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

Uveal melanoma: Current evidence on prognosis, treatment and potential developments

Uveal Melanoma (UM) is a rare disease, yet it is the most common primary intraocular malignancy in adult patients. Despite continuous advancements and research, the risk of metastasis remains high. It is possible to stratify patients according to their risk of metastases using a variety of known risk factors. Even though there is no gold standard for the prognostication of patients with uveal melanoma, it is becoming increasingly clear that combining histo-pathological, patient-related and molecular prognostic markers allows a more accurate prediction of the metastatic risk than by using one parameter. Primary UM in the eye are treated very effectively with eye-sparing radiation-based techniques or enucleation. However, it is not yet possible to prevent or treat metastases with the current therapeutic options. Nonetheless, the efforts to find new therapeutic targets continue and progress is being made, especially in the field of targeted therapy, as exemplified by the anti-gp100 bispecific molecule Tebentafusp. This review delves into the history of uveal melanoma, its incidence, presentation and diagnosis, the known prognostic factors and the treatment options, both for the primary tumour and for metastases. We show that different populations may have different risks for developing UM, and that each country should evaluate their own patients.

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

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A Comprehensive Review of Mammalian Pigmentation: Paving the Way for Innovative Hair Colour-Changing Cosmetics

The natural colour of hair shafts is formed at the bulb of hair follicles, and it is coupled to the hair growth cycle. Three critical processes must happen for efficient pigmentation: (1) melanosome biogenesis in neural crest-derived melanocytes, (2) the biochemical synthesis of melanins (melanogenesis) inside melanosomes, and (3) the transfer of melanin granules to surrounding pre-cortical keratinocytes for their incorporation into nascent hair fibres. All these steps are under complex genetic control. The array of natural hair colour shades are ascribed to polymorphisms in several pigmentary genes. A myriad of factors acting via autocrine, paracrine, and endocrine mechanisms also contributes for hair colour diversity. Given the enormous social and cosmetic importance attributed to hair colour, hair dyeing is today a common practice. Nonetheless, the adverse effects of the long-term usage of such cosmetic procedures demand the development of new methods for colour change. In this context, case reports of hair lightening, darkening and repigmentation as a side-effect of the therapeutic usage of many drugs substantiate the possibility to tune hair colour by interfering with the biology of follicular pigmentary units. By scrutinizing mammalian pigmentation, this review pinpoints key targetable processes for the development of innovative cosmetics that can safely change the hair colour from the inside out.

Advancement in Human Face Prediction Using DNA

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

A genome-wide epistatic network underlies the molecular architecture of continuous color variation of body extremities

Deciphering the molecular architecture of coat coloration for a better understanding of the biological mechanisms underlying pigmentation still remains a challenge. We took advantage of a rabbit French experimental population in which both a pattern and a gradient of coloration from white to brown segregated within the himalayan phenotype. The whole experimental design was genotyped using the high density Affymetrix® AxiomOrcun™ SNP Array and phenotyped into 6 different groups ordered from the lighter to the darker. Genome-wide association analyses pinpointed an oligogenic determinism, under recessive and additive inheritance, involving genes already known in melanogenesis (ASIP, KIT, MC1R, TYR), and likely processed pseudogenes linked to ribosomal function, RPS20 and RPS14. We also identified (i) gene-gene interactions through ASIP:MC1R affecting light cream/beige phenotypes while KIT:RPS responsible of dark chocolate/brown colors and (ii) a genome-wide epistatic network involving several others coloration genes such as POT1 or HPS5. Finally, we determined the recessive inheritance of the English spotting phenotype likely involving a copy number variation affecting at least the end of the coding sequence of the KIT gene. Our analyses of coloration as a continuous trait allowed us to go beyond much of the established knowledge through the detection of additional genes and gene-gene interactions that may contribute to the molecular architecture of the coloration phenotype.

