Spatial Patterns Of Genetic Variability Research Articles

Weak Population Genetic Structure of the Eurasian Crane <i>Grus grus</i> L.

The article presents an extended (as compared with our previous studies) analysis of the population genetic structure of a migratory wide-range bird species with a high abundance, the Eurasian Crane Grus grus L. Using seven highly polymorphic microsatellite loci, high and very similar values of genetic diversity parameters were obtained in the samples of both the western (G. g. grus) and eastern (G. g. lilfordi) subspecies. Coefficients of genetic differentiation between these subspecies (FST = 0.008, GST = 0.002) were also found to be low. According to AMOVA, 99% of genetic variation of G. grus is attributed to individual levels. Using the Bayesian clustering algorithm implemented in STRUCTURE software, no clear population-genetic structuring of the species was revealed. However, visualization of spatial patterns of genetic variability in Geneland showed the presence of a cluster of “pure” subspecies G. g. grus and G. g. lilfordi surrounding a cluster of individuals from the zone of intergradation of these subspecies. This result, along with the observed very low FST values, may indicate subtle genetic differences between cranes from the studied area, possibly having a mutational nature. The lower allelic richness and lack of private alleles in the eastern subspecies suggest that G. g. lilfordi is relatively evolutionary young and suggest its recent origin from some eastern marginal populations of the nominative western subspecies.

Comparing the Utility of Microsatellites and Single Nucleotide Polymorphisms in Conservation Genetics: Insights from a Study on Two Freshwater Fish Species in France

Biodiversity is facing an unprecedented crisis and substantial efforts are needed to conserve natural populations, especially in river ecosystems. The use of molecular tools to guide conservation practices in rivers has grown in popularity over the last decades, but the amount of precision and/or biological information that would be gained by switching from the traditional short tandem repeats (STRs) to the increasingly used single nucleotide polymorphisms (SNPs) is still debated. Here, we compared the usefulness of STRs and SNPs to study spatial patterns of genetic variability in two freshwater fish species (Phoxinus dragarum and Gobio occitaniae) in southern France. SNPs were obtained from a pool-seq procedure and mapped to new genome assemblies. They provided much more precise estimates of genetic diversity and genetic differentiation than STRs, but both markers allowed the detection of very similar genetic structures in each species, which could be useful for delineating conservation units. While both markers provided similar outcomes, there were two discrepancies in genetic structures that could, nonetheless, be explained by unrecorded stocking events. Overall, we demonstrated that SNPs are not unconditionally superior to STRs in the context of large-scale riverscape genetic conservation, and that the choice of marker should primarily be based on research questions and resources available.

Inference of local invasion pathways in two invasive crayfish species displaying contrasting genetic patterns

Abstract The efficient management of invasive alien species (IAS) requires the identification of their introduction pathways. Genetic assessments have proven useful to inform invasion pathways at large (national to worldwide) scales, but studies at local scales are still rare, despite their importance for guiding management. In this study, genetic analyses were used to identify local invasion pathways of two invasive crayfish species (the spiny‐cheek crayfish Faxonius limosus and the red swamp crayfish Procambarus clarkii) in a dense network of artificial lakes. We first characterized the spatial patterns of genetic variability, effective population sizes (Ne) and among‐lakes recent migration events for each species using neutral microsatellite markers. We then identified the environmental factors affecting genetic variability and inferred the potential local invasion pathways. Results revealed different patterns of genetic variability between the two species: F. limosus displayed very low levels of genetic diversity, Ne and spatial structuring compared to P. clarkii, which displayed high genetic diversity, Ne and spatial genetic structuring. We also demonstrated context‐dependent effects of different environmental factors (fishery management, spatial distribution and lake size) on genetic variability indices. We did not identify local invasion pathways for F. limosus due to limited genetic variability, likely caused by a strong founder effect and potential parthenogenetic reproduction. Contrastingly, multiple invasion pathways (release, contaminant, unaided/corridor spread and stowaway) were identified for P. clarkii. Synthesis and applications. Although limited in some particular cases (e.g. for species having experienced strong shaping events and/or displaying asexual reproductive modes), neutral genetic variation assessments can provide important insights for inferring local invasion pathways in complex landscapes for invasive alien species displaying short generation times and complex invasion histories.

