Abstract
Bayesian clustering as implemented in STRUCTURE or GENELAND software is widely used to form genetic groups of populations or individuals. On the other hand, in order to satisfy the need for less computer-intensive approaches, multivariate analyses are specifically devoted to extracting information from large datasets. In this paper, we report the use of a dataset of AFLP markers belonging to 15 sampling sites of Acacia caven for studying the genetic structure and comparing the consistency of three methods: STRUCTURE, GENELAND and DAPC. Of these methods, DAPC was the fastest one and showed accuracy in inferring the K number of populations (K = 12 using the find.clusters option and K = 15 with a priori information of populations). GENELAND in turn, provides information on the area of membership probabilities for individuals or populations in the space, when coordinates are specified (K = 12). STRUCTURE also inferred the number of K populations and the membership probabilities of individuals based on ancestry, presenting the result K = 11 without prior information of populations and K = 15 using the LOCPRIOR option. Finally, in this work all three methods showed high consistency in estimating the population structure, inferring similar numbers of populations and the membership probabilities of individuals to each group, with a high correlation between each other.
Highlights
Evaluating population genetic structure is of considerable interest because it is a precursor to addressing many other issues, such as estimating migration, identifying conservation units, and specifying phylogeographical patterns (Manel et al, 2005)
Analysis of the Acacia caven AFLP dataset obtained using GENELAND yielded a modal number of populations of 12, varying from 11-13 in different runs (Table 3)
The analysis of genetic diversity within species is vital for understanding the evolutionary processes, both at the population and at the genomic levels
Summary
Evaluating population genetic structure is of considerable interest because it is a precursor to addressing many other issues, such as estimating migration, identifying conservation units, and specifying phylogeographical patterns (Manel et al, 2005).Various statistical approaches can be used to form genetic groups of populations or individuals. Bayesian clustering (Manel et al, 2005) based on HardyWeinberg and linkage equilibrium, as implemented in the STRUCTURE (Pritchard et al, 2000) or GENELAND (Guillot et al, 2005) programs, is widely used for this purpose. These programs can consider coordinates of sampling locations. A model is assumed in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus This method attempts to assign individuals to populations on the basis of their genotypes, while simultaneously estimating population allele frequencies. The method assumes that any disequilibrium found is attributable to population structuration
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