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      Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power.

      1 , , ,
      Molecular ecology

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          Abstract

          Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (DLR) appeared to be an effective way to predict whether F0 immigrants could be identified for a particular pair of populations using a given set of markers.

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          Most cited references14

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          Detecting immigration by using multilocus genotypes.

          Immigration is an important force shaping the social structure, evolution, and genetics of populations. A statistical method is presented that uses multilocus genotypes to identify individuals who are immigrants, or have recent immigrant ancestry. The method is appropriate for use with allozymes, microsatellites, or restriction fragment length polymorphisms (RFLPs) and assumes linkage equilibrium among loci. Potential applications include studies of dispersal among natural populations of animals and plants, human evolutionary studies, and typing zoo animals of unknown origin (for use in captive breeding programs). The method is illustrated by analyzing RFLP genotypes in samples of humans from Australian, Japanese, New Guinean, and Senegalese populations. The test has power to detect immigrant ancestors, for these data, up to two generations in the past even though the overall differentiation of allele frequencies among populations is low.
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            Gene flow between insular, coastal and interior populations of brown bears in Alaska.

            The brown bears of coastal Alaska have been recently regarded as comprising from one to three distinct genetic groups. We sampled brown bears from each of the regions for which hypotheses of genetic uniqueness have been made, including the bears of the Kodiak Archipelago and the bears of Admiralty, Baranof and Chichagof (ABC) Islands in southeast Alaska. These samples were analysed with a suite of nuclear microsatellite markers. The 'big brown bears' of coastal Alaska were found to be part of the continuous continental distribution of brown bears, and not genetically isolated from the physically smaller 'grizzly bears' of the interior. By contrast, Kodiak brown bears appear to have experienced little or no genetic exchange with continental populations in recent generations. The bears of the ABC Islands, which have previously been shown to undergo little or no female-mediated gene flow with mainland populations, were found not to be genetically isolated from mainland bears. The data from the four insular populations indicate that female and male dispersal can be reduced or eliminated by water barriers of 2-4 km and 7 km in width, respectively.
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              Comparative analysis of microsatellite and allozyme markers: a case study investigating microgeographic differentiation in brown trout (Salmo trutta).

              A comparative study between microsatellite and allozyme markers was conducted on natural populations of resident brown trout (Salmo trutta) sampled over a reduced geographical scale and on hatchery strains. The higher level of polymorphism observed at microsatellite loci resulted in higher power of statistical tests for differentiation among population samples and for genotypic linkage disequilibrium. Genetic distances of Cavalli-Sforza and Edwards were on average two times larger for microsatellites than for allozymes but multilocus FST estimates computed over the entire set of populations were not significantly different for both categories of markers. Assignment tests of individual fish to the set of sampled populations demonstrated a much higher efficiency of microsatellites compared to allozymes. Pairwise multilocus FST estimates were significantly correlated to waterway distances and there was a significant tendency for the incorrectly classified individuals to be assigned to one of the nearest populations, indicating that isolation-by-distance acted significantly on brown trout populations. This increase of differentiation with distance was higher for allozymes than for microsatellites. Traditional measures of genetic differentiation (Cavalli-Sforza and Edwards' chord distance and FST) were compared for microsatellites to recently proposed statistics taking into account allele size differences (Goldstein's distance and PST). Using Goldstein's distance for neighbour-joining analysis did not improve the tree structure resolution. Multilocus estimates of PST and FST were not significantly different when computed over the entire set of populations but no significant correlation was detected between matrices of pairwise multilocus PST estimates and waterway distances.
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                Author and article information

                Journal
                Mol. Ecol.
                Molecular ecology
                0962-1083
                0962-1083
                Jan 2004
                : 13
                : 1
                Affiliations
                [1 ] Department of Zoology and Entomology, University of Queensland, St. Lucia, QLD 4072, Australia.
                Article
                2008
                10.1046/j.1365-294X.2004.02008.x
                14653788
                8204705d-0df7-45d2-acbd-0ebcdfe3a574
                History

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