ISFG). Task 1 involved the assessment of 10 blood and saliva samples provided on FTA cards by the organising laboratory together with eye colour phenotypes; 99.4% of the genotypes were correctly reported and 99% of the eye colour phenotypes were correctly predicted. Task 2 involved the assessment of 5 DNA samples extracted by the host laboratory from simulated casework samples, artificially degraded, and provided to the participants in varying DNA concentrations. For this task, 98.7% of the genotypes were correctly determined and 96.2% of eye colour phenotypes were correctly inferred. For Tasks 1 and 2 together, 99.2% (1875) of the 1890 genotypes were correctly generated and of the 15 (0.8%) incorrect genotype calls, only 2 (0.1%) resulted in incorrect eye colour phenotypes. The voluntary Task 3 involved participants choosing their own test subjects for IrisPlex genotyping and eye colour phenotype inference, while eye photographs were provided to the organising laboratory and judged; 96% of the eye colour phenotypes were inferred correctly across 100 samples and 19 laboratories. The high success rates in genotyping and eye colour phenotyping clearly demonstrate the reproducibility and the robustness of the IrisPlex assay as well as the accuracy of the IrisPlex model to predict blue and brown eye colour from DNA. Additionally, this study demonstrates the ease with which the IrisPlex system is implementable and applicable across forensic laboratories around the world with varying pre-existing experiences.

The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model

In two recent studies of Spanish individuals, gender was suggested as a factor that contributes to human eye colour variation. However, gender did not improve the predictive accuracy on blue, intermediate and brown eye colours when gender was included in the IrisPlex model. In this study, we investigate the role of gender as a factor that contributes to eye colour variation and suggest that the gender effect on eye colour is population specific. A total of 230 Italian individuals were typed for the six IrisPlex SNPs (rs12913832, rs1800407, rs12896399, rs1393350, rs16891982 and rs12203592). A quantitative eye colour score (Pixel Index of the Eye: PIE-score) was calculated based on digital eye images using the custom made DIAT software. The results were compared with those of Danish and Swedish population samples. As expected, we found HERC2 rs12913832 as the main predictor of human eye colour independently of ancestry. Furthermore, we found gender to be significantly associated with quantitative eye colour measurements in the Italian population sample. We found that the association was statistically significant only among Italian individuals typed as heterozygote GA for HERC2 rs12913832. Interestingly, we did not observe the same association in the Danish and Swedish population. This indicated that the gender effect on eye colour is population specific. We estimated the effect of gender on quantitative eye colour in the Italian population sample to be 4.9%. Among gender and the IrisPlex SNPs, gender ranked as the second most important predictor of human eye colour variation in Italians after HERC2 rs12913832. We, furthermore, tested the five lower ranked IrisPlex predictors, and evaluated all possible 3(6) (729) genotype combinations of the IrisPlex assay and their corresponding predictive values using the IrisPlex prediction model [4]. The results suggested that maximum three (rs12913832, rs1800407, rs16891982) of the six IrisPlex SNPs are useful in practical forensic genetic casework.

Evaluation of the IrisPlex DNA-based eye color prediction assay in a United States population

DNA phenotyping is a rapidly developing area of research in forensic biology. Externally visible characteristics (EVCs) can be determined based on genotype data, specifically based on single nucleotide polymorphisms (SNPs). These SNPs are chosen based on their association with genes related to the phenotypic expression of interest, with known examples in eye, hair, and skin color traits. DNA phenotyping has forensic importance when unknown biological samples at a crime scene do not result in a criminal database hit; a phenotypic profile of the sample can therefore be used to develop investigational leads. IrisPlex, an eye color prediction assay, has previously shown high prediction rates for blue and brown eye color in a Dutch European population. The objective of this work was to evaluate its utility in a North American population. We evaluated six SNPs included in the IrisPlex assay in population sample collected from a USA college campus. We used a quantitative method of eye color classification based on (RGB) color components of digital photographs of the eye taken from each study volunteer so that each eye was placed in one of three eye color categories: brown, intermediate, or blue. Objective color classification was shown to correlate with basic human visual determination making it a feasible option for use in future prediction assay development. Using these samples and various models, the maximum prediction accuracies of the IrisPlex system after allele frequency adjustment was 58% and 95% brown and blue eye color predictions, respectively, and 11% for intermediate eye colors. Future developments should include incorporation of additional informative SNPs, specifically related to the intermediate eye color, and we recommend the use of a Bayesian approach as a prediction model as likelihood ratios can be determined for reporting purposes.

