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Major inconsistencies of inferred population genetic structure estimated in a large set of domestic horse breeds using microsatellites

机译:使用微卫星的大型国内马品种估计推断人口遗传结构的主要不一致

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STRUCTURE remains the most applied software aimed at recovering the true, but unknown, population structure from microsatellite or other genetic markers. About 30% of STRUCTURE‐based studies could not be reproduced (Molecular Ecology, 21, 2012, 4925). Here we use a large set of data from 2,323 horses from 93 domestic breeds plus the Przewalski horse, typed at 15 microsatellites, to evaluate how program settings impact the estimation of the optimal number of population clusters Kopt that best describe the observed data. Domestic horses are suited as a test case as there is extensive background knowledge on the history of many breeds and extensive phylogenetic analyses. Different methods based on different genetic assumptions and statistical procedures (DAPC, FLOCK, PCoA, and STRUCTURE with different run scenarios) all revealed general, broad‐scale breed relationships that largely reflect known breed histories but diverged how they characterized small‐scale patterns. STRUCTURE failed to consistently identify Kopt using the most widespread approach, the ΔK method, despite very large numbers of MCMC iterations (3,000,000) and replicates (100). The interpretation of breed structure over increasing numbers of K, without assuming a Kopt, was consistent with known breed histories. The over‐reliance on Kopt should be replaced by a qualitative description of clustering over increasing K, which is scientifically more honest and has the advantage of being much faster and less computer intensive as lower numbers of MCMC iterations and repetitions suffice for stable results. Very large data sets are highly challenging for cluster analyses, especially when populations with complex genetic histories are investigated.
机译:结构仍然是旨在从微卫星或其他遗传标记的恢复真实但未知的人口结构的最多应用软件。无法复制大约30%的结构研究(分子生态学,21,2012,4925)。在这里,我们使用来自93匹家国内品种的2,323匹马的大量数据加上Przewalski Horse,在15微卫星中键入,评估程序设置如何影响最佳描述观察到的数据的最佳群体群Kopt的估计。由于许多品种的历史和广泛的系统发育分析,国内马匹是一个测试案例。基于不同的遗传假设和统计程序的不同方法(DAPC,群,PCOA和具有不同运行方案的结构)全部揭示了一般性的广泛的品种关系,主要是反映已知的品种历史,但分歧它们是如何表征小规模模式的方式。尽管非常大量的MCMC迭代(3,000,000)并复制(100),但结构未能始终识别ΔK方法的ΔK方法。在不假设kopt的情况下,在越来越多的k上增加培养结构的解释与已知的品种历史一致。 Kopt的过度依赖应该由集群的定性描述替换,这些k的增加的K,这在科学上更诚实,并且具有更快,更少的计算机密集,作为较少数量的MCMC迭代和重复足以实现稳定的结果。非常大的数据集对聚类分析具有高度挑战性,特别是当研究具有复杂遗传历史的群体时。
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