Spatial and temporal variation in the genetic structure of Dascyllus trimaculatus (Pomacentridae) in the Bohol Sea

The potential of microsatellite markers to detect the spatial and temporal genetic structure of reef fish populations within a linear distance of 300 km in the absence of geographic barriers was tested in the Bohol Sea, central Philippines, using the three-spot damselfish Dascyllus trimaculatus. A total of 672 samples from 7 populations in the Bohol Sea were processed to determine temporal and spatial patterns of genetic variability using ten previously developed and tested microsatellite markers. The extent of differentiation was determined based on a variance-based measure of population structure FST and RST, and genetic distances Ds , DA, and dm2, each of which makes different assumptions on the process of migration, mutation, selection, and genetic drift. Patterns of temporal and spatial variation were consistent among 36 possible pairs of populations. Reef groups are defined as (1) the Mantigue-Dinagat on the northeast edge of the Bohol Sea; (2) the Selinog and Dapitan islands, to the southwest and central Bohol sea populations (3) Apo and (4) Sumilon to the west, and (5) Balicasag group to the northwest. The presence of structure in the absence of geographic barriers suggests the influence of strong surface circulation patterns that differ from the east to the west side of the region. The consistency of a population’s genetic signatures over multiple temporal sampling dates implies strong habitat selection for genotypes. Genetic breaks were detected at a distance 4x greater than the marine protected area’s average size, suggesting a minimum linear distance for networking of MPAs should be expanded to this scale. KEYWORDS: Conservation, Hardy-Weinberg equilibrium, marine protected area, microsatellite markers, population genetics, reef fish

Landscape genetic analyses of Cervus elaphus and Sus scrofa: comparative study and analytical developments.

Red deer and wild boar are two major game species whose populations are managed and live in areas impacted by human activities. Measuring and understanding the impact of landscape features on individual movements and spatial patterns of genetic variability in these species is thus of importance for managers. A large number of individuals sampled across Wallonia (Belgium) for both species have been genotyped using microsatellite markers (respectively > 1700 and > 1200 genotyped individuals) and some individuals have also been followed using a capture-mark-recapture (CMR) protocol. The combined data set represents an unprecedented opportunity to study and compare the environmental factors impacting the interconnectivity of these large mammals. The present study describes and uses a landscape genetic workflow to compare spatial patterns of genetic variability and the impact of environmental factors on genetic differentiation. For the latter analyses, we investigate the correlation between genetic and environmental distances (pairwise approach) and also between local genetic dissimilarity and environmental conditions (point approach). Preliminary analyses of CMR data confirm that motorways act as significant barriers to dispersal. However, analyses performed with the pairwise approach do not highlight any evidence of an impact of motorways on genetic differentiation, which is presumably due to their recent establishment. Complementary analyses performed with the point approach reveal that low altitude tends to be associated with higher genetic dissimilarity. From a methodological point of view, the present workflow illustrates the complementary application of both pairwise and point approaches, as well as univariate and multivariate analyses.

Geography Plays a More Important Role than Soil Composition on Structuring Genetic Variation of Pseudometallophyte Commelina communis.

Pseudometallophytes are excellent models to study microevolution and local adaptation to soil pollution, as they can grow both on metalliferous and contrasting non-metalliferous soils. Although, there has been accumulating evidence for the effects of edaphic conditions and geographical isolation on the genetic structure of pesudometallophytes, it is still a difficult problem in evolutionary biology to assess their relative importance. In this study, we investigated the spatial patterns of genetic variability, population differentiation and genetic groups in pseudometallophyte Commelina communis with 12 microsatellite loci. Eight metallicolous and six non-metallicolous populations of C. communis were sampled from cupriferous sites and surrounding non-contaminated areas in China. Neither significant reduction in genetic diversity nor apparent founder and bottleneck effects were observed in metallicolous populations of C. communis. Based on Bayesian and Neighbor-Joining clustering analyses and a principal coordinates analysis, all sampled populations were found to be mainly separated into three genetic groups, corresponding well to their geographical locations rather than edaphic origins. Moreover, a significant and strong correlation between population genetic divergence and geographical distance were detected by Mantel test (r = 0.33; P < 0.05) and multiple matrix regression with randomization (MMRR; βD = 0.57, P < 0.01). However, the effect of copper concentration on genetic patterns of C. communis was not significant (MMRR; βE = -0.17, P = 0.12). Our study clearly demonstrated that the extreme edaphic conditions in metalliferous areas had limited effects on the genetic variability in C. communis. Geographic distance played a more important role in affecting the genetic structure of C. communis than soil composition did. In C. communis, the geographically disjunctive populations on metalliferous soils had multiple origins and evolved independently from nearby non-metallicolous populations.

