Association of polymorphic sites in the OCA2 gene with eye colour using the tree scanning method

Survival in uveal melanoma patients is linked to genetic variation at HERC2 SNP rs12913832

PURPOSE

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

DESIGN

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

SUBJECTS

392 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 six eye colour SNPs from the HIrisPlex-S assay. The genotypes extracted from the sequencing data were uploaded onto the Hirisplex webtool (https://hirisplex.erasmusmc.nl/) for eye colour prediction. We tested the association of eye colour SNPs with tumour characteristics and chromosome aberrations using Pearson's chi-square test and Mann-Whitney U test and survival with Kaplan-Meier curves with log-rank test and Cox regression.

MAIN OUTCOME MEASURES

UM-related survival.

RESULTS

Of the total cohort of 392 patients with analysable genotype data, 307 (78%) were assigned to have blue eyes, 74 (19%) brown eyes and 11 (3%) could not be assigned to either blue or brown. Patients with a genetically-blue eye colour had a worse survival (p = 0.04). This was related to one genotype: patients with the G/G genotype of rs12913832 (HERC2) which codes for blue eye colour had a worse prognosis (p = 0.017), which was related to more often having high-risk tumours (monosomy of chromosome 3, p = 0.04) than patients with an A/G or A/A genotype.

CONCLUSION

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

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

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

Optimizing the genetic prediction of the eye and hair color for North Eurasian populations

Background

Predicting the eye and hair color from genotype became an established and widely used tool in forensic genetics, as well as in studies of ancient human populations. However, the accuracy of this tool has been verified on the West and Central Europeans only, while populations from border regions between Europe and Asia (like Caucasus and Ural) also carry the light pigmentation phenotypes.

Results

We phenotyped 286 samples collected across North Eurasia, genotyped them by the standard HIrisPlex-S markers and found that predictive power in Caucasus/Ural/West Siberian populations is reasonable but lower than that in West Europeans. As these populations have genetic ancestries different from that of West Europeans, we hypothesized they may carry a somewhat different allele spectrum. Thus, for all samples we performed the exome sequencing additionally enriched with the 53 genes and intergenic regions known to be associated with the eye/hair color. Our association analysis replicated the importance of the key previously known SNPs but also identified five new markers whose eye color prediction power for the studied populations is compatible with the two major previously well-known SNPs. Four out of these five SNPs lie within the HERС2 gene and the fifth in the intergenic region. These SNPs are found at high frequencies in most studied populations. The released dataset of exomes from Russian populations can be further used for population genetic and medical genetic studies.

Conclusions

This study demonstrated that precision of the established systems for eye/hair color prediction from a genotype is slightly lower for the populations from the border regions between Europe and Asia that for the West Europeans. However, this precision can be improved if some newly revealed predictive SNPs are added into the panel. We discuss that the replication of these pigmentation-associated SNPs on the independent North Eurasian sample is needed in the future studies.

The accuracy of predicting eye and hair pigmentation based on genetic markers in Russian populations

Prediction of eye and hair color from DNA is being increasingly employed in forensics and the studies of ancient populations. HIrisPlex-S is a prediction tool trained on the Dutch dataset and verified using a few other European populations. The accuracy of its predictions for other regions of the world has not been studied yet. Russian populations pose a special interest because, unlike the majority of world populations, their representatives can have not only dark but also light color eyes and hair. The aim of this work was to evaluate the accuracy of eye and hair color prediction in Russian populations. We recruited 144 representatives of indigenous peoples of Russia (Avar, Aleut, Buryat, Itelmen, Karelian, Koryak, Mari, Nanai, Russian, Rutulian, Chuvash, Chukchi, Evenk, and Even populations). All study participants were photographed. Eye and hair colors were identified from the anthropological images by anthropologists. The SNP markers included in the HIrisPlex system were genotyped. Phenotypes were predicted from the obtained genotypes and subsequently compared to the actual phenotypes. Quality metrics were calculated for HIrisPlex prediction accuracy in the populations of European Russia and Siberia. On the whole, HIrisPlex prediction accuracy was satisfactory, although a bit lower than in Western European datasets. Further research could focus on identifying additional markers to improve the accuracy of predictions in Russian populations.

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.

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.

