Prediction of human eye colour using highly informative phenotype SNPs (PISNPs)

One of the rapidly developing areas in human genetics and genomics is detection of candidate Single Nucleotide Polymorphism (SNPs) for human complex traits. These findings can be used in the field of forensics for predicting the externally visible characteristics (EVCs) of a given individual based on a sample of DNA alone. Eye colour is currently the most thoroughly investigated EVC for forensic genetic applications. In this study, eye colour prediction performance of two currently available major methods was assessed in a set of 100 individuals from Turkey by applying the two statistical approaches of multinomial logistic regression (MLR) and Bayes analysis using each statistical approach’s online portal (https://hirisplex.erasmusmc.nl/ and http://mathgene.usc.es/snipper/eyeclassifier.html) designed for SNP-based forensic prediction for this phenotype. On one hand, eye colour prediction results for IrisPlex SNPs have a high success rate for correctly predicting blue/brown phenotypes but not for green-hazel or intermediate dark phenotypes. On the other hand, Snipper analysis improved detection of intermediate phenotypes but increased the number of unclassified individuals given the prediction probability threshold applied. This study adds data that can be used as a reference for future eye colour prediction investigations in forensic cases.