DNA-based Eye Color Prediction of Pakhtun Population Living in District Swat KP Pakistan

Full Length Research Article

DNA-based Eye Color Prediction of Pakhtun Population Living in District Swat KP Pakistan

Murad Ali Rahat1, Hakim Khan1, Ishtiaq Hassan1, Muhammad Haris1, Muhammad Israr2*

Adv. life sci., vol. 7, no. 3, pp. 157-163, May 2020
*Corresponding Author: Muhammad Israr (Email: afficer@gmail.com)
Authors' Affiliations

 1. Department of Genetics, Hazara University, Mansehra – Pakistan
2. Department of Forensic Sciences, University of Swat – Pakistan

 [Date Received: 14/01/2019; Date Revised: 22/04/2020; Date Published Online: 25/05/2020]

Abstractaa download_button



Background: Forensic DNA Phenotyping (FDP) or the prediction of Externally Visible Characteristics (EVCs) from a DNA sample has gained importance in the last decade or so in the forensic community. If and when the traditional forensic DNA typing via Short Tandem Repeats (STR) fails due to the absence of a reference sample, an individual can be traced by a DNA sample using FDP. Amongst the many available EVCs, eye color is one such character that can be predicted by employing previously developed IrisPlex system using Single Nucleotide Polymorphism (SNP) assay. In this study, we applied the IrisPlex system to samples collected from population of District Swat for prediction of eye colours from DNA.

Method: Eye colour digital photographs and buccal swab samples were collected from 267 Pakhtun individuals of District Swat. Any person with eye disease was excluded from the study. Genomic DNA was extracted through Phenol-Chloroform extraction method. The amplified SNPs were typed using Multiplexed Single Base Extension (SBE). The genotypes were checked for eye color phenotypes through IrisPlex online tool and correlation were checked between SNPs, Gender, pie score and eye color.

Result: Brown eye color was found prevalent as compared to intermediate and blue. Females have highly brown eye color compared to males while males have intermediate and blue. Three SNPs rs12913832 (in the HERC2), rs1393350 (TYR gene), rs1800407 (OCA2 gene) were strongly significant to eye color. Pie score was also significant to eye color and rs12913832 SNP. IrisPlex analysis in 20 individuals of District Swat was performed. The prediction accuracy of IrisPlex for blue or brown was 100% in the studied individuals. However, the IrisPlex tool predicted the intermediate phenotype incorrectly as brown or blue.

Conclusion: It is concluded from the data that intermediate eye colour was not predicted accurately, therefore, inclusion of more SNPs in the IrisPlex system is needed to predict intermediate eye colour accurately.

Keywords: Eye colour, IrisPlex, SNPs, Multiplex genotyping, DNA, District Swat

Introduction6th button-01

Eye and hair colour are two main features in determining an individual’s appearance within a population. Eye and hair colour are extremely heritable. Heritability for eye colour ranges from 61 to 100 percent and for hair, similar estimates are obtained [1-3]. Both eye color and hair color shows a great variation due to type and amount of melanin pigment as well as responsiveness to UV radiations within as well as amongst populations [4,5]. Human colouration of skin, eye and hair are one of the most changeable and having some characteristics, mostly influenced by the combination of hormonal and genetic factors, and also concerned with the environment, drugs, age, and contact with UV [6,7].

Melanin is one of the proteins mostly responsible for pigmentation of eye, hair and skin. Melanin production occurs in melanocytes and can further synthesize two types; eumelanin and pheomelanin. Eumelanin is  concerned with brown and black colour while pheomelanin with yellow and red [8]. SLC24A5 and ASIP genes play key role in the process of melanogenesis [9,10].

Ancestry of European people shows extensive variation in hair and iris pigmentation. Eye colour types mainly brown, intermediate and blue are present in European population, but other parts of the world have a tendency to have brown colour. It follows the theory that darker pigmentation originated in the last 2 million years after our ancestors lost their protective hair covering leading to the exposure of their lighter skin. However, they also present evidence to support the idea that the darker pigmentation in South East Asian populations may indeed result from a common African ancestor whose migration route led them out of African and into East Asia. Ultimately, it may be possible that both factors of convergent evolution and natural selection are behind the pigmentation of the skin [11]. The recent difference in eye colour is assumed to have been created through genetically mixing non-brown irises throughout primary European history [12,13]. It is also thought that the eye colour difference in Europe has been made by positive sexual selection [14,15]. On the other hand, it is suggested the eye colour difference change with skin colour and environmental adaptations [13,15]. It is also proposed that the source for European blue eye color is the southern Baltic region with reducing colour north to south [14,15]. While the particular functional outcome of several SNPs linked with eye colour is presently unknown, however, earlier a systematic study was carried out on thirty-seven SNPs from eight genes linked for eye colour in 6168 Dutch Europeans. It was found that fifteen SNPs could correctly predict brown and non-brown colours. Out of these, all eye colours were covered by only six SNPs from six genes [16]. On the basis of the previous studies, recently, IrisPlex system was developed to accurately predict non-intermediate colour. IrisPlex system consist of six SNP multiplex SNaPshot assays validated for forensics studies. Earlier, a worldwide IrisPlex study established the capability of the IrisPlex system to predict individual categorical eye colour dependably on the basis of bio-geographic ancestry thus eliminating the need for secondary data for genetics origin [17].

