Dokan Kotaro, Kawamura Sayu, Teshima Kosuke M
Graduate School of System Life Science, Kyushu University, Fukuoka 819-0395, Japan.
Department of Biology, Kyushu University, Fukuoka 819-0395, Japan.
G3 (Bethesda). 2021 Sep 6;11(9). doi: 10.1093/g3journal/jkab128.
Single nucleotide polymorphism (SNP) data are widely used in research on natural populations. Although they are useful, SNP genotyping data are known to contain bias, normally referred to as ascertainment bias, because they are conditioned by already confirmed variants. This bias is introduced during the genotyping process, including the selection of populations for novel SNP discovery and the number of individuals involved in the discovery panel and selection of SNP markers. It is widely recognized that ascertainment bias can cause inaccurate inferences in population genetics and several methods to address these bias issues have been proposed. However, especially in natural populations, it is not always possible to apply an ideal ascertainment scheme because natural populations tend to have complex structures and histories. In addition, it was not fully assessed if ascertainment bias has the same effect on different types of population structure. Here, we examine the effects of bias produced during the selection of population for SNP discovery and consequent SNP marker selection processes under three demographic models: the island, stepping-stone, and population split models. Results show that site frequency spectra and summary statistics contain biases that depend on the joint effect of population structure and ascertainment schemes. Additionally, population structure inferences are also affected by ascertainment bias. Based on these results, it is recommended to evaluate the validity of the ascertainment strategy prior to the actual typing process because the direction and extent of ascertainment bias vary depending on several factors.
单核苷酸多态性（SNP）数据在自然种群研究中被广泛使用。尽管它们很有用，但已知SNP基因分型数据存在偏差，通常称为确定偏差，因为它们受到已确认变异的制约。这种偏差是在基因分型过程中引入的，包括用于发现新SNP的种群选择、发现面板中涉及的个体数量以及SNP标记的选择。人们普遍认识到，确定偏差会导致群体遗传学中的推断不准确，并且已经提出了几种解决这些偏差问题的方法。然而，特别是在自然种群中，由于自然种群往往具有复杂的结构和历史，并不总是能够应用理想的确定方案。此外，确定偏差对不同类型的种群结构是否具有相同的影响尚未得到充分评估。在这里，我们在三种人口模型下研究了在选择用于SNP发现的种群以及随后的SNP标记选择过程中产生的偏差的影响：岛屿模型、 stepping-stone模型和种群分裂模型。结果表明，位点频率谱和汇总统计数据包含的偏差取决于种群结构和确定方案的联合效应。此外，种群结构推断也受到确定偏差的影响。基于这些结果，建议在实际分型过程之前评估确定策略的有效性，因为确定偏差的方向和程度会因几个因素而有所不同。