Study on the Correlation Between Iris Characteristics and Schizophrenia

BACKGROUND

Recently, researchers have conducted many studies on the potential contribution of the retina and other eye structures on schizophrenia. This study aimed to evaluate differences in iris characteristics between patients with schizophrenia and healthy individuals so as to find more easily accessible and easily measurable biomarkers with a view to improving clinical assessments and furthering our understanding of the disease.

METHODS

Overall, 80 patients with schizophrenia and 52 healthy individuals were included in the case group and the control group, respectively. Iris images were collected from all subjects to compare differences in the structure and color of the iris. The Positive and Negative Symptom Scale (PANSS) and the Modified Overt Aggression Scale (MOAS) were used to evaluate the clinical symptoms and characteristics of 45 first-episode untreated schizophrenics, and analyzed correlations between iris characteristics and schizophrenia symptoms.

RESULTS

There were significant differences in iris crypts (P<0.05) and pigment spots (P<0.01) between the case and control group, but no significant difference was found in iris wrinkles (P<0.05). The logistic regression analysis demonstrated that the total iris crypts [odds ratio (OR) 1.166, 95% confidence interval (CI) 1.022-1.330] and total iris pigment spots (OR 1.815, 95% CI 1.186-2.775) increased the risk of suffering from schizophrenia. Furthermore, it was demonstrated that the number of iris crypts was positively associated with the MOAS score (r=0.474, P<0.01). Moreover, the number of the iris pigment spots (r=0.395, P<0.01) and wrinkles (r=0.309, P<0.05) were positively correlated with the subjects' negative symptom scores, respectively.

CONCLUSION

Iris crypts and pigment spots were identified as potential biomarkers for detecting schizophrenia. In patients with first-episode untreated schizophrenia, iris characteristics may help psychiatrists to identify the illness and its severity, and to detect characteristic clinical symptoms.

Evolutionary genetics of skin pigmentation in African populations

Skin color is a highly heritable human trait, and global variation in skin pigmentation has been shaped by natural selection, migration and admixture. Ethnically diverse African populations harbor extremely high levels of genetic and phenotypic diversity, and skin pigmentation varies widely across Africa. Recent genome-wide genetic studies of skin pigmentation in African populations have advanced our understanding of pigmentation biology and human evolutionary history. For example, novel roles in skin pigmentation for loci near MFSD12 and DDB1 have recently been identified in African populations. However, due to an underrepresentation of Africans in human genetic studies, there is still much to learn about the evolutionary genetics of skin pigmentation. Here, we summarize recent progress in skin pigmentation genetics in Africans and discuss the importance of including more ethnically diverse African populations in future genetic studies. In addition, we discuss methods for functional validation of adaptive variants related to skin pigmentation.

Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation

Human pigmentation is a highly diverse and complex trait among populations and has drawn particular attention from both academic and non-academic investigators for thousands of years. Previous studies detected selection signals in several human pigmentation genes, but few studies have integrated contribution from multiple genes to the evolution of human pigmentation. Moreover, none has quantified selective pressures on human pigmentation over epochs and between populations. Here, we dissect dynamics and differences of selective pressures during different periods and between distinct populations with new approaches. We use genotype data of 19 genes associated with human pigmentation from 17 publicly available datasets and obtain data for 2346 individuals of six representative population groups from across the world. Our results quantify the strength of natural selection on light pigmentation not only in modern Europeans (0.0259/generation) but also in proto-Eurasians (0.00650/generation). Our results also suggest that several derived alleles associated with human dark pigmentation may be under positive directional selection in some African populations. Our study provides the first attempt to quantitatively investigate the dynamics of selective pressures during different time periods in the evolution of human pigmentation.This article has an associated First Person interview with the first author of the article.

