Population genetics analyses
We constructed a neighbor-joining tree using the pairwise genetic
distance matrix data of all individuals calculated using TreeBest v1.9.2
(Vilella et al. 2009), and the number of bootstrap replicates was
set to 1000 to assess the statistical support for nodes in the tree.
Principal components analysis (PCA) based on SNP markers was performed
using GCTA tools (Yang et al. 2011). We transformed the
population genotypes into a matrix that included the numbers 0, 1, and
2, where 0 was used to represent a genotype that is homozygous for the
reference allele, 1 is a genotype heterozygous for the reference allele;
and 2 is a genotype homozygous for the non-reference allele. We
calculated the sample covariance of the matrix that contained the
information for all individuals (with the numbers 0, 1, and 2). Finally,
we calculated the eigenvector decomposition of the matrix and plotted
the PCA using GCTA tools.
We used PLINK to generate the map files necessary for downstream
analyses (Purcell et al. 2007). Population structure was
determined using the program FRAPPE (Tang et al. 2005). We
increased the pre-defined parameter K from 2 to 5 to cover the maximum
numbers of lineages that could be identified in the tree, representing
the assumed groups of a simulated population in ancient times.
Population genetic structure and individual ancestry proportions were
finally inferred using FRAPPE.