Mantel test in population genetics

Abstract

The comparison of genetic divergence or genetic distances, estimated by pairwise FST and related statistics, with geographical distances by Mantel test is one of the most popular approaches to evaluate spatial processes driving population structure. There have been, however, recent criticisms and discussions on the statistical performance of the Mantel test. Simultaneously, alternative frameworks for data analyses are being proposed. Here, we review the Mantel test and its variations, including Mantel correlograms and partial correlations and regressions. For illustrative purposes, we studied spatial genetic divergence among 25 populations of Dipteryx alata (“Baru”), a tree species endemic to the Cerrado, the Brazilian savannas, based on 8 microsatellite loci. We also applied alternative methods to analyze spatial patterns in this dataset, especially a multivariate generalization of Spatial Eigenfunction Analysis based on redundancy analysis. The different approaches resulted in similar estimates of the magnitude of spatial structure in the genetic data. Furthermore, the results were expected based on previous knowledge of the ecological and evolutionary processes underlying genetic variation in this species. Our review shows that a careful application and interpretation of Mantel tests, especially Mantel correlograms, can overcome some potential statistical problems and provide a simple and useful tool for multivariate analysis of spatial patterns of genetic divergence.

Grouping and genetic diversity of different watermelon ecotypes based on agro-morphological traits and ISSR marker

“…6 software (Perrier & Jacquemoud-Collet 2006). Finally, the Mantel`s test (Diniz-Filho et al 2013, Mantel 1967) was performed via XLSTAT software.…”

Isolation by distance and non-identical patterns of gene flow within two river populations of the freshwater fish Rutilus rutilus (L. 1758)

“…These variables were regressed against genetic divergence whilst controlling for river distance. Although Mantel tests have come under recent criticism over issues related to type I errors associated with autocorrelation of data points and overestimation of statistical significance (Guillot and Rousset 2013), these tests may still be powerful approaches to spatial genetic analysis when data are independent and assumptions of normality are met (Diniz-Filho et al 2013). Data matrices were permuted 10 6 times.…”

Spatial genetic structure of the sea sandwort (<i>Honckenya peploides</i>) on Surtsey: an immigrant's journey

“…Twenty independent simulations were run for each K value with a burn-in length of 10 4 and a run length of 10 5 Markov chain Monte Carlo generations. The optimal value of K was estimated by using the R script STRUCTURE-sum- (Ehrich, 2006), to summarize the output files, calculate similarity coefficients between replicate runs and to plot the means of the estimated log posterior probability of the data over the replicate runs for each K value or L(K) in order to determine the highest level of hierarchical structure (Evanno et al, 2005). After detection of genetic divergence among populations, the analysis was repeated for each group to determine if any substructure existed below the highest hierarchical level.…”

“…Multiple introductions increase both the effective population size and the population growth rate, and have been shown to lead to an increase in gene diversity in newly colonized populations (Dlugosch and Parker, 2008). Therefore, it seems probable that long distance dispersal from multiple locations is a key driver of the current genetic structure on Surtsey.…”

“…Some plant invaders show diversity gain, a potential influence of mating systems (Sakai et al, 2001;Fernández-Mazuecos and Vargas, 2011). Although in general there are significant losses of both allelic richness and heterozygosity in introduced populations, and large gains in diversity are rare, multiple introductions have been shown to rescue the losses in diversity in a wide range of plant, animal and fungal taxa (reviewed in Dlugosch and Parker, 2008). Genetic diversity or allelic variation also appears to increase over long timescales, suggesting that gene flow plays a role in augmenting diversity over the long-term (e.g.…”