Analysis of molecular variance components based on the 849 SNPs showed that wheat lines within breeding populations are more highly genetically differentiated than wheat lines among different populations, which is reflected by a higher proportion of variance within breeding populations than among breeding populations and growth habit groups (Table 3).
Analysis of molecular variance showed all variance components to be highly significant (P < 0.001), indicating more variation within (91%%) than between populations (9 %).
The analysis partitions out total molecular variance into different components, and statistical significance is obtained by randomization after 5000 permutations.
For each group, total molecular variance is partitioned into three components: among groups (commercial varieties versus feral populations), among populations within groups and within populations.
We also used the Arlequin software to perform an analysis of molecular variance (AMOVA) with 10 000 permutations to estimate variance components between Atlantic salmon populations and between individuals within populations by applying the bootstrapped FST estimator of Weir and Cockerham [ 24].
Genetic distances (F st ) [ 20] between all pairs of horticultural types with at least two accessions, analysis of molecular variance (AMOVA) [ 21], and principal components analysis (PCA) were calculated using GenoDive v.2.0b20.
In this case, Fst was calculated as F s t = σ a 2 σ T 2, where σa2 is the covariance component due to differences among the populations, and σT2 is the total molecular variance calculated as the sum of the covariance components among haplotypes within a population, among haplotypes in different populations and the component originated by differences among populations.
Local populations are genetically different according to RAPD markers, and an analysis of molecular variation (AMOVA) revealed a significant interpopulational variance component around 10%.
Analysis of molecular variance (AMOVA; [ 29]) was used to quantify variance components and the significance of the genetic subdivisions identified by the Bayesian test, as well as a range of other relevant groupings.
We also found strong evidence for hierarchical structure in both nuclear and mitochondrial SNPs through an analysis of molecular variance (AMOVA: see additional file 2); significance of variance components was found in all three SNP sets.