Prediction of eye color in the Slovenian population using the IrisPlex SNPs

AimTo evaluate the accuracy of eye color prediction based on six IrisPlex single nucleotide polymorphisms (SNP) in a Slovenian population sample.MethodsSix IrisPlex predictor SNPs (HERC2 – rs12913832, OCA2 – rs1800407, SLC45A2 – rs16891982 and TYR – rs1393350, SLC24A4 – rs12896399, and IRF4 – rs12203592) of 105 individuals were analyzed using single base extension approach and SNaPshot chemistry. The IrisPlex multinomial regression prediction model was used to infer eye color probabilities. The accuracy of the IrisPlex was assessed through the calculation of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the receiver characteristic operating curves (AUC).ResultsBlue eye color was observed in 44.7%, brown in 29.6%, and intermediate in 25.7% participants. Prediction accuracy expressed by the AUC was 0.966 for blue, 0.913 for brown, and 0.796 for intermediate eye color. Sensitivity was 93.6% for blue, 58.1% for brown, and 0% for intermediate eye color. Specificity was 93.1% for blue, 89.2% for brown, and 100% for intermediate eye color. PPV was 91.7% for blue and 69.2% for brown color. NPV was 94.7% for blue and 83.5% for brown eye color. These values indicate prediction accuracy comparable to that established in other studies.ConclusionBlue and brown eye color can be reliably predicted from DNA samples using only six polymorphisms, while intermediate eye color defies prediction, indicating that more research is needed to genetically predict the whole variation of eye color in humans.

Genetic analyses of the human eye colours using a novel objective method for eye colour classification

In this study, we present a new objective method for measuring the eye colour on a continuous scale that allows researchers to associate genetic markers with different shades of eye colour. With the use of the custom designed software Digital Iris Analysis Tool (DIAT), the iris was automatically identified and extracted from high resolution digital images. DIAT was made user friendly with a graphical user interface. The software counted the number of blue and brown pixels in the iris image and calculated a Pixel Index of the Eye (PIE-score) that described the eye colour quantitatively. The PIE-score ranged from -1 to 1 (brown to blue). The software eliminated the need for user based interpretation and qualitative eye colour categories. In 94% (570) of 605 analyzed eye images, the iris region was successfully extracted and a PIE-score was calculated. A very high correlation between the PIE-score and the human perception of eye colour was observed. The correlations between the PIE-scores and the six IrisPlex SNPs (HERC2 rs12913832, OCA2 rs1800407, SLC24A4 rs12896399, TYR rs1393350, SLC45A2 rs16891982 and IRF4 rs12203592) were analyzed in 570 individuals. Significant differences (p<10(-6)) in the PIE-scores of the individuals typed as HERC2 rs12913832 G (PIE=0.99) and rs12913832 GA (PIE=-0.71) or A (PIE=-0.87) were observed. We adjusted for the effect of HERC2 rs12913832 and showed that the quantitative PIE-scores were significantly associated with SNPs with minor effects (OCA2 rs1800407, SLC24A4 rs12896399 and TYR rs1393350) on the eye colour. We evaluated the two published prediction models for eye colour (IrisPlex [1] and Snipper[2]) and compared the predictions with the PIE-scores. We found good concordance with the prediction from individuals typed as HERC2 rs12913832 G. However, both methods had difficulties in categorizing individuals typed as HERC2 rs12913832 GA because of the large variation in eye colour in HERC2 rs12913832 GA individuals. With the use of the DIAT software and the PIE-score, it will be possible to automatically compare the iris colour of large numbers of iris images obtained by different studies and to perform large meta-studies that may reveal loci with small effects on the eye colour.

SNP model development for the prediction of eye colour in New Zealand

The ability to predict externally visible characteristics (EVCs) from DNA has appeal for use in forensic science, particularly where a forensic database match is not made and an eye witness account is unavailable. This technology has yet to be implemented in casework in New Zealand. The broad cultural diversity and likely population stratification within New Zealand dictates that any EVC predictions made using anonymous DNA must perform accurately in the absence of knowledge of the donor's ancestral background. Here we construct classification tree models with SNPs of known association with eye colour phenotypes in three categories, blue vs. non-blue, brown vs. non-brown and intermediate vs. non-intermediate. A set of nineteen SNPs from ten different known or suspected pigmentation genes were selected from the literature. A training dataset of 101 unrelated individuals from the New Zealand population and representing different ancestral backgrounds were used. We constructed four alternate models capable of predicting eye colour from the DNA genotypes of SNPs located within the HERC2, OCA2, TYR and SLC24A4 genes using probability calculation and classification trees. The final model selected for eye colour prediction exhibited high levels of accuracy for both blue (89%) and brown eye colour (94%). Models were further assessed with a test set of 25 'blind' samples where phenotype was unknown, with blue and brown eye colour predicted correctly where model thresholds were met. Classification trees offer an aesthetically simple and comprehendible model to predict blue and brown eye colour.