Inbreeding coefficients and runs of homozygosity islands in Brazilian water buffalo

Characterization of autozygosity is relevant to monitor genetic diversity and manage inbreeding levels in breeding programs. Identification of autozygosity hotspots can unravel genomic regions targeted by selection for economically important traits and can help identify candidate genes for selection. In this study, we estimated the inbreeding levels of a Brazilian population of Murrah buffalo undergoing selection for milk production traits, particularly milk yield. We also studied the distribution of runs of homozygosity (ROH) islands and identified putative genes and quantitative trait loci (QTL) under selection. We genotyped 422 Murrah buffalo for 51,611 SNP; 350 of these had ROH longer than 10 Mb, indicating the occurrence of inbreeding in the last 5 generations. The mean length of the ROH per animal was 4.28 ± 1.85 Mb. Inbreeding coefficients were calculated from the genomic relationship matrix, the pedigree, and the ROH, with estimates varying between 0.242 and 0.035. Inbreeding estimates from the pedigree had a low correlation with the genomic estimates, and estimates from the genomic relationship matrix were much higher than those from the pedigree or the ROH. Signatures of selection were identified in 6 genomic regions, located on chromosomes 1, 2, 3, 5, 16, and 18, encompassing a total of 190 genes and 174 QTL. Many of the genes (e.g., APRT and ACSF3) and QTL identified are related to milk production traits, such as milk yield, milk fat yield and percentage, and milk protein yield and percentage. Other genes are associated with reproduction and immune response traits as well as morphological aspects of the buffalo species. Inbreeding levels in this population are still low but are increasing due to selection and should be managed to avoid future losses due to inbreeding depression. The proximity of genes linked to milk production traits with genes associated with reproduction and immune system traits suggests the need to include these latter genes in the breeding program to avoid negatively affecting them due to selection for production traits.

Predicting target genes of non-coding regulatory variants with IRT

SUMMARY

Interpreting genetic variants of unknown significance (VUS) is essential in clinical applications of genome sequencing for diagnosis and personalized care. Non-coding variants remain particularly difficult to interpret, despite making up a large majority of trait associations identified in genome-wide association studies (GWAS) analyses. Predicting the regulatory effects of non-coding variants on candidate genes is a key step in evaluating their clinical significance. Here, we develop a machine-learning algorithm, Inference of Connected expression quantitative trait loci (eQTLs) (IRT), to predict the regulatory targets of non-coding variants identified in studies of eQTLs. We assemble datasets using eQTL results from the Genotype-Tissue Expression (GTEx) project and learn to separate positive and negative pairs based on annotations characterizing the variant, gene and the intermediate sequence. IRT achieves an area under the receiver operating characteristic curve (ROC-AUC) of 0.799 using random cross-validation, and 0.700 for a more stringent position-based cross-validation. Further evaluation on rare variants and experimentally validated regulatory variants shows a significant enrichment in IRT identifying the true target genes versus negative controls. In gene-ranking experiments, IRT achieves a top-1 accuracy of 50% and top-3 accuracy of 90%. Salient features, including GC-content, histone modifications and Hi-C interactions are further analyzed and visualized to illustrate their influences on predictions. IRT can be applied to any VUS of interest and each candidate nearby gene to output a score reflecting the likelihood of regulatory effect on the expression level. These scores can be used to prioritize variants and genes to assist in patient diagnosis and GWAS follow-up studies.

AVAILABILITY AND IMPLEMENTATION

Codes and data used in this work are available at https://github.com/miaecle/eQTL_Trees.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

HERCing: Structural and Functional Relevance of the Large HERC Ubiquitin Ligases

Homologous to the E6AP carboxyl terminus (HECT) and regulator of chromosome condensation 1 (RCC1)-like domain-containing proteins (HERCs) belong to the superfamily of ubiquitin ligases. HERC proteins are divided into two subfamilies, Large and Small HERCs. Despite their similarities in terms of both structure and domains, these subfamilies are evolutionarily very distant and result from a convergence phenomenon rather than from a common origin. Large HERC genes, HERC1 and HERC2, are present in most metazoan taxa. They encode very large proteins (approximately 5,000 amino acid residues in a single polypeptide chain) that contain more than one RCC1-like domain as a structural characteristic. Accumulating evidences show that these unusually large proteins play key roles in a wide range of cellular functions which include neurodevelopment, DNA damage repair, and cell proliferation. To better understand the origin, evolution, and function of the Large HERC family, this minireview provides with an integrated overview of their structure and function and details their physiological implications. This study also highlights and discusses how dysregulation of these proteins is associated with severe human diseases such as neurological disorders and cancer.

