Medrano, Herrera and Bazaga
Appendix S2 – 1
Appendix S2. Genetic structure of Helleborus foetidus plants sampled for this study
Methods
To examine whether the 200 H. foetidus plants sampled for this study from ten locations
were genetically structured, and to define the most likely number of genetic clusters (K)
represented in the sample, we used Bayesian clustering analyses as implemented in
STRUCTURE v2.3 (Pritchard et al. 2000; Falush et al. 2003, 2007). These analyses were
performed on the data set of 270 AFLP fragments, using the following parameters: length
of burn-in period = 500,000, number of Markov chain Monte Carlo reps after burn-in =
1,000,000, admixture model, and correlated allele frequencies. To test the stability of the
results, 30 iterations per K level were performed from K = 1 through K = 10. The most
probable number of genetic clusters was determined by calculating the ad hoc statistic
delta K, which identifies the highest rate of change in the log-likelihood between
successive Ks (Evanno et al. 2005), in STRUCTURE HARVESTER (Earl & vonHoldt
2012). The program CLUMPP (Jakobsson & Rosenberg 2007) was used to compile
individual assignments across all 30 replicates for the most likely K, with the Greedy
algorithm and 5000 reps. Individual group membership probabilities for individual plants
were plotted for visualization using DISTRUCT 1.1 (Rosenberg 2004).
Results
The results of the STRUCTURE analyses revealed that the recognition of two clusters (K
= 2) best reflected the genetic structure present in our data (Fig. S2A). At K = 2, a
southern group of four populations (PLL, SCA, CFU, and ESP respectively) were clearly
differentiated from the two northernmost populations (TEJ, CAN) as well as the four
geographically intermediate populations (NAV, MES, FBE, and VCU; Fig. S2B). The
vast majority of individuals (86%) were assigned to one of these two genetic clusters with
a probability of 0.9 or more. Some admixture between these two main lineages occurred
in three of the four central populations (MES, NAV, and FBE) as denoted by a certain
proportion of admixed individuals (Fig. S2B).
Medrano, Herrera and Bazaga
Appendix S2 – 2
Figure S2. Results of the Bayesian clustering analysis using STRUCTURE of the 200 plants x 270 AFLP
marker data matrix. (A) Estimation of the most probable number of genetic clusters present in the sample (K)
for K=1-10 and 30 independent STRUCTURE simulations: posterior probabilities of the data LnP(D) (open
circles) and values of Evanno’s Delta K (filled circles). (B) Maps showing the location of the ten studied
populations in south eastern Europe (left panel) and the distribution of the two different genetic groups
obtained using STRUCTURE (right panel) represented as: the proportion of the two genetic pools detected in
each population (pie charts); and the probability of membership to the two inferred clusters for each of the
200 Helleborus foetidus individuals sampled (horizontal lines inside the barplot). Colors represent the
estimated probabilities of membership to each cluster. Population codes as in Appendix S1.
A)
B)
Medrano, Herrera and Bazaga
Appendix S2 – 3
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