Kosman Evsey, Feijen Frida, Jokela Jukka
Institute for Cereal Crops Research, School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences Tel Aviv University Tel Aviv Israel.
ETH Zurich, Department of Environmental Systems Science Institute of Integrative Biology (IBZ) Zürich Switzerland.
Ecol Evol. 2024 Sep 15;14(9):e70303. doi: 10.1002/ece3.70303. eCollection 2024 Sep.
Widely used methods to assess population genetic structure and differentiation rely on independence of marker loci. Following the assumption, the common metrics, for example , evaluate genetic structure by averaging across loci. Common metrics do not use information in the associations among loci at the individual level and are often criticized for failing to measure true differentiation even when loci segregate independently. We introduce a new concept to measure β-variation (Effective Number of Different Populations, ENDP). It requires the following steps: (a) calculation of a proper dissimilarity between genetic profiles of all individuals; (b) calculation of suitable pairwise distances between the samples based on the dissimilarities between individuals; (c) calculation of diversity (in terms of Hill numbers) and dispersion of samples based on the pairwise distances between samples; (d) ENDP is then estimated by combining the diversity and dispersion. ENDP estimates β-variation independently of estimates of within-sample α-variation, although β- and α-estimates could statistically correlate to some extent. This new concept differs from the existing standard where β-diversity is estimated based on the "partition of variation" scheme ( or ), so that estimates of β-diversity directly depend on the corresponding values of α-diversity. ENDP estimates are obtained by evaluating information in the available genetic profiles of individuals including association of loci. Therefore, ENDP can be used even in an absence of panmixia. We illustrate the use of this concept by analyzing the population genetic structure of a sexual species (a trematode parasite) occupying connected populations across a broad geographic area. The analysis is complicated by geographically coexisting cryptic species and the potential mixed-mating system of this hermaphroditic parasite. Analyses with subsampled data demonstrated that ENDP estimates are robust. Number of loci used for genotyping has much stronger effect on variation of point ENDP estimates than sample size.
评估群体遗传结构和分化的广泛使用的方法依赖于标记位点的独立性。基于这一假设，常见的指标，例如 ，通过对各个位点进行平均来评估遗传结构。常见指标没有利用个体水平上位点间关联中的信息，并且常常因即使位点独立分离时也未能衡量真正的分化而受到批评。我们引入了一个新的概念来衡量β-变异（不同群体的有效数量，ENDP）。它需要以下步骤：(a) 计算所有个体遗传图谱之间适当的不相似性；(b) 根据个体间的不相似性计算样本之间合适的成对距离；(c) 根据样本之间的成对距离计算样本的多样性（以希尔数表示）和离散度；(d) 然后通过结合多样性和离散度来估计ENDP。ENDP独立于样本内α-变异的估计来估计β-变异，尽管β-和α-估计在一定程度上可能存在统计相关性。这个新概念不同于现有的标准，在现有标准中，β-多样性是基于“变异划分”方案（ 或 ）来估计的，因此β-多样性的估计直接依赖于α-多样性的相应值。ENDP估计是通过评估个体可用遗传图谱中的信息（包括位点关联）获得的。因此，即使在不存在随机交配的情况下也可以使用ENDP。我们通过分析一种有性物种（一种吸虫寄生虫）的群体遗传结构来说明这个概念的使用，该物种占据了广泛地理区域内相连的群体。由于地理上共存的隐存物种以及这种雌雄同体寄生虫潜在的混合交配系统，分析变得复杂。对抽样数据的分析表明，ENDP估计是稳健的。用于基因分型的位点数对单个ENDP估计值的变异影响比对样本量的影响要强得多。