Genetic conservation of Ficus bonijesulapensis R.M. Castro in a dry forest on limestone outcrops

Ficus bonijesulapensis is endemic to a seasonally dry forest on limestone outcrops and it is arranged in disjunct areas in the Cerrado and Caatinga Domains. Species of this genus are considered to be key plants in tropical forests, since they provide resources during periods of scarcity of other resources and, additionally, they contribute in a plant community's restoration. Therefore, the conservation of these species in their natural habitat contributes to the maintenance of the long-term population viability and their genetic diversity. We used nine ISSR primers to analyze the genetic diversity and the genetic spatial patterns of 15 populations of F. bonijesulapensis. We obtained 75 polymorphic bands, the expected heterozygosity (He) was 0.30 and AMOVA showed that most of the genetic diversity was found within populations (77%). The historical gene flow was 1.1 migrants and the Bayesian genetic structure assigned individuals genotypes to eight groups. However, there was not a spatial pattern of genetic variability according to a multivariate correlogram and as confirmed by Mantel's test (r = 0.06, p = 0.68). Eight management units (MU) were proposed and were aiming at the MU's ability to maintain minimally viable populations and a higher genetic variability.

Study of the genetic diversity and structure of a natural population of Nectandra megapotamica (Spreng.) Mez. using RAPD markers.

Nectandra megapotamica (Spreng.) Mez. is a tree species that naturally occurs in the Atlantic Forest, Brazil. The aim of this study was to evaluate the genetic diversity and structure of a natural population of 12 N. megapotamica individuals using random amplified polymorphic DNA markers. Eleven primers were used in this study, producing 81 bands, of which 98.99% were polymorphic. Analysis using STRUCTURE defined three different clusters (K = 3), results that were consistent with those of principal coordinates analysis. Both Nei's genetic diversity (h = 0.33) and Shannon's diversity index (I = 0.49) were relatively high. Analysis of molecular variance indicated that 24.89% of the genetic variability was among clusters, while the remaining 75.11% was within clusters. The Mantel test showed a weak correlation between genetic and geographic distances (r = 0.25, P = 0.105). Overall, the results revealed high levels of genetic diversity within clusters and high genetic differentiation among clusters without any spatial pattern of genetic variability. In addition, gene flow was independent of the geographical distribution and was compatible with the hierarchical island model.

Microbial metabolism: optimal control of uptake versus synthesis

Microbes require several complex organic molecules for growth. A species may obtain a required factor by taking up molecules released by other species or by synthesizing the molecule. The patterns of uptake and synthesis set a flow of resources through the multiple species that create a microbial community. This article analyzes a simple mathematical model of the tradeoff between uptake and synthesis. Key factors include the influx rate from external sources relative to the outflux rate, the rate of internal decay within cells, and the cost of synthesis. Aspects of demography also matter, such as cellular birth and death rates, the expected time course of a local resource flow, and the associated lifespan of the local population. Spatial patterns of genetic variability and differentiation between populations may also strongly influence the evolution of metabolic regulatory controls of individual species and thus the structuring of microbial communities. The widespread use of optimality approaches in recent work on microbial metabolism has ignored demography and genetic structure.