Genetic Architecture of Skin and Eye Color in an African-European Admixed Population

Variation in human skin and eye color is substantial and especially apparent in admixed populations, yet the underlying genetic architecture is poorly understood because most genome-wide studies are based on individuals of European ancestry. We study pigmentary variation in 699 individuals from Cape Verde, where extensive West African/European admixture has given rise to a broad range in trait values and genomic ancestry proportions. We develop and apply a new approach for measuring eye color, and identify two major loci (HERC2[OCA2] P = 2.3×10−62, SLC24A5 P = 9.6×10−9) that account for both blue versus brown eye color and varying intensities of brown eye color. We identify four major loci (SLC24A5 P = 5.4×10−27, TYR P = 1.1×10−9, APBA2[OCA2] P = 1.5×10−8, SLC45A2 P = 6×10−9) for skin color that together account for 35% of the total variance, but the genetic component with the largest effect (∼44%) is average genomic ancestry. Our results suggest that adjacent cis-acting regulatory loci for OCA2 explain the relationship between skin and eye color, and point to an underlying genetic architecture in which several genes of moderate effect act together with many genes of small effect to explain ∼70% of the estimated heritability.

Bona fide colour: DNA prediction of human eye and hair colour from ancient and contemporary skeletal remains

BackgroundDNA analysis of ancient skeletal remains is invaluable in evolutionary biology for exploring the history of species, including humans. Contemporary human bones and teeth, however, are relevant in forensic DNA analyses that deal with the identification of perpetrators, missing persons, disaster victims or family relationships. They may also provide useful information towards unravelling controversies that surround famous historical individuals. Retrieving information about a deceased person’s externally visible characteristics can be informative in both types of DNA analyses. Recently, we demonstrated that human eye and hair colour can be reliably predicted from DNA using the HIrisPlex system. Here we test the feasibility of the novel HIrisPlex system at establishing eye and hair colour of deceased individuals from skeletal remains of various post-mortem time ranges and storage conditions.MethodsTwenty-one teeth between 1 and approximately 800 years of age and 5 contemporary bones were subjected to DNA extraction using standard organic protocol followed by analysis using the HIrisPlex system.ResultsTwenty-three out of 26 bone DNA extracts yielded the full 24 SNP HIrisPlex profile, therefore successfully allowing model-based eye and hair colour prediction. HIrisPlex analysis of a tooth from the Polish general Władysław Sikorski (1881 to 1943) revealed blue eye colour and blond hair colour, which was positively verified from reliable documentation. The partial profiles collected in the remaining three cases (two contemporary samples and a 14th century sample) were sufficient for eye colour prediction.ConclusionsOverall, we demonstrate that the HIrisPlex system is suitable, sufficiently sensitive and robust to successfully predict eye and hair colour from ancient and contemporary skeletal remains. Our findings, therefore, highlight the HIrisPlex system as a promising tool in future routine forensic casework involving skeletal remains, including ancient DNA studies, for the prediction of eye and hair colour of deceased individuals.

The genetics of eye colours in an Italian population measured with an objective method for eye colour quantification

Brown and blue eye colours are primarily explained by the single nucleotide polymorphism (SNP) HERC2 rs12913832. However, the genetics of eye colours that appear to be neither blue nor brown are not well understood. In this study, 230 unrelated Italian individuals were typed for 32 SNP loci in pigmentary genes. High resolution digital images of the participants’ eyes were taken and the iris region was successfully extracted with the use of the custom designed software Digital Iris Analysis Tool (DIAT) from 218 of the 230 (95%) images. The software counted the numbers of blue and brown pixels in the iris region and calculated a Pixel Index of the Eye (PIE-score) that described the eye colours quantitatively. The PIE-score ranged from −1 to 1 (brown to blue). We investigated the association of the PIE-scores extracted from the eye images with the genotypes of the 32 pigmentary SNPs. We observed a statistically significant association between the PIE-scores and the SNP loci rs12913832, rs4778241, rs7495174 in the HERC2/OCA2 region and the locus rs16891982 in SLC45A2.