Meta-analysis of GWA studies provides new insights on the genetic architecture of skin pigmentation in recently admixed populations

BACKGROUND

Association studies in recently admixed populations are extremely useful to identify the genetic architecture of pigmentation, due to their high genotypic and phenotypic variation. However, to date only four Genome-Wide Association Studies (GWAS) have been carried out in these populations.

RESULTS

We present a GWAS of skin pigmentation in an admixed sample from Cuba (N = 762). Additionally, we conducted a meta-analysis including the Cuban sample, and admixed samples from Cape Verde, Puerto Rico and African-Americans from San Francisco. This meta-analysis is one of the largest efforts so far to characterize the genetic basis of skin pigmentation in admixed populations (N = 2,104). We identified five genome-wide significant regions in the meta-analysis, and explored if the markers observed in these regions are associated with the expression of relevant pigmentary genes in human melanocyte cultures. In three of the regions identified in the meta-analysis (SLC24A5, SLC45A2, and GRM5/TYR), the association seems to be driven by non-synonymous variants (rs1426654, rs16891982, and rs1042602, respectively). The rs16891982 polymorphism is strongly associated with the expression of the SLC45A2 gene. In the GRM5/TYR region, in addition to the rs1042602 non-synonymous SNP located on the TYR gene, variants located in the nearby GRM5 gene have an independent effect on pigmentation, possibly through regulation of gene expression of the TYR gene. We also replicated an association recently described near the MFSD12 gene on chromosome 19 (lead variant rs112332856). Additionally, our analyses support the presence of multiple signals in the OCA2/HERC2/APBA2 region on chromosome 15. A clear causal candidate is the HERC2 intronic variant rs12913832, which has a profound influence on OCA2 expression. This variant has pleiotropic effects on eye, hair, and skin pigmentation. However, conditional and haplotype-based analyses indicate the presence of other variants with independent effects on melanin levels in OCA2 and APBA2. Finally, a follow-up of genome-wide signals identified in a recent GWAS for tanning response indicates that there is a substantial overlap in the genetic factors influencing skin pigmentation and tanning response.

CONCLUSIONS

Our meta-analysis of skin pigmentation GWAS in recently admixed populations provides new insights about the genetic architecture of this complex trait.

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

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

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

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

Genetic variants associated with skin photosensitivity in a southern European population from Spain

BACKGROUND/PURPOSE

Recent GWAS studies, mostly performed in populations of North European origin, have identified the genetic loci associated with pigmentation, sun sensitivity, freckling and skin cancer susceptibility. Here, we aimed at addressing the genetic determinants of sunlight sensitivity in Spain, a southern European population.

METHODS

Nine SNPs located in 8 pigmentation-related genes (IRF4, TYR, ASP, HERC2, OCA2, BNC2, SLC24A4 and SLC45A2) were genotyped in 456 Spaniards. Additionally, the complete sequence of the MC1R gene was obtained, testing each nonsynonymous mutation supported by the classification as R or r alleles. A standardised questionnaire was used to collect demographic characteristics, pigmentation and sun sensitivity traits, as well as sun exposure habits.

RESULTS

MC1R R alleles and IRF4 rs12203592 were significantly associated with sunlight sensitivity at the Bonferroni-corrected level (P-value < 4.54 × 10^-3 ). Genetic variants in SLC45A2 (rs16891982) and HERC2 (rs12913832) were also found to be significantly associated with skin photosensitivity in our Spanish sample. Interaction analysis using the MDR method revealed epistatic effects when these four variants were considered together.

CONCLUSION

MC1R, IRF4, HERC2 and SLC45A2 play a significant role in skin sensitivity to sunlight in the Spanish population. Moreover, interaction among these four loci seems to modulate the ability of the skin to respond to UV radiation.

