Discriminant Analysis of Principal Components (DAPC) was used to cluster individuals based on genotypes. This well-known method aims to maximize group differences while minimizing within cluster variances . DAPC was applied on a matrix composed of 506 individuals and 5838 SNPs using an implementation available in the R package adegenet 2.0.0. To identify clusters, the principal component analysis (PCA) of the matrix data was first computed followed by Discriminant Analysis on the number of retained principal components as provided by DAPC method.