The aim of the instant study was to check IrisPlex system for prediction of eye colour in Pakhtun population of Swat district and compare the results with previously reported populations. We also aimed to check the accuracy of IrisPlex system on the Pakhtun population of District Swat. 

Methods6th button-01

Sample collection and DNA extraction

After approval of Institutional Ethical Committee, samples were collected from healthy male and female volunteers of different areas of District Swat. Individuals having heterochromia and any eye diseases were excluded. Consent form was taken from the participant mentioning written declaration by the participant, gender, eye colour, age, ethnicity, and place of birth. Buccal tissue cells were collected from the same participants by using two sterile buccal swabs for each participant. Genomic DNA was isolated through organic extraction method [18].

Digital photographs

Left Eye pictures of each participant at a distance of almost 10 cm were taken with shutter 1/100 and AV 18 by using lens 18-55 mm Nikon D5300 camera using uniform light conditions and saved in ‘JPEG’ format.

SNPs amplification and Genotyping

Six SNPs namely, rs12896399 (HERC2), rs1800407 (OCA2), rs16891982 (SLC24A4), rs1393350 (SLC45A2), rs12913832 (TYR) and rs12203592 (IFR4) representing the respective genes were selected. The primers used for the study were already published [16]. DNA was amplified in 20 µl reaction consisting of: 2.0 µl MgCl2, 2.0 µl reaction buffer, 0.4 µl dNTPs (10µM), 0.5 µl each of forward and reverse primers (10µM), 0.5 µl Taq polymerase, 2.0 µl DNA and ddH2O. The reactions were allowed to proceed in a thermal cycler (XP Thermal Cycler, BIOER TECHNOLOGY CO., LTD). Thermal cycling parameters were adjusted as; initial denaturation for 10 minutes at 95°C, followed by 35 cycles of (denaturation for 30 seconds at 95 °C, annealing and extension for 30 seconds at 60°C) followed by final extension at 62 °C for 5 minutes. Multiplexed SNaPshot (Life Technologies Inc, USA) SBE chemistry was used for SNP typing. PCR product was treated with ExoSAP-IT (USB1 Corporation) at 37 °C for 15 min to eliminate unused dNTPs or PCR primers. It was followed by 85 °C for 15 min to stop the enzyme activity. Then 1.5 µl of treated PCR product was added to 2.5 µl of SNaPshot prepared reaction mix and 1.5 µl of extension primer mix. Conditions for extension were 30 cycles as: 96°C for 10 seconds, 50°C for 5 seconds and 60°C for 30 seconds. To clean up, the extension reaction products were treated with 1 µl of SAP at 37 °C for 80 minutes. To stop enzymatic activity, the mixture was treated at 85°C for 15 minutes. Capillary electrophoresis was performed using ABI Prism 3730xl Genetic Analyzer (Life Technologies Inc, USA).

Data Analysis

Genotype analysis was done through GeneMapper software v 4.0 (Life Technologies Inc, USA). Statistical analyses were performed through IBM SPSS Statistics 23 (IBM Inc). Correlation was checked between SNPs, eye colour pie score. Pixel Index of Eye (PIE) score was calculated for all digital eye photographs. The score ranges from -1 to 1 (from brown to blue respectively), however intermediate colour has been given a score of 0 only. The score was calculated using the following equation [19]:




Iris assessment was done through seven untrained observers. They were allowed to assess the iris colour in the digital eye colour photograph kept from them in the same distance and similar light conditions. They were asked to assign the iris colour in one of the following 3 categories, i.e. brown, intermediate, and blue. The intermediate colour was either green or hazel. In case of no consensus among observers to assess the eye colour, it was then assigned on majority-voting system between the observers.

All the genotype data of the 20 samples present on the excel sheet were checked on online IrisPlex tool (http://hirisplex.erasmusmc.nl/) and the result was compared with phenotype data. 

