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).