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Short-Term Genetic Changes: Evaluating Effective Population Size Estimates in a Comprehensively Described Brown Trout (Salmo trutta) Population

机译:短期遗传变化:在综合描述的褐鳟(Salmo trutta)种群中评估有效种群规模估计

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摘要

The effective population size (Ne) is notoriously difficult to accurately estimate in wild populations as it is influenced by a number of parameters that are difficult to delineate in natural systems. The different methods that are used to estimate Ne are affected variously by different processes at the population level, such as the life-history characteristics of the organism, gene flow, and population substructure, as well as by the frequency patterns of genetic markers used and the sampling design. Here, we compare Ne estimates obtained by different genetic methods and from demographic data and elucidate how the estimates are affected by various factors in an exhaustively sampled and comprehensively described natural brown trout (Salmo trutta) system. In general, the methods yielded rather congruent estimates, and we ascribe that to the adequate genotyping and exhaustive sampling. Effects of violating the assumptions of the different methods were nevertheless apparent. In accordance with theoretical studies, skewed allele frequencies would underestimate temporal allele frequency changes and thereby upwardly bias Ne if not accounted for. Overlapping generations and iteroparity would also upwardly bias Ne when applied to temporal samples taken over short time spans. Gene flow from a genetically not very dissimilar source population decreases temporal allele frequency changes and thereby acts to increase estimates of Ne. Our study reiterates the importance of adequate sampling, quantification of life-history parameters and gene flow, and incorporating these data into the Ne estimation.
机译:众所周知,有效种群数量(Ne)很难在野生种群中准确估计,因为它受自然系统中难以描述的许多参数的影响。用于估计Ne的不同方法会受到种群水平上不同过程的不同影响,例如生物体的生命史特征,基因流和种群子结构,以及所使用的遗传标记的频率模式。抽样设计。在这里,我们比较了通过不同遗传方法和人口统计学数据获得的Ne估计值,并阐明了在详尽采样和全面描述的天然鳟鱼(Salmo trutta)系统中,估计值如何受到各种因素的影响。通常,这些方法得出的估计值相当一致,我们将其归因于适当的基因分型和详尽的抽样。但是,违反不同方法的假设的效果是显而易见的。根据理论研究,倾斜的等位基因频率会低估时间等位基因的频率变化,因此如果不加以考虑,则会向上偏向Ne。当将重叠的世代和等位性应用于短时间范围内的时间样本时,Ne也将向上偏移。来自遗传上不太相似的来源群体的基因流减少了时间等位基因频率变化,从而起到增加Ne估计值的作用。我们的研究重申了适当采样,量化生活史参数和基因流并将这些数据纳入Ne估计的重要性。

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