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首页> 外文期刊>Fisheries Research >Detecting fine-scale population structure in the age of genomics: a case study of lake sturgeon in the Great Lakes
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Detecting fine-scale population structure in the age of genomics: a case study of lake sturgeon in the Great Lakes

机译:检测基因组学时的细尺群体结构 - 以湖泊湖泊湖泊为例

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Great Lakes-wide population structure analyses using neutral markers have provided an understanding of broadscale genetic structure of lake sturgeon. To assess the fine-scale genetic structure of lake sturgeon populations in two different rivers, we combined both microsatellites and genome-wide SNP markers. The St. Clair-Detroit River System (SCDRS) is entirely freshwater with no known impediments to sturgeon movement. In contrast, the St. Lawrence River (SLR) outlets into the Atlantic Ocean and is fragmented by hydroelectric dams. Both microsatellites and SNPs provided evidence of differentiation between the rivers. When applied to fine-scale structure, microsatellites failed to detect population structure using a Bayesian approach for within either river and F-ST values using microsatellites identified only a low level of differentiation between the upper and lower St. Clair River. Using the full set of SNPs for each comparison yielded similar results to the microsatellite results. Discriminant analysis of principal components using both markers partitioned the samples into spatially structured clusters. The SNP datasets filtered for high F-ST values had greater success for detecting fine-scale population structure and had the highest accuracy for reassignment to prior populations. This reduced SNP dataset may represent a more meaningful set of loci that can be used to estimate lake sturgeon fine-scale population structure, which is complicated by their long-generation times.
机译:使用中性标记的大湖泊人口结构分析已经了解湖泊鲟的广阔遗传结构。为了评估两种不同河流湖鲟种群的细尺遗传结构,我们组合微卫星和基因组的SNP标记。圣克莱特 - 底特律河流系统(SCDRS)完全是淡水,没有已知的鲟鱼运动的障碍。相比之下,圣劳伦斯河(SLR)插入大西洋,并由水力发电坝分散。微卫星和SNP都提供了河流之间的差异的证据。当应用于微尺度结构时,微卫星未能使用微卫星在河流和F-ST值内使用贝叶斯方法来检测人口结构,这些方法仅使用微卫星鉴定了上部和下部圣克莱尔河之间的低水平差异。每个比较的全套SNP都会产生类似的结果与微卫星结果。使用两个标记的主要组分的判别分析将样品分配到空间结构簇中。为高F-ST值过滤的SNP数据集对检测微尺度人口结构具有更大的成功,并具有最高的准确性以重新分配给事先人群。这种减少的SNP数据集可以代表一种更有意义的基因座,可用于估计湖泊鲟鱼细尺寸人口结构,这与他们的长代时间变得复杂。

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