A single-nucleotide polymorphism (SNP) multiplex system: the association of five SNPs with human eye and hair color in the Slovenian population and comparison using a Bayesian network and logistic regression model

Aim To analyze two phenotype characteristics – eye and hair color – using single-nucleotide polymorphisms (SNPs) and evaluate their prediction accuracy in Slovenian population. Methods Twelve SNPs (OCA2 – rs1667394, rs7170989, rs1800407, rs7495174; HERC2 – rs1129038, rs12913832; MC1R – rs1805005, rs1805008; TYR – rs1393350; SLC45A2 – rs16891982, rs26722; SLC24A5 – rs1426654) were used for the development of a single multiplex assay. The single multiplex assay was based on SNaPshot chemistry and capillary electrophoresis. In order to evaluate the accuracy of the prediction of eye and hair color, we used the logistic regression model and the Bayesian network model, and compared the parameters of both. Results The new single multiplex assay displayed high levels of genotyping sensitivity with complete profiles generated from as little as 62 pg of DNA. Based on a prior evaluation of all SNPs in a single multiplex, we focused on the five most statistically significant in our population in order to investigate the predictive value. The two prediction models performed reliably without prior ancestry information, and revealed very good accuracy for both eye and hair color. Both models determined the highest predictive value for rs12913832 (P