Association of common genetic variants with human skin color variation in Indian populations

OBJECTIVES

Human skin color is one of the most conspicuously variable physical traits that has attracted the attention of physical anthropologists, social scientists and human geneticists. Although several studies have established the underlying genes and their variants affecting human skin color, they were mostly confined to Europeans and Africans and similar studies in Indian populations have been scanty. Studying the association between candidate genetic variants and skin color will help to validate previous findings and to better understand the molecular mechanism of skin color variation.

METHODS

In this study, 22 candidate SNPs from 12 genes were tested for association with skin color in 299 unrelated samples sourced from nine geographical locations in India.

RESULTS

Our study establishes the association of 9 SNPs with the phenotype in Indian populations and could explain ∼31% of the variance in skin color. Haplotype analysis of chromosome 15 revealed a significant association of alleles G, A and C of SNPs rs1426654, rs11070627, and rs12913316, respectively, to the phenotype, and accounted for 17% of the variance. Latitude of the sampling location was also a significant factor, contributing to ∼19% of the variation observed in the samples.

CONCLUSIONS

These observations support the findings that rs1426654 and rs4775730 located in SLC24A5, and rs11070627 and rs12913316 located in MYEF2 and CTXN2 genes respectively, are major contributors toward skin pigmentation and would aid in further unraveling the genotype-phenotype association in Indian populations. These findings can be utilized in forensic DNA applications for criminal investigations.

Recognizing Latinos' range of skin pigment and phototypes to enhance skin cancer prevention

Latinos in the United States may have the mistaken assumption that their natural pigmentation protects them from developing skin cancer that, effectively, serves as a barrier to Latinos receiving education in primary and secondary prevention of skin cancer. Latino adults of Mexican or Puerto Rican heritage attending community health fairs in the greater Chicago area responded to a culturally informed and sensitive measure for sunburn and tan, which was previously adapted to capture skin irritation with tenderness from the sun occurring in darker skin types (n = 350). By self-reported responses and spectrophotometry assessment of constitutive pigmentation, adapted Fitzpatrick skin types (FST) ranged from skin type I-IV in the Mexican American participants and from II to V in the Puerto Rican participants. The objectively measured proportion of adapted FST II skin type was greater than commonly perceived and demonstrated that many Latinos do indeed have sun-sensitive skin.

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.

Identification of a novel locus associated with skin colour in African-admixed populations

Skin pigmentation is a complex trait that varies largely among populations. Most genome-wide association studies of this trait have been performed in Europeans and Asians. We aimed to uncover genes influencing skin colour in African-admixed individuals. We performed a genome-wide association study of melanin levels in 285 Hispanic/Latino individuals from Puerto Rico, analyzing 14 million genetic variants. A total of 82 variants with p-value ≤1 × 10⁻⁵ were followed up in 373 African Americans. Fourteen single nucleotide polymorphisms were replicated, of which nine were associated with skin colour at genome-wide significance in a meta-analysis across the two studies. These results validated the association of two previously known skin pigmentation genes, SLC24A5 (minimum p = 2.62 × 10⁻¹⁴, rs1426654) and SLC45A2 (minimum p = 9.71 × 10⁻¹⁰, rs16891982), and revealed the intergenic region of BEND7 and PRPF18 as a novel locus associated with this trait (minimum p = 4.58 × 10⁻⁹, rs6602666). The most significant variant within this region is common among African-descent populations but not among Europeans or Native Americans. Our findings support the advantages of analyzing African-admixed populations to discover new genes influencing skin pigmentation.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.

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.

Human adaptation and population differentiation in the light of ancient genomes

The influence of positive selection sweeps in human evolution is increasingly debated, although our ability to detect them is hampered by inherent uncertainties in the timing of past events. Ancient genomes provide snapshots of allele frequencies in the past and can help address this question. We combine modern and ancient genomic data in a simple statistic (DAnc) to time allele frequency changes, and investigate the role of drift and adaptation in population differentiation. Only 30% of the most strongly differentiated alleles between Africans and Eurasians changed in frequency during the colonization of Eurasia, but in Europe these alleles are enriched in genic and putatively functional alleles to an extent only compatible with local adaptation. Adaptive alleles—especially those associated with pigmentation—are mostly of hunter-gatherer origin, although lactose persistence arose in a haplotype present in farmers. These results provide evidence for a role of local adaptation in human population differentiation.