Assessing spatial genetic structure from molecular marker data via principal component analyses: A case study in a &amp;lt;i&amp;gt;Prosopis&amp;lt;/i&amp;gt; sp. forest

Advances in genotyping technology, such as molecular markers, have noticeably improved our capacity to characterize genomes at multiple loci. Concomitantly, the methodological framework to analyze genetic data has expanded, and keeping abreast with the latest statistical developments to analyze molecular marker data in the context of spatial genetics has become a difficult task. Most methods in spatial statistics are devoted to univariate data whereas the nature of molecular marker data is highly dimensional. Multivariate methods are aimed at finding proximities between entities characterized by multiple variables by summarizing information in few synthetic variables. In particular, Principal Component analysis (PCA) has been used to study genetic structure of geo-referenced allele frequency profiles, incorporating spatial information with a posteriori analysis. Conversely, the recently developed spatially restricted PCA (sPCA) explicitly includes spatial data in the optimization criterion. In this work, we compared the results of the application of PCA and sPCA in the study of the spatial genetic structure at fine scale of a Prosopis flexuosa and P. chilensis hybrid swarm. Data consisted in the genetic characterization of 87 trees sampled in Córdoba, Argentina and genotyped at six microsatellites, which yielded 72 alleles. As expected, principal components explained more variance than sPCA components, but were less spatially autocorrelated. The maps obtained by the interpolation of sPC1 values allowed a better visualization of a patchy spatial pattern of genetic variability than the PC1 synthetic map. We also proposed a PC-sPC scatter plot of allele loadings to better understand the allele contributions to spatial genetic variability.

A new eigenfunction spatial analysis describing population genetic structure

Several methods of spatial analyses have been proposed to infer the relative importance of evolutionary processes on genetic population structure. Here we show how a new eigenfunction spatial analysis can be used to model spatial patterns in genetic data. Considering a sample of n local populations, the method starts by modeling the response variable (allele frequencies or phenotypic variation) against the eigenvectors sequentially extracted from a geographic distance matrix (n × n). The relationship between the coefficient of determination (R(2)) of the models and the cumulative eigenvalues, which we named the spatial signal-representation (SSR) curve, can be more efficient than Moran's I correlograms in describing different patterns. The SSR curve was also applied to simulated data (under distinct scenarios of population differentiation) and to analyze spatial patterns in alleles from microsatellite data for 25 local populations of Dipteryx alata, a tree species endemic to the Brazilian Cerrado. The SSR curves are consistent with previous phylogeographical patterns of the species, revealing combined effects of isolation-by-distance and range expansion. Our analyses demonstrate that the SSR curve is a useful exploratory tool for describing spatial patterns of genetic variability and for selecting spatial eigenvectors for models aiming to explain spatial responses to environmental variables and landscape features.

Colonization of the Aeolian Islands byPimelia rugulosa rugulosaGermar, 1824 (Coleoptera: Tenebrionidae) inferred from the genetic structure of populations: geological and environmental relations

The darkling beetle Pimelia rugulosa rugulosa Germar, 1824 was selected to investigate the process of colonization in a volcanic archipelago and the role of volcanism in determining spatial patterns of genetic variability. Analyses were conducted in the Aeolian Islands, located in the central Mediterranean directly off the Sicilian coast. Genetic variability and geographic structure were studied in individuals from each island of the archipelago based on sequences of the cytochrome c oxidase subunit 2 mitochondrial gene; a network approach was employed to identify haplotype lineages. A strong genetic structure, with no haplotype sharing among islands, was observed. Six separate lineages were identified that independently colonized different islands of the archipelago from the mainland and differentiated locally to form small haplogroups. Variability of observed haplogroups is correlated with island age and a positive correlation between tenebrionid diversity and mitotype diversity is reported. Some, yet undescribed, catastrophic event is hypothesized to explain the depletion of a substantial part of the genetic, as well as biological diversity in the island of Filicudi. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 104, 29–37.

