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SNP model development for the prediction of eye colour in New Zealand

Abstract

The ability to predict externally visible characteristics (EVCs) from DNA has appeal for use in forensic science, particularly where a forensic database match is not made and an eye witness account is unavailable. This technology has yet to be implemented in casework in New Zealand. The broad cultural diversity and likely population stratification within New Zealand dictates that any EVC predictions made using anonymous DNA must perform accurately in the absence of knowledge of the donor's ancestral background. Here we construct classification tree models with SNPs of known association with eye colour phenotypes in three categories, blue vs. non-blue, brown vs. non-brown and intermediate vs. non-intermediate. A set of nineteen SNPs from ten different known or suspected pigmentation genes were selected from the literature. A training dataset of 101 unrelated individuals from the New Zealand population and representing different ancestral backgrounds were used. We constructed four alternate models capable of predicting eye colour from the DNA genotypes of SNPs located within the HERC2, OCA2, TYR and SLC24A4 genes using probability calculation and classification trees. The final model selected for eye colour prediction exhibited high levels of accuracy for both blue (89%) and brown eye colour (94%). Models were further assessed with a test set of 25 'blind' samples where phenotype was unknown, with blue and brown eye colour predicted correctly where model thresholds were met. Classification trees offer an aesthetically simple and comprehendible model to predict blue and brown eye colour.

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