Detecting the targets of positive selection in the human genome is challenging. Here, the authors combine modern and ancient genomes to show that alleles strongly differentiated between Africans and Europeans mediated local adaptation in European populations, and were mostly contributed by ancient hunter-gatherers.

Identification of Susceptibility Loci for Cutaneous Squamous Cell Carcinoma

We report a genome-wide association study of cutaneous squamous cell carcinoma conducted among non-Hispanic white members of the Kaiser Permanente Northern California health care system. The study includes a genome-wide screen of 61,457 members (6,891 cases and 54,566 controls) genotyped on the Affymetrix Axiom European array and a replication phase involving an independent set of 6,410 additional members (810 cases and 5,600 controls). Combined analysis of screening and replication phases identified 10 loci containing single-nucleotide polymorphisms (SNPs) with P-values < 5 × 10(-8). Six loci contain genes in the pigmentation pathway; SNPs at these loci appear to modulate squamous cell carcinoma risk independently of the pigmentation phenotypes. Another locus contains HLA class II genes studied in relation to elevated squamous cell carcinoma risk following immunosuppression. SNPs at the remaining three loci include an intronic SNP in FOXP1 at locus 3p13, an intergenic SNP at 3q28 near TP63, and an intergenic SNP at 9p22 near BNC2. These findings provide insights into the genetic factors accounting for inherited squamous cell carcinoma susceptibility.

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.

Testing for Ancient Selection Using Cross-population Allele Frequency Differentiation

A powerful way to detect selection in a population is by modeling local allele frequency changes in a particular region of the genome under scenarios of selection and neutrality and finding which model is most compatible with the data. A previous method based on a cross-population composite likelihood ratio (XP-CLR) uses an outgroup population to detect departures from neutrality that could be compatible with hard or soft sweeps, at linked sites near a beneficial allele. However, this method is most sensitive to recent selection and may miss selective events that happened a long time ago. To overcome this, we developed an extension of XP-CLR that jointly models the behavior of a selected allele in a three-population tree. Our method - called "3-population composite likelihood ratio" (3P-CLR) - outperforms XP-CLR when testing for selection that occurred before two populations split from each other and can distinguish between those events and events that occurred specifically in each of the populations after the split. We applied our new test to population genomic data from the 1000 Genomes Project, to search for selective sweeps that occurred before the split of Yoruba and Eurasians, but after their split from Neanderthals, and that could have led to the spread of modern-human-specific phenotypes. We also searched for sweep events that occurred in East Asians, Europeans, and the ancestors of both populations, after their split from Yoruba. In both cases, we are able to confirm a number of regions identified by previous methods and find several new candidates for selection in recent and ancient times. For some of these, we also find suggestive functional mutations that may have driven the selective events.

Estimating the Ages of Selection Signals from Different Epochs in Human History

Genetic variation harbors signatures of natural selection driven by selective pressures that are often unknown. Estimating the ages of selection signals may allow reconstructing the history of environmental changes that shaped human phenotypes and diseases. We have developed an approximate Bayesian computation (ABC) approach to estimate allele ages under a model of selection on new mutations and under demographic models appropriate for human populations. We have applied it to two resequencing data sets: An ultra-high depth data set from a relatively small sample of unrelated individuals and a lower depth data set in a larger sample with transmission information. In addition to evaluating the accuracy of our method based on simulations, for each SNP, we assessed the consistency between the posterior probabilities estimated by the ABC approach and the ancient DNA record, finding good agreement between the two types of data and methods. Applying this ABC approach to data for eight single nucleotide polymorphisms (SNPs), we were able to rule out an onset of selection prior to the dispersal out-of-Africa for three of them and more recent than the spread of agriculture for an additional three SNPs.