Results6th button-01

Phenotype distribution eye colour across the study population

A Total of 267 individuals (149 males and 118 females) were selected. Brown eye colour was present in 202 (75.7%) individual’s, intermediate was in 40 (15.0%) and blue eye colour was in 25 (9.4%). Brown eye colour was slightly more in females as compared to males (51.48 %, vs 48.51%), while blue (20% vs 80%) and intermediate (22.5% vs 77.5%) were less prevalent in females as compared to males.

SNPs amplification and Genotyping

Six SNPs included in the IrisPlex system were amplified and results are presented in (Figure 3). Product size of SNPs is from 84 bp to 128 bp.

IrisPlex SNPs genotype distributions across the study population

Result show that SNP rs12913832 having three genotypes:  homozygous CC (60%), TT (30%) and

heterozygous CT (10%). CC genotype occurred (100%) in blue and intermediate eye coloured individuals while in brown eyed individuals CT (25%) and TT (75%) genotype was present.  SNP rs1800407 had two types of genotypes: homozygous GG (90%) and heterozygous GA (10%). GA heterozygous genotype was present only in Brown eye colour while GG homozygous genotype was present in intermediate (45%), brown (30%) and blue (15%) eye colour. SNP rs12896399 showed three types of genotype: homozygous AA (20%), CC (40%) and CA (40%) heterozygous. In three blue eye-coloured individuals, two types of genotype were present heterozygous CA (33%) and homozygous CC (66%). Brown eye-coloured individuals had three different types of genotype combinations: AA (25%), CA (50%) and CC (25%). Intermediate eye-coloured individuals also had three types of genotype combinations: AA (22%), CA (33%) and CC (44%) CC. SNP rs1691982 showed three types of genotypes: homozygous GG (25%), CC (30%) and heterozygous GC (45%). In blue eye-coloured individuals, two types of genotypes were present: heterozygous GC (66%) and homozygous GG (33%). In brown eye-coloured samples, three types of genotypes were present: homozygous CC (25%), GG (37%) and heterozygous GC (37%). Intermediate eye-coloured individuals also had three types of genotypes: homozygous CC (44%), GG (44.44%) and heterozygous GC (11%). SNP rs1393350 showed three types of genotypes: homozygous GG (85%), AA (5%) and heterozygous GA (10%). In blue eye-coloured individuals, the only genotype was homozygous GG (100%) while in intermediate coloured samples, two types were present: GA (11%) and GG (88%). Brown eye-coloured individuals had three types of genotypes: AA (12%), GA (12%) and GG (75%). SNP rs12203592 showed only one type of homozygous genotype: CC.

Association of IrisPlex SNPs with gender and PIE score

Associations of six SNPs included in IrisPlex were checked with gender and PIE-score (Table 2). SNP rs12913832 (HERC2) showed the strongest association showing significant difference. Moreover, no significant associations with gender and PIE-score were detected. Statistical correlation found significant association of rs1291832 with eye colour phenotype.

Prediction Model accuracy

Original IrisPlex system was tested on 20 samples of unrelated individuals of Pakhtun population of District Swat. The individual eye colour was assigned by high probability value of IrisPlex system. Predicted eye colour was compared to the real eye colour. Accuracy of IrisPlex system for predicting brown eye colour was 100 percent with a high probability value of 0.994407, blue eye colour was also predicted 100 percent with a probability value of 0.84781. Intermediate eye colour was incorrectly predicted as blue (55.55%) with 0.649894 probability or brown (44.55%) with 0.547452 probability. Total probabilities and eye colour prediction result of the IrisPlex system is shown in Table 3.

Figures & Tables












Discussion6th button-01

All individuals were classified in three eye colour categories: blue, brown and intermediate. The Pakhtun population of Swat district have dominantly brown eye colour followed by the intermediate and blue eye (Figure 2). Our data show almost similar results with Spanish population where brown eye colour is dominant over other colours. In Europe, blue eye colour decreases from Northern to Southern while brown colour increases, from average 17.8% in southern Europe and 81% in Northern Europe. Estonia, Norway and Northern Ireland showing the highest number (75%) of blue-eye colour. Northern Italy (29%) and France (28.7%) showed average to low blue-eye colour individuals. Greece (12.4%) and Spain (16%) showed the lowest average frequency of blue eye colour [16,17,19,20]. So, it may be inferred from the data that specificity of any eye colour is not related with any population or region of the world.

