Thannya Nascimento Soares

Mantel test in population genetics

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.

A review of techniques for spatial modeling in geographical, conservation and landscape genetics

Most evolutionary processes occur in a spatial context and several spatial analysis techniques have been employed in an exploratory context. However, the existence of autocorrelation can also perturb significance tests when data is analyzed using standard correlation and regression techniques on modeling genetic data as a function of explanatory variables. In this case, more complex models incorporating the effects of autocorrelation must be used. Here we review those models and compared their relative performances in a simple simulation, in which spatial patterns in allele frequencies were generated by a balance between random variation within populations and spatially-structured gene flow. Notwithstanding the somewhat idiosyncratic behavior of the techniques evaluated, it is clear that spatial autocorrelation affects Type I errors and that standard linear regression does not provide minimum variance estimators. Due to its flexibility, we stress that principal coordinate of neighbor matrices (PCNM) and related eigenvector mapping techniques seem to be the best approaches to spatial regression. In general, we hope that our review of commonly used spatial regression techniques in biology and ecology may aid population geneticists towards providing better explanations for population structures dealing with more complex regression problems throughout geographic space.

Landscape conservation genetics of Dipteryx alata (“baru” tree: Fabaceae) from Cerrado region of central Brazil

In this paper random amplified polymorphic DNA (RAPD) was used to evaluate the degree of among-population differentiation and associated spatial patterns of genetic divergence for Dipteryx alata Vogel populations from Cerrado region of central Brazil, furnishing support for future programs of conservation of this species. We analyzed patterns of genetic and spatial population structure using 45 RAPD loci scored for 309 trees, sampled from five different regions with two populations each. Genetic structure analysis suggested that panmixia null hypothesis can be rejected, with significant among-population components of 15%. Hierarchical partition by Analysis of Molecular Variance (AMOVA) shows that 5% of genetic variation is within regions, whereas 10% of variation is among regions, and these results were confirmed by a Bayesian analyses on HICKORY. The Mantel correlogram revealed that this divergence is spatially structured, so that local populations situated at short geographic distances could not be considered independent units for conservation and management. However, genetic discontinuities among populations were found in the northwest and southeast parts of the study area, corresponding to regions of recent socio-economic expansion and high population density, respectively. Taking both geographic distances and genetic discontinuities into account it is possible to establish a group of population to be conserved, covering most of D. alata geographic distribution and congruent with previously established priority areas for conservation in the Cerrado region.

Planning for optimal conservation of geographical genetic variability within species

Systematic Conservation Planning (SCP) involves a series of steps that should be accomplished to determine the most cost-effective way to invest in conservation action. Although SCP has been usually applied at the species level (or hierarchically higher), it is possible to use alleles from molecular analyses at the population level as basic units for analyses. Here we demonstrate how SCP procedures can be used to establish optimum strategies for in situ and ex situ conservation of a single species, using Dipteryx alata (a Fabaceae tree species widely distributed and endemics to Brazilian Cerrado) as a case study. Data for the analyses consisted in 52 alleles from eight microsatellite loci coded for a total of 644 individual trees sampled in 25 local populations throughout species’ geographic range. We found optimal solutions in which seven local populations are the smallest set of local populations of D. alata that should be conserved to represent the known genetic diversity. Combining these several solutions allowed estimating the relative importance of the local populations for conserving all known alleles, taking into account the current land-use patterns in the region. A germplasm collection for this species already exists, so we also used SCP approach to identify the smallest number of populations that should be further collected in the field to complement the existing collection, showing that only four local populations should be sampled for optimizing the species ex situ representation. The initial application of the SCP methods to genetic data showed here can be a useful starting point for methodological and conceptual improvements and may be a first important step towards a comprehensive and balanced quantitative definition of conservation goals, shedding light to new possibilities for in situ and ex situ designs within species.

Niche modelling and landscape genetics of Caryocar brasiliense ("Pequi" tree: Caryocaraceae) in Brazilian Cerrado: an integrative approach for evaluating central-peripheral population patterns.

Complex and integrative approaches may be necessary to understand the abundant-centre model and the patterns in genetic diversity that may be explained by this model. Here we developed an integrated framework to study spatial patterns in genetic diversity within local populations, coupling genetic data, niche modelling and landscape genetics, and applied this framework to evaluate population structure of Caryocar brasiliense, an endemic tree from the Brazilian Cerrado. We showed different geographical patterns for genetic diversity, allelic richness and inbreeding levels, estimated using microsatellite data for ten local populations. Ecological suitability was estimating by combining five niche modelling techniques. Genetic diversity tend to follow a central-periphery model and is associated with ecological variables. On the other hand, inbreeding levels may be alternatively explained by isolation processes and habitat fragmentation more related to intense recent human occupation in the southern border of the biome, or by deeper historical patterns in the origin of the populations. Although still suffering from some of the problems of central-periphery analysis (small number of local populations), our analyses show how these patterns can be better investigated and offering a better understanding of the processes structuring genetic diversity within species’ geographic ranges.

