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Genealogical lineage sorting leads to significant, but incorrect Bayesian multilocus inference of population structure

机译:谱系谱系排序导致显着但不正确的人口结构贝叶斯多位点推断

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Over the past decades, the use of molecular markers has revolutionized biology and led to the foundation of a new research discipline-phylogeography. Of particular interest has been the inference of population structure and biogeography. While initial studies focused on mtDNA as a molecular marker, it has become apparent that selection and genealogical lineage sorting could lead to erroneous inferences. As it is not clear to what extent these forces affect a given marker, it has become common practice to use the combined evidence from a set of molecular markers as an attempt to recover the signals that approximate the true underlying demography. Typically, the number of markers used is determined by either budget constraints or by statistical power required to recognize significant population differentiation. Using microsatellite markers from Drosophila and humans, we show that even large numbers of loci (>50) can frequently result in statistically well-supported, but incorrect inference of population structure using the software baps. Most importantly, genomic features, such as chromosomal location, variability of the markers, or recombination rate, cannot explain this observation. Instead, it can be attributed to sampling variation among loci with different realizations of the stochastic lineage sorting. This phenomenon is particularly pronounced for low levels of population differentiation. Our results have important implications for ongoing studies of population differentiation, as we unambiguously demonstrate that statistical significance of population structure inferred from a random set of genetic markers cannot necessarily be taken as evidence for a reliable demographic inference.
机译:在过去的几十年中,分子标记的使用彻底改变了生物学,并导致了新的研究领域-系统地理学的建立。特别令人感兴趣的是人口结构和生物地理学的推论。虽然最初的研究集中在作为分子标记的mtDNA上,但很明显,选择和谱系谱系分类可能导致错误的推断。由于尚不清楚这些力在多大程度上影响给定的标记物,因此已习惯使用一组分子标记物的组合证据来尝试恢复近似真实人口统计学的信号。通常,使用的标记数由预算约束条件或由识别显着人群差异所需的统计能力决定。使用果蝇和人类的微卫星标记,我们显示即使大量的基因座(> 50)也经常会导致统计上得到很好的支持,但是使用软件小插曲就无法正确推断出种群结构。最重要的是,基因组特征(例如染色体位置,标记的变异性或重组率)无法解释这一现象。取而代之的是,它可以归因于随机谱系分类的不同实现的基因座之间的采样差异。对于低水平的人口分化,这种现象尤为明显。我们的结果对正在进行的人口分化研究具有重要意义,因为我们明确地表明,从一组随机的遗传标记推断出的人口结构的统计意义不一定能作为可靠的人口统计学推论的证据。

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