Isozyme and RAPD studies in Prosopis glandulosa and P. Velutina (Leguminosae, Mimosoideae)

Allozyme and random amplified polymorphic DNA (RAPD) techniques have been compared for their usefulness for genetic and taxonomic studies in Prosopis glandulosa and P. velutina populations. Isozymes and RAPDs yielded similarly high estimates of genetic variability. Genetic structure and differentiation were analyzed through non-hierarchical Wright's F DT. For all populations considered, both markers produced low gene flow (Nm < 1) estimates. When only P. glandulosa populations were analyzed, isozyme data yielded higher gene flow estimates (Nm > 1), in agreement with that expected for conspecific populations. However, in RAPD data the expected reduction in F DT and the increase in Nm were not observed. Correlation between F DT and geographical distance matrices (Mantel test) for all populations was significant (P = 0.02) when based on isozymes, but not so (P = 0.33) when based on RAPDs. No significant associations among genetic and geographical or climatic variables were observed. Two isoenzyme systems (GOT and PRX) enabled us to distinguish between P. glandulosa and P. velutina, but no diagnostic band for recognition of populations or species studied here were detected by RAPD. However, RAPD markers showed higher values for genetic differentiation among conspecific populations of P. glandulosa and a lower coefficient of variation than those obtained from isozymes

Analysis of genetic population structure in Acacia caven (Leguminosae, Mimosoideae), comparing one exploratory and two Bayesian-model-based methods

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