Development of microsatellite markers for the neotropical tree species Dipteryx alata (Fabaceae)

PREMISE OF THE STUDY Microsatellite markers were developed for the population genetic analyses of the neotropical tree Dipteryx alata (Fabaceae). METHODS AND RESULTS Microsatellites were developed from a genomic shotgun library. Polymorphism at each microsatellite loci was analyzed based on 94 individuals from three populations. Eight loci amplified successfully and presented one to 10 alleles, and expected heterozygosities ranged from 0.097 to 0.862. Four loci also amplified in Pterodon emarginatus and presented similar polymorphism. CONCLUSION The eight microsatellite primer pairs are potentially suitable for population genetic studies and successfully amplified in another Fabaceae species.

Paternity testing and behavioral ecology: a case study of jaguars (Panthera onca) in Emas National Park, Central Brazil

We used microsatellite loci to test the paternity of two male jaguars involved in an infanticide event recorded during a long-term monitoring program of this species. Seven microsatellite primers originally developed for domestic cats and previously selected for Panthera onca were used. In order to deal with uncertainty in the mothers genotypes for some of the loci, 10000 values of W were derived by simulation procedures. The male that killed the two cubs was assigned as the true sire. Although the reasons for this behavior remain obscure, it shows, in principle, a low recognition of paternity and kinship in the species. Since the two cubs were not very young, one possibility is that the adult male did not recognize the cubs and killed them for simple territorial reasons. Thus, ecological stress in this local population becomes a very plausible explanation for this infanticide, without further sociobiological implications.

RAPD variation and population genetic structure of Physalaemus cuvieri (Anura: Leptodactylidae) in Central Brazil.

Studies about the organization of the genetic variability and population structure in natural populations are used either to understand microevolutionary processes or the effects of isolation by human-inducted landscape modifications. In this paper, we analyzed patterns of genetic population structure using 126 RAPD loci scored for 214 individuals of Physalaemus cuvieri, sampled from 18 local populations. Around 97% of these loci were polymorphic. The among-population variation component (ΦST) obtained by AMOVA was equal to 0.101 and θB obtained using a Bayesian approach for dominant markers was 0.103. Genetic divergence, analyzed by Mantel spatial correlogram, revealed only a short-distance significant correlation between genetic and geographic distances. This is expected if low levels of population differentiation, due to high abundance buffering the effect of stochastic processes, are combined with low spatially restricted gene flow. Although this may be consistent with the current knowledge of species’ biology, the spatial distribution of local populations observed in this study also suggest that, at least in part, recent human occupation and habitat fragmentation may also explain part of the interpopulational component of the genetic variation.

Patterns of genetic variability in central and peripheral populations of Dipteryx alata (Fabaceae) in the Brazilian Cerrado

This study tested whether genetic parameters in Dipteryx alata populations, estimated from genomic and chloroplastidial microsatellite markers, were distributed according to a central-peripheral model, inferring which factors drive this spatial distribution of genetic variability within populations. For each of the 23 populations sampled throughout the species’ range, the mean number of alleles per locus, expected heterozygosity and intrapopulation fixation indices were calculated using a rarefaction approach based on 54 alleles from 8 nuclear microsatellites. Explanatory variables were grouped into three subsets: the ecological suitability estimated by combining different techniques of ecological niche modeling, variables expressing human occupation, and a historical variable represented by the first eigenvector from the pairwise FST matrix based on cpDNA microsatellites. Each response variable was modeled using first (linear) and second (quadratic) order trend surface analysis (TSA). Multiple regressions were then used to evaluate the relative effects of the explanatory variables, based on AIC multi-model selection. In general, the genetic parameters did not follow a classical central-periphery model. Ecological suitability had a significance influence in all genetic parameters, so more suitable regions have higher genetic diversity and low endogamy. There was also a relationship between fixation indices and human impacts. The high genetic diversity in the southwestern region of Cerrado suggested that recent range expansion (after the Last Glacial Maximum) may also influenced the observed intrapopulation genetic patterns. Thus, complex combinations of both historical and ecological drivers, as well as contemporary human occupation, seem to drive current genetic composition within D. alata populations throughout its geographic range.

Multi-objective optimization for plant germplasm collection conservation of genetic resources based on molecular variability

Germplasm collections play a significant role among strategies for conservation of diversity. It is common to select a core collection to represent the genetic diversity of a germplasm collection, in order to minimize the cost of conservation, while ensuring the maximization of genetic variation. We aimed to solve two main problems: (1) to select a set of individuals, from an in situ data set, that is genetically complementary to an existing germplasm collection, and (2) to define a core collection for a germplasm collection. We proposed a new multi-objective optimization (MOO) approach based on principles of systematic conservation planning (SCP) incorporating heterozygosity information; therefore, optimization takes genotypic diversity and variability patterns into account as well. As a case study, we used Dipteryx alata microsatellite loci information from two sources, an ex situ germplasm collection located at the Agronomy School of the Federal University of Goiás (UFG-AS), and an in situ data set composed of 642 sampled individual trees. We were able to identify within a population of several individuals, the exact accessions/samples that should be chosen in order to preserve the species diversity. We found that material from nine in situ individual trees are enough to complement the UFG-AS germplasm collection as it is, and that it is possible to define a core collection of 20 individual trees representing all studied genetic diversity. Moreover, we defined a method (a protocol) to deal with large amounts of accessions in the context of MOO. The proposed approach can be used to help constructing collections with maximal allelic richness and can also be extended to the in situ conservation. As far as we know, this is the first time that principles of SCP and the MOO approach are applied to the problem of complementing a germplasm collection and of finding a core collection for a germplasm collection.