Assessment of genetic differentiation of populations by analysis of molecular variance (analytical review)

Different approaches to using the analysis of molecular variance (AMOVA) to assess the genetic differentiation of populations have been compared in the research. Data on 11 microsatellite loci of 84 bulls of seven breeds were used. The results were compared for three options of the AMOVA module of the GenAlEx 6.502 program: the allele distance matrix (calculated FST(W&C)(=θ) statistics – variant AMOVA1); the genotype distance matrix (ΦPT– AMOVA2); and the allele size difference matrix (RST– AMOVA3). Similar summary estimates of the genetic differentiation of breeds were obtained: FST(W&C)= 0.108, ΦPT= 0.115, RST= 0.110 (all with pperm≤ 0.001). Between the estimates of FST(W&C)and ΦPTfor each locus, the correlation coefficient was 0.99 (pvalue<0.0001); no statistically significant correlations with RSTwere found. A high correlation of FST(W&C)and ΦPTwith the estimates of differentiation according to Nei’s (0.96) was found. Programs other than GenAlEx (Arlequin v.3.5, GenePop v.4.7.3, RST22) gave similar AMOVA estimates. The negative linear dependence of FST(W&C)and ΦPTon the level of the average heterozygosity of the breed samples was established (R2= 0.6, rS= -0.75 for pvalue < 0.02) and the absence of such dependence for RST(R2= 0.04, rS= -0.23 for pvalue= 0.47). The standardization of the FST(W&C)and ΦPTestimates according to Hedrick’s eliminated this dependence and raised the initial estimates to 0.35 and 0.37, respectively. The latter were comparable to the estimates obtained by the Nei-Hedrick’s (0.364-0.375), Jost’s (0.292), and Morisit-Horn’s (0.308) methods. The Mantel correlations between the matrices of paired genetic distances (GD) calculated by different measures were >0.9 in most cases. The projections of the GD matrices in the principal coordinate analysis (PCoA) on the 2D plane were generally similar. The PCoA identified a cluster of Holstein «ecotypes», a cluster of «Red» breeds, and a branch of the Jersey breed. In the two-factor AMOVA of data on clusters (as two «regions»), the interregional GD was 0.357; the differentiation of breeds within the «regions» did not exceed 0.027. Modeling the association of breeds with close to zero GD resulted in an increase in the number of alleles per locus in the «new» breeds by 29 %, and an increase in the combined estimate of genetic differentiation by 29-46 %. The results obtained can be used in the development of measures for the conservation of endangered breeds.

Sensitivity of migratory connectivity estimates to spatial sampling design

Background The use of statistical methods to quantify the strength of migratory connectivity is commonplace. However, little attention has been given to their sensitivity to spatial sampling designs and scales of inference. Methods We examine sources of bias and imprecision in the most widely used methodology, Mantel correlations, under a range of plausible sampling regimes using simulated migratory populations. Results As Mantel correlations depend fundamentally on the spatial scale and configuration of sampling, unbiased inferences about population-scale connectivity can only be made under certain sampling regimes. Within a contiguous population, samples drawn from smaller spatial subsets of the range generate lower connectivity metrics than samples drawn from the range as a whole, even when the underlying migratory ecology of the population is constant across the population. Random sampling of individuals from contiguous subsets of species ranges can therefore underestimate population-scale connectivity. Where multiple discrete sampling sites are used, by contrast, overestimation of connectivity can arise due to samples being biased towards larger between-individual pairwise distances in the seasonal range where sampling occurs (typically breeding). Severity of all biases was greater for populations with lower levels of true connectivity. When plausible sampling regimes were applied to realistic simulated populations, accuracy of connectivity measures was maximised by increasing the number of discrete sampling sites and ensuring an even spread of sites across the full range. Conclusions These results suggest strong potential for bias and imprecision when making quantitative inferences about migratory connectivity using Mantel statistics. Researchers wishing to apply these methods should limit inference to the spatial extent of their sampling, maximise their number of sampling sites, and avoid drawing strong conclusions based on small sample sizes.