Revealing cryptic spatial patterns in genetic variability by a new multivariate method

Increasing attention is being devoted to taking landscape information into account in genetic studies. Among landscape variables, space is often considered as one of the most important. To reveal spatial patterns, a statistical method should be spatially explicit, that is, it should directly take spatial information into account as a component of the adjusted model or of the optimized criterion. In this paper we propose a new spatially explicit multivariate method, spatial principal component analysis (sPCA), to investigate the spatial pattern of genetic variability using allelic frequency data of individuals or populations. This analysis does not require data to meet Hardy-Weinberg expectations or linkage equilibrium to exist between loci. The sPCA yields scores summarizing both the genetic variability and the spatial structure among individuals (or populations). Global structures (patches, clines and intermediates) are disentangled from local ones (strong genetic differences between neighbors) and from random noise. Two statistical tests are proposed to detect the existence of both types of patterns. As an illustration, the results of principal component analysis (PCA) and sPCA are compared using simulated datasets and real georeferenced microsatellite data of Scandinavian brown bear individuals (Ursus arctos). sPCA performed better than PCA to reveal spatial genetic patterns. The proposed methodology is implemented in the adegenet package of the free software R.

The Organization of the Mitochondrial Control Region in 2 Brachyuran Crustaceans: Ucides cordatus (Ocypodidae) and Cardisoma guanhumi (Gecarcinidae)

The control region (CR) is the largest noncoding segment of the mitochondrial DNA and includes the major regulatory elements for its replication and expression. In addition, the high level of intraspecific genetic variability found in the CR favors its use in phylogeographical and population genetic studies of a variety of organisms. However, most of the work on the structure of the CR has focused on vertebrates and insects, and little is known about the evolution of the CR in other taxa. In this study, we sequenced the entire CR of several individuals of 2 crab species: Ucides cordatus (Ocypodidae) and Cardisoma guanhumi (Gecarcinidae). There were neither large conserved regions in the CR of either species nor any similarity among species at the nucleotide level. However, the spatial pattern of genetic variability on the CR was similar among species. In addition, interesting similarities were found in the formation of stable secondary structures and in the position of regulatory elements. These results indicate that the evolution of CR in crustaceans is a remarkably dynamic process, with most homology among species being found at the secondary level.

Spatial patterns of cone serotiny in Pinus banksiana in relation to fire disturbance

Fire disturbance effects on tree species distribution and landscape pattern have been widely studied. However, the effects of differences among fire regimes on the spatial pattern of genetic variability within a tree species have received less attention. The objectives of this study were to examine (a) whether the marked gradient in serotiny in Pinus banksiana along its southern range limit is related to differences in fire regimes and (b) at what scale serotiny varies most strongly in P. banksiana in the US Midwest. P. banksiana in the 450,000 ha Pine Barrens area in northwestern Wisconsin, USA showed a marked broad scale pattern in serotiny. The percentage of serotinous trees was highest in the northeast (mean 83%, S.D. 13.5) and lowest in the southwest (mean 9%, S.D. 3.7). Historic fire regimes were inferred from pre-European settlement (mid-1800s) vegetation data. Serotiny was highest in pine forests that exhibited stand-replacing fires, and lowest in savannas where more frequent but less intense ground fires occurred. The data presented in this study suggest possible spatial control of genetic variability within a tree species by an ecological process (disturbance) at the landscape-scale.

New microsatellite markers for the endemic Mediterranean seagrass Posidonia oceanica

AbstractThe seagrass Posidonia oceanica is endemic to the Mediterranean Sea, where it plays an important role in coastal ecosystem dynamics. Because of this important role and concerns about the observed regression of some meadows, population genetic studies of this species have been promoted. However, the markers used until now were not polymorphic enough to efficiently assess the level and spatial pattern of genetic variability. Hypervariable molecular markers were obtained by screening a genomic library enriched for microsatellite dinucleotide repeats. Among 25 primer pairs defined, eight amplified polymorphic microsatellites with an encouraging level of variability at the two geographical scales sampled.

Spatial patterns of genetic variability in Italian chestnut (Castanea sativa)

The spatial patterns of genetic variation for 15 loci in 18 Italian populations of chestnut were analyzed. Multivariate analysis and spatial autocorrelation analysis showed two clinal variations, one in a west–east direction, the other in a north–south direction. There was a nonrandom spatial pattern of at least three alleles and a marked heterogeneity among populations of many others. An explanation is proposed in terms of migration flow for the majority of the polymorphisms and of selection for the three autocorrelated alleles. However, anthropic interferences may also be important. Key words: chestnut, electrophoresis, spatial autocorrelation, correspondence analysis, genetic boundaries, discriminant analysis.