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The effect of gene flow from unsampled demes in landscape genetic analysis
Molecular Ecology Resources ( IF 7.7 ) Pub Date : 2020-10-04 , DOI: 10.1111/1755-0998.13267
Andrew J Shirk 1 , Erin L Landguth 2 , Samuel A Cushman 3
Affiliation  

An assumption of correlative landscape genetic methods is that genetic differentiation at neutral markers arises solely from the degree to which the intervening landscape between individuals or populations resists gene flow. However, this assumption is violated when gene flow occurs into the sampled population from an unsampled, differentiated deme. This may happen when sampling within only a portion of a population's extent or when closely related species hybridize with the sampled population. In both cases, violation of the modelling assumptions has the potential to reduce landscape genetic model selection accuracy and result in poor inferences. We used individual‐based population genetic simulations in complex landscapes within a model selection framework to explore the potential confounding effect of gene flow from unsampled demes. We hypothesized that as gene flow from outside the sampling extent increased, model selection accuracy would decrease due to the formation of a hybrid zone where allele frequencies were perturbed in a way that was not correlated with effective distances between sampled individuals. Surprisingly, we found this expectation was unfounded, because the reduced accuracy due to admixture was counteracted by an increase in allelic diversity as alleles spread from the unsampled deme into the sampled population. These new alleles increased the power to detect landscape genetic relationships and even slightly improving model selection accuracy overall. This is a reassuring result, suggesting that sampling the full extent of a population or related species that may hybridize may be unnecessary, as long as other well‐established sampling requirements are met.

中文翻译:

景观遗传分析中未采样区域基因流的影响

相关景观遗传方法的一个假设是,中性标记的遗传分化完全取决于个体或种群之间的干预景观抵抗基因流动的程度。然而,当基因从未抽样的、分化的基因流入抽样群体时,这一假设就被违反了。当仅在种群范围的一部分内采样或当密切相关的物种与采样种群杂交时,可能会发生这种情况。在这两种情况下,违反建模假设都有可能降低景观遗传模型选择的准确性并导致推断不佳。我们在模型选择框架内的复杂景观中使用基于个体的种群遗传模拟,以探索来自未采样区域的基因流的潜在混杂效应。我们假设,随着来自采样范围之外的基因流增加,模型选择的准确性会降低,因为形成了一个混合区,其中等位基因频率以与采样个体之间的有效距离无关的方式受到干扰。令人惊讶的是,我们发现这种预期是没有根据的,因为随着等位基因从未采样的区域传播到采样的群体中,等位基因多样性的增加抵消了由于混合而导致的准确性降低。这些新的等位基因增加了检测景观遗传关系的能力,甚至在整体上略微提高了模型选择的准确性。这是一个令人欣慰的结果,表明只要满足其他既定的抽样要求,就可能没有必要对可能杂交的种群或相关物种的全部范围进行抽样。
更新日期:2020-10-04
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