A Practical Guide to the HIrisPlex System: Simultaneous Prediction of Eye and Hair Color from DNA

The HIrisPlex system, which consists of two parts, allows the simultaneous prediction of eye and hair color from DNA, e.g., samples extracted from crime scene evidence. The first part is a highly sensitive multiplex genotyping assay consisting of 24 DNA markers using SNaPshot™ chemistry, for analysis on all Capillary Electrophoresis machines. The second part consists of statistical models that respectively establish eye and hair color prediction probabilities from complete and incomplete genotype profiles using parameters generated from large genotype and phenotype databases. This combined prediction tool constitutes the online system freely available to users. Here we provide a practical guide on how to use the HIrisPlex system for forensic and other DNA applications.

Genetic differences among ethnic groups

BACKGROUND

Many differences between different ethnic groups have been observed, such as skin color, eye color, height, susceptibility to some diseases, and response to certain drugs. However, the genetic bases of such differences have been under-investigated. Since the HapMap project, large-scale genotype data from Caucasian, African and Asian population samples have been available. The project found that these populations were located in different areas of the PCA (Principal Component Analysis) plot. However, as an unsupervised method, PCA does not measure the differences in each single nucleotide polymorphism (SNP) among populations.

RESULTS

We applied an advanced mutual information-based feature selection method to detect associations between SNP status and ethnic groups using the latest HapMap Phase 3 release version 3, which included more sub-populations. A total of 299 SNPs were identified, and they can accurately predicted the ethnicity of all HapMap populations. The 10-fold cross validation accuracy of the SMO (sequential minimal optimization) model on training dataset was 0.901, and the accuracy on independent test dataset was 0.895.

CONCLUSIONS

In-depth functional analysis of these SNPs and their nearby genes revealed the genetic bases of skin and eye color differences among populations.

Assay Development and Validation of an 8-SNP Multiplex Test to Predict Eye and Skin Coloration

Identifying human remains is one of the many responsibilities of forensic scientists. An eye- and skin-color predictor translates genotypic information into phenotypic description. Eight single nucleotide polymorphisms (SNPs) are utilized for this predictor, five for eye, and six for skin coloration. Here, we describe the development and validation of an 8-SNP multiplex assay that consists of a multiplex PCR, followed by a multiplexed single-base primer extension reaction generating fluorescently labeled oligonucleotides of distinct length that are detected by multicolor capillary electrophoresis. Validation of this assay included tests for reproducibility, reliability, sensitivity, species specificity, its performance on degraded DNA, and on forensic samples. It can be concluded that the 8-SNP multiplex assay is robust and can be used on challenging samples, including bones, to reliably determine the genotypes to predict eye and skin color of individuals. This information can assist in the identification of human remains and missing persons.

Developmental validation of the HIrisPlex system: DNA-based eye and hair colour prediction for forensic and anthropological usage

Forensic DNA Phenotyping or 'DNA intelligence' tools are expected to aid police investigations and find unknown individuals by providing information on externally visible characteristics of unknown suspects, perpetrators and missing persons from biological samples. This is especially useful in cases where conventional DNA profiling or other means remain non-informative. Recently, we introduced the HIrisPlex system, capable of predicting both eye and hair colour from DNA. In the present developmental validation study, we demonstrate that the HIrisPlex assay performs in full agreement with the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines providing an essential prerequisite for future HIrisPlex applications to forensic casework. The HIrisPlex assay produces complete profiles down to only 63 pg of DNA. Species testing revealed human specificity for a complete HIrisPlex profile, while only non-human primates showed the closest full profile at 20 out of the 24 DNA markers, in all animals tested. Rigorous testing of simulated forensic casework samples such as blood, semen, saliva stains, hairs with roots as well as extremely low quantity touch (trace) DNA samples, produced complete profiles in 88% of cases. Concordance testing performed between five independent forensic laboratories displayed consistent reproducible results on varying types of DNA samples. Due to its design, the assay caters for degraded samples, underlined here by results from artificially degraded DNA and from simulated casework samples of degraded DNA. This aspect was also demonstrated previously on DNA samples from human remains up to several hundreds of years old. With this paper, we also introduce enhanced eye and hair colour prediction models based on enlarged underlying databases of HIrisPlex genotypes and eye/hair colour phenotypes (eye colour: N = 9188 and hair colour: N = 1601). Furthermore, we present an online web-based system for individual eye and hair colour prediction from full and partial HIrisPlex DNA profiles. By demonstrating that the HIrisPlex assay is fully compatible with the SWGDAM guidelines, we provide the first forensically validated DNA test system for parallel eye and hair colour prediction now available to forensic laboratories for immediate casework application, including missing person cases. Given the robustness and sensitivity described here and in previous work, the HIrisPlex system is also suitable for analysing old and ancient DNA in anthropological and evolutionary studies.

