Article

Estimation of the Population Scaled Mutation Rate From Microsatellite Data

Genetics (Impact Factor: 5.96). 12/2007; 177(3):1967-8. DOI: 10.1534/genetics.107.078931
Source: PubMed

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    • "MODEL II is the same as MODEL I, but here, we pooled NWA and NT (NWA + NT) as biogeographic studies across northern Australia often find close relationships among populations in these two areas (Bowman et al. 2010); MODEL III assumes that NT + NWA is the source and all other populations are sinks; MODEL IV assumes that CYP is the source; MODEL V assumes that FNQ is the source; and MODEL VI assumes that PNG is the source; MODEL VII finally assumes that all sampled magpie geese belong to a single panmictic population. MIGRATE was run for each model using the microsatellite data; we used the Brownian mutation model (Beerli 2007). The MIGRATE run parameters were calibrated on the most complex Model I, so that the settings used for the comparison show convergence of the Markov chain Monte Carlo sampling method. "
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    ABSTRACT: There are many large, easy-to-observe anseriform birds (ducks, geese, and swans) in northern Australia and New Guinea and they often gather in large numbers. Yet, the structure of their populations and their regional movements are poorly understood. Lack of understanding of population structure limits our capacity to understand source-sink dynamics relevant to their conservation or assess risks associated with avian-borne pathogens, in particular, avian influenza for which waterfowl are the main reservoir species. We set out to assess present-day genetic connectivity between populations of two widely distributed waterfowl in the Australo-Papuan tropics, magpie goose Anseranas semipalmata (Latham, 1798) and wandering whistling-duck Dendrocygna arcuata (Horsfield, 1824). Microsatellite data were obtained from 237 magpie geese and 64 wandering whistling-duck. Samples were collected across northern Australia, and at one site each in New Guinea and Timor Leste. In the wandering whistling-duck, genetic diversity was significantly apportioned by region and sampling location. For this species, the best model of population structure was New Guinea as the source population for all other populations. One remarkable result for this species was genetic separation of two flocks sampled contemporaneously on Cape York Peninsula only a few kilometers apart. In contrast, evidence for population structure was much weaker in the magpie goose, and Cape York as the source population provided the best fit to the observed structure. The fine scale genetic structure observed in wandering whistling-duck and magpie goose is consistent with earlier suggestions that the west-coast of Cape York Peninsula is a flyway for Australo-Papuan anseriforms between Australia and New Guinea across Torres Strait.
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    • "Both a nonlinear relationship between F ST and the number of migrants per generation and sampling error in esti - mates of allele frequencies can make estimates based on F ST imprecise ( Whitlock & McCauley , 1999 ) . Each method require assumptions , but Migrate - n allows realistic patterns of migration , explicitly models the mutation process , provides a robust approx - imation to the stepwise mutation model appropriate for the mi - crosatellite markers that we used ( Beerli , 2007 ) , and is more powerful and therefore less prone to sampling error in small population samples ( Beerli & Felsenstein , 1999 ) . Coalescent methods that explicitly account for migration also provide more accurate estimates of relative effective population sizes . "
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