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Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data.

ABSTRACT: A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation.

SUBMITTER: Wagner HH

PROVIDER: S-EPMC1449570 | biostudies-other | 2005 Mar

REPOSITORIES: biostudies-other

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Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data.

Wagner Helene H HH Holderegger Rolf R Werth Silke S Gugerli Felix F Hoebee Susan E SE Scheidegger Christoph C

Genetics 20050116 3

A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of ...[more]

PMID: 15654102

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Project description:BackgroundThe dynamic re-emergence of visceral leishmaniasis (VL) in south Europe and the northward shift to Leishmania-free European countries are well-documented. However, the epidemiology of VL due to Leishmania infantum in southeastern (SE) Europe and the Balkans is inadequately examined. Herein, we aim to re-evaluate and compare the population structure of L. infantum in SE and southwestern (SW) Europe.MethodsLeishmania strains collected from humans and canines in Turkey, Cyprus, Bulgaria, Greece, Albania and Croatia, were characterized by the K26-PCR assay and multilocus enzyme electrophoresis (MLEE). Genetic diversity was assessed by multilocus microsatellite typing (MLMT) and MLM Types were analyzed by model- and distance- based algorithms to infer the population structure of 128 L. infantum strains.ResultsL. infantum MON-1 was found predominant in SE Europe, whilst 16.8% of strains were MON-98. Distinct genetic populations revealed clear differentiation between SE and SW European strains. Interestingly, Cypriot canine isolates were genetically isolated and formed a monophyletic group, suggesting the constitution of a clonal MON-1 population circulating among dogs. In contrast, two highly heterogeneous populations enclosed all MON-1 and MON-98 strains from the other SE European countries. Structure sub-clustering, phylogenetic and Splitstree analysis also revealed two distinct Croatian subpopulations. A mosaic of evolutionary effects resulted in consecutive sub-structuring, which indicated substantial differentiation and gene flow among strains of both zymodemes.ConclusionsThis is the first population genetic study of L. infantum in SE Europe and the Balkans. Our findings demonstrate the differentiation between SE and SW European strains; revealing the partition of Croatian strains between these populations and the genetic isolation of Cypriot strains. This mirrors the geographic position of Croatia located in central Europe and the natural isolation of the island of Cyprus. We have analysed the largest number of MON-98 strains so far. Our results indicate extensive gene flow, recombination and no differentiation between MON-1 and MON-98 zymodemes. No correlation either to host specificity or place and year of strain isolation was identified. Our findings may be associated with intensive host migration and common eco-epidemiological characteristics in these countries and give valuable insight into the dynamics of VL.

Project description:Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

Dataset Information

Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data.

Publications

Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data.

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