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.

Gender is a major factor explaining discrepancies in eye colour prediction based on HERC2/OCA2 genotype and the IrisPlex model

In recent years, several studies have greatly increased our understanding of the genetic basis underlying human eye colour variation. A large percentage of the eye colour diversity present in humans can already be genetically explained, so much so that different DNA-based eye colour prediction models, such as IrisPlex, have been recently developed for forensic purposes. Though these models are already highly accurate, they are by no means perfect, with many genotype-phenotype discrepancies still remaining unresolved. In this work we have genotyped six SNPs associated with eye colour (IrisPlex) in 535 individuals from Spain, a Mediterranean population. Aside from different SNP frequencies in Spain compared to Northern Europe, the results for eye colour prediction are quite similar to other studies. However, we have found an association between gender and eye colour prediction. When comparing similar eye colour genetic profiles, females tend, as a whole, to have darker eyes than males (and, conversely, males lighter than females). These results are also corroborated by the revision and meta-analysis of data from previously published eye colour genetic studies in several Caucasian populations, which significantly support the fact that males are more likely to have blue eyes than females, while females tend to show higher frequencies of green and brown eyes than males. This significant gender difference would suggest that there is an as yet unidentified gender-related factor contributing to human eye colour variation.

Prediction of people's origin from degraded DNA--presentation of SNP assays and calculation of probability

The characterization of externally visible traits by DNA analysis is already an important tool when investigating ancient skeletal remains and may gain similar importance in future forensic DNA analysis. This, however, depends on the different legal regulations in the different countries. Besides eye or hair color, the population origin can provide crucial information in criminal prosecution. In this study, we present the analysis of 16 single-nucleotide polymorphisms (SNPs) combined to two robust SNaPshot assays with a detection threshold of 25-pg DNA. This assay was applied to 891 people from seven different populations (West Africa, North Africa, Turkey, Near East, Balkan states, North Europe, and Japan) with a thorough statistical evaluation. The prediction model was validated by an additional 125 individuals predominantly with an ancestry from those same regions. The specificity of these SNPs for the prediction of all population origins is very high (>90 %), but the sensitivity varied greatly (more than 90 % for West Africa, but only 25 % for the Near East). We could identify West Africans with a certainty of 100 %, and people from North Africa, the Balkan states, or North Europe nearly with the same reliability while determination of Turks or people from the Near East was rather difficult. In conclusion, the two SNaPshot assays are a powerful and reliable tool for the identification of people with an ancestry in one of the above listed populations, even from degraded DNA.

The HIrisPlex system for simultaneous prediction of hair and eye colour from DNA

Recently, the field of predicting phenotypes of externally visible characteristics (EVCs) from DNA genotypes with the final aim of concentrating police investigations to find persons completely unknown to investigating authorities, also referred to as Forensic DNA Phenotyping (FDP), has started to become established in forensic biology. We previously developed and forensically validated the IrisPlex system for accurate prediction of blue and brown eye colour from DNA, and recently showed that all major hair colour categories are predictable from carefully selected DNA markers. Here, we introduce the newly developed HIrisPlex system, which is capable of simultaneously predicting both hair and eye colour from DNA. HIrisPlex consists of a single multiplex assay targeting 24 eye and hair colour predictive DNA variants including all 6 IrisPlex SNPs, as well as two prediction models, a newly developed model for hair colour categories and shade, and the previously developed IrisPlex model for eye colour. The HIrisPlex assay was designed to cope with low amounts of template DNA, as well as degraded DNA, and preliminary sensitivity testing revealed full DNA profiles down to 63pg input DNA. The power of the HIrisPlex system to predict hair colour was assessed in 1551 individuals from three different parts of Europe showing different hair colour frequencies. Using a 20% subset of individuals, while 80% were used for model building, the individual-based prediction accuracies employing a prediction-guided approach were 69.5% for blond, 78.5% for brown, 80% for red and 87.5% for black hair colour on average. Results from HIrisPlex analysis on worldwide DNA samples imply that HIrisPlex hair colour prediction is reliable independent of bio-geographic ancestry (similar to previous IrisPlex findings for eye colour). We furthermore demonstrate that it is possible to infer with a prediction accuracy of >86% if a brown-eyed, black-haired individual is of non-European (excluding regions nearby Europe) versus European (including nearby regions) bio-geographic origin solely from the strength of HIrisPlex eye and hair colour probabilities, which can provide extra intelligence for future forensic applications. The HIrisPlex system introduced here, including a single multiplex test assay, an interactive tool and prediction guide, and recommendations for reporting final outcomes, represents the first tool for simultaneously establishing categorical eye and hair colour of a person from DNA. The practical forensic application of the HIrisPlex system is expected to benefit cases where other avenues of investigation, including STR profiling, provide no leads on who the unknown crime scene sample donor or the unknown missing person might be.