Geographically structured genetic diversity in the cave beetle Darlingtonea kentuckensis Valentine, 1952 (Coleoptera, Carabidae, Trechini, Trechina)

Cave beetles of the eastern USA are one of many poorly studied groups of insects and nearly all previous work delimiting species is based solely on morphology. This study assesses genetic diversity in the monotypic cave carabid beetle genus DarlingtoneaValentine 1952, to test the relationship between putative geographical barriers to subterranean dispersal and the boundaries of genetically distinct groups. Approximately 400bp of the mitochondrial cytochrome oxidase I (COI) gene was sequenced from up to four individuals from each of 27 populations, sampled from caves along the escarpments of the Mississippian and Cumberland plateaus in eastern Kentucky, USA. The 81 individuals sequenced yielded 28 unique haplotypes. Hierarchical analyses of molecular variance (AMOVA) within and among geographically defined groups tested two a priori hypotheses of structure based on major and minor river drainages, as well as genetic distance clusters defined a posteriori from an unrooted analysis. High genetic differentiation (FST) between populations was found across analyses. The influence of isolation by distance could potentially account for much but not all of the variation found among geographically defined groups at both levels. High variability among the three northernmost genetic clusters (FCT), low variability among populations within clusters (FSC), and low within-cluster Mantel correlations indicate the importance of unidentified likely intra-karst barriers to gene flow separating closely grouped cave populations. Overall phylogeographic patterns are consistent with previous evidence of population isolation among cave systems in the region, revealing geographically structured cryptic diversity in Darlingtonea over its distribution. The landscape features considered a priori in this study were not predictive of the genetic breaks among the three northern clusters, which are genetically distinct despite their close geographic proximity.

HOW TO MEASURE THE INFLUENCE OF LANDSCAPE ON POPULATION GENETIC STRUCTURE: DEVELOPING RESISTANCE SURFACES USING A PATTERN-ORIENTED MODELING APPROACH

There are several approaches to understand how a landscape, with its several components, affects the genetic population structure by imposing resistance to gene flow. Here we propose the creation of resistance surfaces using a Pattern-Oriented Modeling approach to explain genetic differentiation, estimated by pairwise FST, among “Baruzeiro” populations (Dipteryx alata), a tree species widely distributed in Brazilian Cerrado. To establish the resistance surface, we used land use layers from the area in which the 25 “Baruzeiro” populations were sampled, generating 10000 resistance surfaces. To establish the resistance surface, we used land use layers from the area in which the 25 “Baru” populations were sampled, generating 10000 resistance surfaces. We randomized the cost values for each landscape component between 0 and 100. We use these surfaces to calculate pairwise matrices of the effective resistance among populations. Mantel test revealed a correlation of pairwise FST with a geographical distance equal to r = 0.48 (P < 0.001), whereas the Mantel correlations between pairwise FST and the generated resistance matrices ranged between r = −0.2019 and r= 0.6736. Partial regression on distance matrices was used to select the resistance matrix that provided the highest correlation with pairwise FST, based on the AIC criterion. The selected models suggest that the areas with lower resistance are characterized as natural savanna habitats of different forms, mainly arboreal dense savannas. In contrast, roads, big rivers, and agricultural lands cause higher resistance to gene flow.

Superposición de la dieta del pez león Pterois volitans (Teleostei: Scorpaenidae) con la de peces nativos de nivel trófico similar en Cuba

The spread of the Indo-Pacific lionfish has been one of the most rapid marine fish invasions in the history of the tropical and subtropical western Atlantic, and populations of this species pose a threat to native fishes feeding at similar trophic levels due to competition for food. To determine dietary overlap, 899 lionfish and 377 native fishes of the families Haemulidae, Holocentridae, Serranidae and Lutjanidae were caught in three Cuban localities, and their stomach contents were analyzed based on the number of items, frequency, volume and index of relative importance. Diet composition was similar in the studied localities; Lutjanidae, Serranidae and lionfish mainly fed on fish while Haemulidae and Holocentridae primarily consumed small benthic invertebrates. Mantel correlations showed that the consumption of fish and crustaceans did not increase as lionfish increased in size. The degree of dietary overlap between lionfish and some native fishes depends on locality, ecological zone and the characteristics of each family, confirming the opportunistic nature of the invader. It is likely that native fishes are not affected by competition with lionfish for food because they feed on the mostabundant and available organisms; therefore, food availability is not a limiting factor for these groups.

