2.4.3 Population genetic structure
To assess population genetic structure, Bayesian clustering analysis and
principal component analysis (PCA) were conducted for both haploid and
diploid datasets. Bayesian clustering analysis was performed using
STRUCTURE v. 2.3.4 (Pritchard, Stephens, & Donnelly, 2000). The number
of clusters (K ) of 1–10 was tested by running 10 simulations for
each K , with 100,000 Markov chain Monte Carlo steps and a burn-in
of 100,000, using the model with admixture and correlated allele
frequencies. The meaningful number of K was determined based on
the mean estimated Ln probability of the data [LnP(K )] and
the second-order rate of change in the log probability of the data
(ΔK ; Evanno et al., 2005). The ΔK values were calculated
using STRUCTURE HARVESTER v. 0.6.94 (Earl & vonHoldt, 2012). Principal
component analysis was performed using PLINK and the results were
visualized using R software v. 3.6.0 (R Core Team, 2019). To reveal
phylogenetic relationships between parthenogenetic and sexual
populations, a phylogenetic network was constructed based on uncorrectedP distances using NeighborNet method (Bryant & Moulton, 2004) in
SplitsTree v. 4.15.1 (Huson & Bryant, 2006).