Smouse PE, Peakall R. Spatial autocorrelation analysis of multi-allele and multi-locus genetic microstructure. Heredity 82: 561-573

Department of Ecology, Evolution and Natural Resources and Center for Theoretical & Applied Genetics, Cook College, Rutgers University, New Brunswick, NJ 08901-8551, USA.
Heredity (Impact Factor: 3.81). 06/1999; 82 ( Pt 5)(5):561-73. DOI: 10.1038/sj.hdy.6885180
Source: PubMed

ABSTRACT Population genetic theory predicts that plant populations will exhibit internal spatial autocorrelation when propagule flow is restricted, but as an empirical reality, spatial structure is rarely consistent across loci or sites, and is generally weak. A lack of sensitivity in the statistical procedures may explain the discrepancy. Most work to date, based on allozymes, has involved pattern analysis for individual alleles, but new PCR-based genetic markers are coming into vogue, with vastly increased numbers of alleles. The field is badly in need of an explicitly multivariate approach to autocorrelation analysis, and our purpose here is to introduce a new approach that is applicable to multiallelic codominant, multilocus arrays. The procedure treats the genetic data set as a whole, strengthening the spatial signal and reducing the stochastic (allele-to-allele, and locus-to-locus) noise. We (i) develop a very general multivariate method, based on genetic distance methods, (ii) illustrate it for multiallelic codominant loci, and (iii) provide nonparametric permutational testing procedures for the full correlogram. We illustrate the new method with an example data set from the orchid Caladenia tentaculata, for which we show (iv) how the multivariate treatment compares with the single-allele treatment, (v) that intermediate frequency alleles from highly polymorphic loci perform well and rare alleles poorly, (vi) that a multilocus treatment provides clearer answers than separate single-locus treatments, and (vii) that weighting alleles differentially improves our resolution minimally. The results, though specific to Caladenia, offer encouragement for wider application.

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    • "The two matrices were then analyzed using the Isolation by Distance Web Service v3.23 (Jensen et al. 2005). We also performed a spatial autocorrelation analysis (Smouse and Peakall 1999) as implemented by GenAlEx to compare the genetic similarity among individuals at different intervals of distance. For this analysis we selected one individual from each unique trapping site (n = 150 individuals) in order to not exceed the computational capacity of the software. "
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    • "Existence of isolation-by-distance between individuals was tested using the Mantel test with 999 permutations on matrices of linearized genetic distance between individuals (Smouse and Peakall 1999) and a corresponding log-geographic distance in GenAlEx 6.5 (Peakall and Smouse 2012). "
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    ABSTRACT: Dengue is the most prevalent global arboviral disease that affects over 300 million people every year. Brazil has the highest number of dengue cases in the world, with the most severe epidemics in the city of Rio de Janeiro (Rio). The effective control of dengue is critically dependent on the knowledge of population genetic structuring in the primary dengue vector, the mosquito Aedes aegypti. We analyzed mitochondrial and nuclear genome-wide SNP markers generated via Restriction-site Associated DNA sequencing, as well as traditional microsatellite markers in Ae. aegypti from Rio. We found four divergent mitochondrial lineages and a strong spatial structuring of mitochondrial variation, in contrast to the overall nuclear homogeneity across Rio. Despite a low overall differentiation in the nuclear genome, we detected strong spatial structure for variation in over 20 genes that have a significantly altered expression in response to insecticides, xenobiotics and pathogens, including the novel biocontrol agent Wolbachia. Our results indicate that high genetic diversity, spatially unconstrained admixing likely mediated by male dispersal, along with locally heterogeneous genetic variation that could affect insecticide resistance and mosquito vectorial capacity, set limits to the effectiveness of measures to control dengue fever in Rio.
    Evolutionary Applications 08/2015; DOI:10.1111/eva.12301 · 4.15 Impact Factor
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    • "Genotypic diversity and clonal variation were calculated in GenoDive version 2.0b4 (Meirmans and Van Tienderen, 2004) and GenClone version 2.0 (Arnaud-Haond and Belkhir, 2007). We first calculated genetic distances using the method of Smouse and Peakall – a squared Euclidean distance based on the number of times a certain allele is found in the two individuals (Smouse and Peakall,1999). The minimal distance class was set as threshold to identify the follow: (i) the number of multilocus genotypes (G) where parasite samples with identical genotypes at all the examined microsatellite loci were identified as a single clone and thus the number of unique multilocus genotypes was referred to the number of unique clones; (ii) Simpson's diversity index (D), also referred as clonal diversity corrected for sample size (a measure of the proportion of unique genotypes/clones in a population) that ranges from zero (where two randomly chosen individuals in a population represent a single clone) to one (where individuals all represent different clones); and (iii) genotype evenness (E) that ranges from zero (where one or a few clones dominate in a population ) to one (where all clones are of equal frequency in a population ). "
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    ABSTRACT: In Myanmar, civil unrest and establishment of internally displaced persons (IDP) settlement along the Myanmar-China border have impacted malaria transmission. The growing IDP populations raise deep concerns about health impact on local communities. Microsatellite markers were used to examine the source and spreading patterns of Plasmodium falciparum between IDP settlement and surrounding villages in Myanmar along the China border. Genotypic structure of P. falciparum was compared over the past three years from the same area and the demographic history was inferred to determine the source of recent infections. In addition, we examined if border migration is a factor of P. falciparum infections in China by determining gene flow patterns across borders. Compared to local community, the IDP samples showed a reduced and consistently lower genetic diversity over the past three years. A strong signature of genetic bottleneck was detected in the IDP samples. P. falciparum infections from the border regions in China were genetically similar to Myanmar and parasite gene flow was not constrained by geographical distance. Reduced genetic diversity of P. falciparum suggested intense malaria control within the IDP settlement. Human movement was a key factor to the spread of malaria both locally in Myanmar and across the international border. Copyright © 2015. Published by Elsevier B.V.
    Infection, genetics and evolution: journal of molecular epidemiology and evolutionary genetics in infectious diseases 05/2015; 33. DOI:10.1016/j.meegid.2015.05.002 · 3.02 Impact Factor
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