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.

Genetic variation in regulatory DNA elements: the case of OCA2 transcriptional regulation

Mutations within the OCA2 gene or the complete absence of the OCA2 protein leads to oculocutaneous albinism type 2. The OCA2 protein plays a central role in melanosome biogenesis, and it is a strong determinant of the eumelanin content in melanocytes. Transcript levels of the OCA2 gene are strongly correlated with pigmentation intensities. Recent studies demonstrated that the transcriptional level of OCA2 is to a large extent determined by the noncoding SNP rs12913832 located 21.5 kb upstream of the OCA2 gene promoter. In this review, we discuss current hypotheses and the available data on the mechanism of OCA2 transcriptional regulation and how this is influenced by genetic variation. Finally, we will explore how future epigenetic studies can be used to advance our insight into the functional biology that connects genetic variation to human pigmentation.

Don't it make your brown eyes blue? A comparison of iris colour across latitude in Australian twins

BACKGROUND

The aim was to determine whether latitudinal (Queensland versus Tasmania) variation in reported disease frequency in Australia may be biased by differences in population.

METHODS

A retrospective analysis was conducted from data of two large Australian twin studies (n = 1,835) having undertaken ophthalmic examination, namely, Twins Eye Study in Tasmania (TEST) and the Brisbane Adolescent Twins Study (BATS). Ordinal logistic regression was used to compute odds ratios and predicted probabilities for each category of eye colour by state.

RESULTS

Tasmanian residence was associated with lower odds of darker iris colour (odds ratio 0.77, 95% CI [0.63-0.95]) signifying that participants living in Tasmania (TAS) are less likely to have darker-coloured irides than those residing in Queensland (QLD). For individuals living in Tasmania the predicted probability (TAS versus QLD) of having light blue eyes was greater (16.7 versus 13.3 per cent), approximately the same for green eyes and less for brown/dark brown-coloured eyes (6.2 versus 7.9 per cent).

CONCLUSIONS

We found a general trend of individuals living in the southern states (TAS/VIC) of Australia having lighter-coloured irides compared to those living in the north (QLD). This finding has potential implications for all epidemiological research conducted to explore differences in UV-associated disease frequency in Australia, as population heterogeneity may confound the estimates obtained.

Increased risk of developing cutaneous malignant melanoma is associated with variation in pigmentation genes and VDR, and may involve epistatic effects

Cutaneous malignant melanoma (CMM) is a malicious human skin cancer that primarily affects individuals with light pigmentation and heavy sun exposure, but also has a known familial association. Multiple genes and polymorphisms have been reported as low-penetrance susceptibility loci for CMM. Here, we examined 33 candidate polymorphisms located in 11 pigmentation genes and the vitamin D receptor gene (VDR) in a population of 130 cutaneous melanoma patients and 707 healthy controls. The genotypes obtained were evaluated for main association effects and potential gene-gene interactions. MC1R, TYR, VDR and SLC45A2 genes were found to be associated with CMM in our population. The results obtained for major function MC1R mutations were the most significant [with odds ratio (OR)=1.787, confidence interval (CI)=1.320-2.419 and P=1.715(-4)], followed by TYR (rs1393350) (with OR=1.569, CI=1.162-2.118, P=0.003), VDR (GCCC haplotype in rs2238136-rs4516035-rs7139166-rs11568820 block) (with OR=5.653, CI=1.794-17.811, P=0.003) and SLC45A2 (rs16891982) (with OR=0.238, CI=0.057-0.987, P=0.048). The study also detected significant intermolecular epistatic effects between MC1R and TYR, SLC45A2 and VDR, HERC2 and VDR, OCA2 and TPCN2, as well as intramolecular interactions between variants within the genes MC1R and VDR. In the final multivariate logistic regression model for CMM development, only the gene-gene interactions discovered remained significant, showing that epistasis may be an important factor in the risk of melanoma.

