2.4 | Population structure, mismatch distribution
analysis, and neutrality detection
The population structure of nrDNA and cpDNA sequences was inferred using
the Bayesian clustering procedure implemented in STRUCTURE v.2.3.4
(Evanno et al., 2005) without prior structure information; this software
identifies the most probable number (K ) of genetic clusters of
origin of the sampled individuals and assigns individuals to clusters.
We used MCMC iterations as implemented in STRUCTURE to explore the
parameter space considering individual memberships to K clusters,
ranging from K = 1 (null hypothesis of panmixia) to K = 8
(the total number of populations sampled). Three independent runs were
performed with an admixture model at 105 MCMC
iterations and a 105 burn-in period. The most likely
number of population groups (K , indicating the number of true
clusters in the data) and the model values
(ΔK , according to the
second-order rate of change of cluster K that best fits the data)
were calculated in STRUCTURE HARVESTER (Earl & vonHoldt, 2012). The
graphical representation of results was performed in the CLUMPAK server
(http://clumpak.tau.ac.il/index.html).
An analysis of molecular variance (AMOVA) was conducted on nrDNA and
cpDNA sequences separately to test genetic differentiation within
populations, among groups, and populations within groups using GenAlEx
v.6.503 (Peakall & Smouse, 2012). Population pairwiseF ST was measured using DNASP v.6.12.01, and
population pairwise geographic distances were calculated by GenAlEx. To
test whether there was local genetic variation attributable to
isolation-by-distance among populations, the estimates ofF ST/(1-F ST) and the
corresponding natural logarithm of geographic distances (in km) between
all pairwise combinations of the eight populations were regressed and
subjected to a Mantel test (Mantel, 1967) with 999 random permutations
in GenAlEx.
The genealogical relationships
between ribotypes/chlorotypes based on the Medium-Joining model were
inferred using NETWORK v.4.6.1.0
(http://www.fluxus-Engineering.com/). To identify and quantify
potential genetic discontinuities and biogeographic boundaries acting as
major genetic barriers among P. heterotricha populations from
both nrITS and cpDNA datasets, we calculated the Monmonierʼs
maximum-difference algorithm in Barrier v.2.2 (Manni et al., 2004). The
robustness of these barriers was assessed by bootstrapping genetic
distances.
In order to detect possible
recent range expansions, Tajimaʼs D (Tajima, 1989) and FuʼsF s (Fu, 1997) were calculated to test the deviations from the
null hypothesis of constant population size and neutral evolution for
each DNA fragment. Pairwise mismatch distribution and neutrality tests
for all populations were conducted in DNASP using the nrITS and cpDNA
datasets separately.