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

The ability to predict Externally Visible Characteristics (EVCs) from DNA, also referred to as Forensic DNA Phenotyping (FDP), is an exciting new chapter in forensic genetics holding great promise for tracing unknown individuals who are unidentifiable via standard forensic short tandem repeat (STR) profiling. For the purpose of DNA-based eye colour prediction, we previously developed the IrisPlex system consisting of a multiplex genotyping assay and a prediction model based on genotype and phenotype data from 3804 Dutch Europeans. Recently, we performed a forensic developmental validation study of the highly sensitive IrisPlex assay, which currently represents the only validated tool available for DNA-based prediction of eye colour in forensic applications. In the present study, we validate the IrisPlex prediction model by extending our initially described model towards genotype and phenotype data from multiple European populations. We performed IrisPlex analysis on 3840 individuals from seven sites across Europe as part of the European Eye (EUREYE) study for which DNA and high-resolution eye images were available. The accuracy rate of correctly predicting an individual's eye colour as being blue or brown, above the empirically established probability threshold of 0.7, was on average 94% across all seven European populations, ranging from 91% to 98%, despite the large variation in eye colour frequencies between the populations. The overall prediction accuracies expressed by the area under the receiver characteristic operating curves (AUC) were 0.96 for blue and 0.96 for brown eyes, which is considerably higher than those established before. The IrisPlex prediction model parameters generated from this multi-population European dataset, and thus its prediction capabilities, were highly comparable to those previously established. Therefore, the increased information regarding eye colour phenotype and genotype distributions across Europe, and the system's ability to provide eye colour predictions across Europe accurately, both highlight additional evidence for the utility of the IrisPlex system in forensic casework.

Gene-gene interactions contribute to eye colour variation in humans

Prediction of phenotypes from genetic data is considered to be the first practical application of data gained from association studies, with potential importance for medicine and the forensic sciences. Multiple genes and polymorphisms have been found to be associated with variation in human pigmentation. Their analysis enables prediction of blue and brown eye colour with a reasonably high accuracy. More accurate prediction, especially in the case of intermediate eye colours, may require better understanding of gene-gene interactions affecting this polygenic trait. Using multifactor dimensionality reduction and logistic regression methods, a study of gene-gene interactions was conducted based on variation in 11 known pigmentation genes examined in a cohort of 718 individuals of European descent. The study revealed significant interactions of a redundant character between the HERC2 and OCA2 genes affecting determination of hazel eye colour and between HERC2 and SLC24A4 affecting determination of blue eye colour. Our research indicates interactive effects of a synergistic character between HERC2 and OCA2, and also provides evidence for a novel strong synergistic interaction between HERC2 and TYRP1, both affecting determination of green eye colour.

Model-based prediction of human hair color using DNA variants

Predicting complex human phenotypes from genotypes is the central concept of widely advocated personalized medicine, but so far has rarely led to high accuracies limiting practical applications. One notable exception, although less relevant for medical but important for forensic purposes, is human eye color, for which it has been recently demonstrated that highly accurate prediction is feasible from a small number of DNA variants. Here, we demonstrate that human hair color is predictable from DNA variants with similarly high accuracies. We analyzed in Polish Europeans with single-observer hair color grading 45 single nucleotide polymorphisms (SNPs) from 12 genes previously associated with human hair color variation. We found that a model based on a subset of 13 single or compound genetic markers from 11 genes predicted red hair color with over 0.9, black hair color with almost 0.9, as well as blond, and brown hair color with over 0.8 prevalence-adjusted accuracy expressed by the area under the receiver characteristic operating curves (AUC). The identified genetic predictors also differentiate reasonably well between similar hair colors, such as between red and blond-red, as well as between blond and dark-blond, highlighting the value of the identified DNA variants for accurate hair color prediction.

