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Estimating effective population size using RADseq: Effects of SNP selection and sample size

机译:使用Radseq估算有效的人口大小:SNP选择和样本大小的影响

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Effective population size (Ne) is a key parameter of population genetics. However, Ne remains challenging to estimate for natural populations as several factors are likely to bias estimates. These factors include sampling design, sequencing method, and data filtering. One issue inherent to the restriction site‐associated DNA sequencing (RADseq) protocol is missing data and SNP selection criteria (e.g., minimum minor allele frequency, number of SNPs). To evaluate the potential impact of SNP selection criteria on Ne estimates (Linkage Disequilibrium method) we used RADseq data for a nonmodel species, the thornback ray. In this data set, the inbreeding coefficient FIS was positively correlated with the amount of missing data, implying data were missing nonrandomly. The precision of Neestimates decreased with the number of SNPs. Mean Ne estimates (averaged across 50 random data sets with2000 SNPs) ranged between 237 and 1784. Increasing the percentage of missing data from 25% to 50% increased Ne estimates between 82% and 120%, while increasing the minor allele frequency (MAF) threshold from 0.01 to 0.1 decreased estimates between 71% and 75%. Considering these effects is important when interpreting RADseq data‐derived estimates of effective population size in empirical studies.
机译:有效的人口大小(NE)是人口遗传学的关键参数。然而,由于若干因素可能偏见估计,NE仍然挑战自然群体。这些因素包括采样设计,排序方法和数据过滤。限制性位点相关的DNA测序(RADSEQ)协议固定的一个问题是缺少数据和SNP选择标准(例如,最小次要等位基因频率,SNP的数量)。为了评估SNP选择标准对NE估计的潜在影响(连杆不平衡方法)我们使用RADSEQ数据进行非典范物种,索道射线。在该数据集中,近亲繁殖系数FIS与缺失数据量呈正相关,暗示数据缺少非粗糙度。半段的精度随SNP的数量而降低。平均NE估计(平均在50个随机数据集中,50个SNP)之间的范围在237和1784之间。增加了25%至50%的缺失数据的百分比增加了82%和120%,同时增加了次要等位基因频率(MAF)阈值从0.01到0.1减少71%和75%之间的估计值。考虑这些效果在解释实证研究中解释RADSEQ数据衍生有效人口大小的数据衍生的估计。

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