Efficiency in inventories of ants in a forest reservein Central Amazonia

The objective of this work was to evaluate an inventory method efficiency for ants. We used subsamples collected in 24 transects of 100 m, distributed in 6 plots of 600 ha each in primary forest, as part of a long-term project. Ten litter subsamples were extracted per transect using Winkler extractors. Ants were identified to genus level, and Crematogaster, Gnamptogenys and Pachycondyla genera to species/morphospecies level. To evaluate the consequences of reduced sampling on the retention of ecological information, we estimated the lowest number of subsamples needed to detect the effects of environmental variables. Multidimensional scaling (MDS) was used to generate dissimilarity matrices, and Mantel correlations between each reduced-sampling effort and maximum effort were used as an index of how much information was maintained and could still be used in multivariate analyses. Lower p-values was observed on the effect of soil pH in the community of genera, and on the effect of the litter volume for the community of Crematogaster. The trend was still detectable in the analysis based on reduced-sampling. The number of subsamples can be reduced, and the cost-efficiency of the protocol can be improved with little loss of information.

Are floristic and edaphic patterns in Amazonian rain forests congruent for trees, pteridophytes and Melastomataceae?

Studies in western Amazonian forests have found that similarities in soil cation concentration and texture explain floristic similarities between sites, when these are measured using trees, pteridophytes or Melastomataceae. However, it is not known to what extent the three plant groups react to the same soil characteristics, because tree studies have almost always been conducted in different areas than studies on the understorey plant groups. We made inventories in 23 sites representing non-inundated rain forests on clayey to loamy soil in three regions of western Amazonia. Significant Mantel correlations between the floristic patterns of trees and pteridophytes were found in all three regions when floristic differences were measured with species presence–absence data. When species abundance data were used, and when the floristic patterns of trees and Melastomataceae were compared, significant correlations were found in one or two regions. Mantel correlations between plant groups were highest in the two regions where the observed variation in soil characteristics was largest. In all regions, the same soil variables emerged with significant Mantel correlations with trees, pteridophytes and Melastomataceae. Soil calcium and magnesium were most frequently retained in the models of multiple regression on distance matrices. On average, soil differences explained 50% of the variation in floristic differences (range = 14–84%), and geographical distances explained 16% (range = 0–64%). Our results demonstrate that beta diversities of the three plant groups are highly correlated, and that much of this congruence is explained by similar reactions to soil variation. These results support the idea that pteridophytes, and to a lesser degree Melastomataceae, can be used as indicators of general floristic and edaphic patterns in Amazonian rain forests. Since understorey plants are much quicker to inventory than trees, this would make it possible to recognize and map floristic patterns over huge areas of lowland Amazonia within a reasonable time.

Is a Multivariate Consensus Representation of Genetic Relationships Among Populations Always Meaningful?

To determine the relationships among closely related populations or species, two methods are commonly used in the literature: phylogenetic reconstruction or multivariate analysis. The aim of this article is to assess the reliability of multivariate analysis. We describe a method that is based on principal component analysis and Mantel correlations, using a two-step process: The first step consists of a single-marker analysis and the second step tests if each marker reveals the same typology concerning population differentiation. We conclude that if single markers are not congruent, the compromise structure is not meaningful. Our model is not based on any particular mutation process and it can be applied to most of the commonly used genetic markers. This method is also useful to determine the contribution of each marker to the typology of populations. We test whether our method is efficient with two real data sets based on microsatellite markers. Our analysis suggests that for closely related populations, it is not always possible to accept the hypothesis that an increase in the number of markers will increase the reliability of the typology analysis.