Prediction of eye and skin color in diverse populations using seven SNPs

An essential component in identifying human remains is the documentation of the decedent's visible characteristics, such as eye, hair and skin color. However, if a decedent is decomposed or only skeletal remains are found, this critical, visibly identifying information is lost. It would be beneficial to use genetic information to reveal these visible characteristics. In this study, seven single nucleotide polymorphisms (SNPs), located in and nearby genes known for their important role in pigmentation, were validated on 554 samples, donated from non-related individuals of various populations. Six SNPs were used in predicting the eye color of an individual, and all seven were used to describe the skin coloration. The outcome revealed that these markers can be applied to all populations with very low error rates. However, the call-rate to determine the skin coloration varied between populations, demonstrating its complexity. Overall, these results prove the importance of these seven SNPs for potential forensic tests.

Human eye colour and HERC2, OCA2 and MATP

Prediction of human eye colour by forensic genetic methods is of great value in certain crime investigations. Strong associations between blue/brown eye colour and the SNP loci rs1129038 and rs12913832 in the HERC2 gene were recently described. Weaker associations between eye colour and other genetic markers also exist. In 395 randomly selected Danes, we investigated the predictive values of various combinations of SNP alleles in the HERC2, OCA2 and MATP (SLC45A2) genes and compared the results to the eye colours as they were described by the individuals themselves. The highest predictive value of typing either the HERC2 SNPs rs1129038 and/or rs12913832 that are in strong linkage disequilibrium was observed when eye colour was divided into two groups, (1) blue, grey and green (light) and (2) brown and hazel (dark). Sequence variations in rs11636232 and rs7170852 in HERC2, rs1800407 in OCA2 and rs16891982 in MATP showed additional association with eye colours in addition to the effect of HERC2 rs1129038. Diplotype analysis of three sequence variations in HERC2 and one sequence variation in OCA2 showed the best discrimination between light and dark eye colours with a likelihood ratio of 29.3.

Genetics of human iris colour and patterns

The presence of melanin pigment within the iris is responsible for the visual impression of human eye colouration with complex patterns also evident in this tissue, including Fuchs' crypts, nevi, Wolfflin nodules and contraction furrows. The genetic basis underlying the determination and inheritance of these traits has been the subject of debate and research from the very beginning of quantitative trait studies in humans. Although segregation of blue-brown eye colour has been described using a simple Mendelian dominant-recessive gene model this is too simplistic, and a new molecular genetic perspective is needed to fully understand the biological complexities of this process as a polygenic trait. Nevertheless, it has been estimated that 74% of the variance in human eye colour can be explained by one interval on chromosome 15 that contains the OCA2 gene. Fine mapping of this region has identified a single base change rs12913832 T/C within intron 86 of the upstream HERC2 locus that explains almost all of this association with blue-brown eye colour. A model is presented whereby this SNP, serving as a target site for the SWI/SNF family member HLTF, acts as part of a highly evolutionary conserved regulatory element required for OCA2 gene activation through chromatin remodelling. Major candidate genes possibly effecting iris patterns are also discussed, including MITF and PAX6.

Interactions between HERC2, OCA2 and MC1R may influence human pigmentation phenotype

Human pigmentation is a polygenic trait which may be shaped by different kinds of gene-gene interactions. Recent studies have revealed that interactive effects between HERC2 and OCA2 may be responsible for blue eye colour determination in humans. Here we performed a population association study, examining important polymorphisms within the HERC2 and OCA2 genes. Furthermore, pooling these results with genotyping data for MC1R, ASIP and SLC45A2 obtained for the same population sample we also analysed potential genetic interactions affecting variation in eye, hair and skin colour. Our results confirmed the association of HERC2 rs12913832 with eye colour and showed that this SNP is also significantly associated with skin and hair colouration. It is also concluded that OCA2 rs1800407 is independently associated with eye colour. Finally, using various approaches we were able to show that there is an interaction between MC1R and HERC2 in determination of skin and hair colour in the studied population sample.

Association of the SLC45A2 gene with physiological human hair colour variation

Pigmentation is a complex physical trait with multiple genes involved. Several genes have already been associated with natural differences in human pigmentation. The SLC45A2 gene encoding a transporter protein involved in melanin synthesis is considered to be one of the most important genes affecting human pigmentation. Here we present results of an association study conducted on a population of European origin, where the relationship between two non-synonymous polymorphisms in the SLC45A2 gene - rs26722 (E272K) and rs16891982 (L374F) - and different pigmentation traits was examined. The study revealed a significant association between both variable sites and normal variation in hair colour. Only L374F remained significantly associated with hair colour when both SNPs were included in a logistic regression model. No association with other pigmentation traits was detected in this population sample. Our results indicate that the rare allele L374 significantly increases the possibility of having black hair colour (OR = 7.05) and thus may be considered as a future marker for black hair colour prediction.