Cuba: exploring the history of admixture and the genetic basis of pigmentation using autosomal and uniparental markers

We carried out an admixture analysis of a sample comprising 1,019 individuals from all the provinces of Cuba. We used a panel of 128 autosomal Ancestry Informative Markers (AIMs) to estimate the admixture proportions. We also characterized a number of haplogroup diagnostic markers in the mtDNA and Y-chromosome in order to evaluate admixture using uniparental markers. Finally, we analyzed the association of 16 single nucleotide polymorphisms (SNPs) with quantitative estimates of skin pigmentation. In the total sample, the average European, African and Native American contributions as estimated from autosomal AIMs were 72%, 20% and 8%, respectively. The Eastern provinces of Cuba showed relatively higher African and Native American contributions than the Western provinces. In particular, the highest proportion of African ancestry was observed in the provinces of Guantánamo (40%) and Santiago de Cuba (39%), and the highest proportion of Native American ancestry in Granma (15%), Holguín (12%) and Las Tunas (12%). We found evidence of substantial population stratification in the current Cuban population, emphasizing the need to control for the effects of population stratification in association studies including individuals from Cuba. The results of the analyses of uniparental markers were concordant with those observed in the autosomes. These geographic patterns in admixture proportions are fully consistent with historical and archaeological information. Additionally, we identified a sex-biased pattern in the process of gene flow, with a substantially higher European contribution from the paternal side, and higher Native American and African contributions from the maternal side. This sex-biased contribution was particularly evident for Native American ancestry. Finally, we observed that SNPs located in the genes SLC24A5 and SLC45A2 are strongly associated with melanin levels in the sample.

Direct evidence for positive selection of skin, hair, and eye pigmentation in Europeans during the last 5,000 y

Pigmentation is a polygenic trait encompassing some of the most visible phenotypic variation observed in humans. Here we present direct estimates of selection acting on functional alleles in three key genes known to be involved in human pigmentation pathways--HERC2, SLC45A2, and TYR--using allele frequency estimates from Eneolithic, Bronze Age, and modern Eastern European samples and forward simulations. Neutrality was overwhelmingly rejected for all alleles studied, with point estimates of selection ranging from around 2-10% per generation. Our results provide direct evidence that strong selection favoring lighter skin, hair, and eye pigmentation has been operating in European populations over the last 5,000 y.

Association of genetic variants with self-assessed color categories in Brazilians

The Brazilian population was formed by extensive admixture of three different ancestral roots: Amerindians, Europeans and Africans. Our previous work has shown that at an individual level, ancestry, as estimated using molecular markers, was a poor predictor of color in Brazilians. We now investigate if SNPs known to be associated with human skin pigmentation can be used to predict color in Brazilians. For that, we studied the association of fifteen SNPs, previously known to be linked with skin color, in 243 unrelated Brazilian individuals self-identified as White, Browns or Blacks from Rio de Janeiro and 212 unrelated Brazilian individuals self-identified as White or Blacks from São Paulo. The significance of association of SNP genotypes with self-assessed color was evaluated using partial regression analysis. After controlling for ancestry estimates as covariates, only four SNPs remained significantly associated with skin pigmentation: rs1426654 and rs2555364 within SLC24A5, rs16891982 at SLC45A2 and rs1042602 at TYR. These loci are known to be involved in melanin synthesis or transport of melanosomes. We found that neither genotypes of these SNPs, nor their combination with biogeographical ancestry in principal component analysis, could predict self-assessed color in Brazilians at an individual level. However, significant correlations did emerge at group level, demonstrating that even though elements other than skin, eye and hair pigmentation do influence self-assessed color in Brazilians, the sociological act of self-classification is still substantially dependent of genotype at these four SNPs.

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

AIM

To evaluate the accuracy of eye color prediction based on six IrisPlex single nucleotide polymorphisms (SNP) in a Slovenian population sample.

METHODS

Six 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).

RESULTS

Blue 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.

CONCLUSION

Blue 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.