Irwin K K, Laurent S, Matuszewski S, Vuilleumier S, Ormond L, Shim H, Bank C, Jensen J D
École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
Heredity (Edinb). 2016 Dec;117(6):393-399. doi: 10.1038/hdy.2016.58. Epub 2016 Sep 21.
Many features of virus populations make them excellent candidates for population genetic study, including a very high rate of mutation, high levels of nucleotide diversity, exceptionally large census population sizes, and frequent positive selection. However, these attributes also mean that special care must be taken in population genetic inference. For example, highly skewed offspring distributions, frequent and severe population bottleneck events associated with infection and compartmentalization, and strong purifying selection all affect the distribution of genetic variation but are often not taken into account. Here, we draw particular attention to multiple-merger coalescent events and background selection, discuss potential misinference associated with these processes, and highlight potential avenues for better incorporating them into future population genetic analyses.
病毒群体的许多特征使其成为群体遗传学研究的理想对象,包括极高的突变率、高水平的核苷酸多样性、异常庞大的普查群体规模以及频繁的正选择。然而,这些特性也意味着在群体遗传学推断中必须格外小心。例如,高度偏态的后代分布、与感染和区室化相关的频繁且严重的群体瓶颈事件,以及强烈的净化选择都会影响遗传变异的分布,但往往未被考虑在内。在此,我们特别关注多重合并的溯祖事件和背景选择,讨论与这些过程相关的潜在错误推断,并强调将它们更好地纳入未来群体遗传学分析的潜在途径。