Eye colour percentage turn out to change between male and females (Figure 1). The percentage of brown eye females was higher than male while intermediate and blue eye colours were more dominant in males as compared to females. In comparison, in a study of Polish individuals, most dominant colour was blue (52.5%) followed by hazel and green (12.5% and 21.4%) while brown was comparatively low (13.7%). Blue eye males were common (58.1%) then blue eye females (42.2) [21]. Our results concords with those of Spanish population where males were found to have predominantly blue and intermediate colours while females have dominantly brown eye colours. Blue-eyed females (8.5%) were less than blue-eyed males (14.71%) whereas brown colour was more prevalent in females (78.45%) than males (71.43%) in the Spanish population [22]. Some similar results were found in other countries where blue colour was more prevalent in males than females in populations such as Iceland, Holland [23], Australia [24], Poland [25] and France [26], as well as in this study (Figure 1). These data indicate darker eye colours for females and brighter eye colours for males.

Although previous studies showed significant association of IrisPlex SNPs with eye colour in Northern European populations [16,20,27,28], In this study, rs12913832 (in the HERC2 ), rs1393350 (TYR gene), rs1800407 (OCA2 gene) showed strong association with eye colour (Table 3). Previously, rs12913832 is shown to account for most eye colour variations in Caucasians [12,14-17,19,20,22-25,27,29], while the remaining 5 SNPs apparently have a relatively minor role [16,20,28,30].

The eye colour distribution in the current data set (n = 20) consisted of brown = 8 (40.0 %), intermediate = 9 (45.0%) and blue = 3 (5.0%) eye colour. The SNPs association test is presented in (Table 2), which shows that rs12913832 is associated most significantly with eye colour (P-value = 0.000). The allele (CC) is responsible for having non-brown eyes. All brown-eyed subjects were either homozygous or heterozygous i.e. TT or CT. The remaining non blue and non-brown were homozygous for CC genotype. rs12203592 SNP was not included in they were not polymorphic in this population (Figure 6). SNP, rs12913832 associated with eye colour was previously in rank 1 [20], shows a durable geographic design in genotypes across District Swat.

Irisplex online tool (http://hirisplex.erasmusmc.nl/) was used for the present samples. Considering all SNPs of irisplex, probabilities for eye colours were generated for the samples. The highest probability value of irixplex system was used to assign eye colour of the individual. Predicted eye colour was compared to the real eye colour. Accuracy of IrisPlex system for predictingd brown eye colour was 100 percent with a high probability value of 0.994407, blue eye colour was also predicted 100 percent with a probability value of 0.84781. Intermediate eye colour was incorrectly predicted as blue (55.55%) with 0.649894 probability or brown (44.55%) with 0.547452 probability (Table 3). In New Zealand, accuracy for blue eye colour was 89% and 94% for brown, while prediction accuracy was low (46%) for intermediate eye colour [31]. In the United States, the correct eye color prediction rate was 95% and 88% for blue and brown eye colors, respectively, the intermediate color at this threshold did not yield any true positive predictions [32]. In Slovenian population sensitivity was 93.6% for blue, 58.1% for brown, and 0% for intermediate eye color [33]. In Portuguese population the results demonstrated eye colour prediction accuracies of the IrisPlex system of 90% and 60 % for brown and blue eye color, respectively, and 77 % for intermediate eye color [34].

PIE-score was assessed by comparing photographs with human groupings of the similar images. The PIE-score showed association with colour phenotypes (Table 2). This was predictable because the PIE-score is created on the numbers of blue and brown. Blue pixels (both light and dark) were classified as blue and brown pixels (both light and dark) were classified as brown. Variation in the PIE-score was mostly clarified by SNP rs12913832. After the association for the effect of rs12913832 influenced the PIE-score significantly, whereas rs16891982, rs12896399, rs1393350, rs1800407 and rs12203592 did not (Table 2). Our result is similar to [35] where PIE score is significant with eye colour and rs1291832 SNP.

This study shows reliability of the IrisPlex model for accurately predicting brown and blue eye colour in Pakhtun population of Swat. The IrisPlex system, with sign providing for data across Swat district, is highly informative and appropriate for FDP applications in forensic sciences. However, more detailed study is required for increasing the accuracy of prediction especially for intermediate colours. In the near future, these data along with data for prediction of hair colour, age and other such EVCs that may become available with further studies may be used for forensic case work. These types of studies may be required for police and law enforcement agencies to solve cold cases where no data are available except DNA samples without any reference to match.


This research was funded by Higher Education Commission of Pakistan (HEC) under National Research Program for Universities Grant No. NRPU # 6828.

Authors' Contribution

MAR and MH performed experimental work. HK and IH were involved in planning and data analysis. MI was the Principal Investigator.

Conflict of interest

All the authors declare that they have no competing interest that can negatively affect the current study.

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