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A heuristic two-dimensional presentation of microsatellite-based data applied to dogs and wolves

机译:应用于狗和狼的基于微卫星的数据的启发式二维表示

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摘要

Methods based on genetic distance matrices usually lose information during the process of tree-building by converting a multi-dimensional matrix into a phylogenetic tree. We applied a heuristic method of two-dimensional presentation to achieve a better resolution of the relationship between breeds and individuals investigated. Four hundred and nine individuals from nine German dog breed populations and one free-living wolf population were analysed with a marker set of 23 microsatellites. The result of the two-dimensional presentation was partly comparable with and complemented a model-based analysis that uses genotype patterns. The assignment test and the neighbour-joining tree based on allele sharing estimate allocated 99% and 97% of the individuals according to their breed, respectively. The application of the two-dimensional presentation to distances on the basis of the proportion of shared alleles resulted in comparable and further complementary insight into inferred population structure by multilocus genotype data. We expect that the inference of population structure in domesticated species with complex breeding histories can be strongly supported by the two-dimensional presentation based on the described heuristic method.
机译:基于遗传距离矩阵的方法通常会在树木构建过程中通过将多维矩阵转换为系统发育树而丢失信息。我们应用了二维表示法的启发式方法,以更好地解决品种与被调查者之间的关系。使用23个微卫星标记集分析了来自9个德国犬种和1个自由狼群的490个个体。二维表示的结果与使用基因型模式的基于模型的分析部分可比并相辅相成。分配测试和基于等位基因共享估计的邻居树分别根据其品种分配了99%和97%的个体。根据共享等位基因的比例将二维表示应用于距离,可以通过多基因座基因型数据对推断的种群结构进行比较和补充。我们期望,基于描述的启发式方法的二维表示可以强有力地支持具有复杂繁殖历史的驯化物种的种群结构推断。

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