Prediction of hair colour from genotype in the Argentine population: a preliminary study

Abstract

Hair colour is an external visible phenotypic trait, which is determined by a set of genes that are variable among individuals and among populations. It is possible to predict the physical appearance of an individual with a certain probability, by genotyping a biological sample, being a valuable tool for the identification of persons in the field of forensic genetics. Based on previous studies of phenotyping, systems for predicting phenotype using genetic data have been developed, such as HIrisPlex-S and Snipper, among others. However, these studies have been carried out mainly on populations of European origin, and may not be directly applicable to admixed populations, as is the case of Argentineans, where genotype-phenotype association could differ, given their multiple ancestry components (Eurasian, Native, and Sub-Saharan). The aim of this work is to describe the genetic variation underlying hair colour in Argentina population. We obtained DNA from 158 samples of mouthwash from donors from the province of Buenos Aires. Five SNPs were genotyped for MC1R gene, rs11547464, rs1805006, rs1805007, rs1805008, rs1805009, and one for SLC45A2 gene rs28777. Samples were visually classified into two colour categories, and on the other hand, using Snipper as a bayesian classifier. The coincidence rate was 56.96%, indicating a correlation between the Snipper results and observations in that percentage of instances, with a higher incidence among individuals with dark hair (58.9% for dark-haired individuals and 41.1% for blondes). Our results suggest the need for improving the values of prediction of hair colour from genotype information for this admixed population. Given the substantial amount of genetic and phenotypic variability of this population, influenced by various ancestry components, it is crucial to increase the accuracy and applicability in forensic investigations by continuing these studies with more markers and a bigger sample of individuals.