Allelic Diversity and Its Implications for the Rate of Adaptation
Allelic Diversity and Its Implications for the Rate of Adaptation
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DOI：
10.1534/genetics.113.158410
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发表时间：
2013-12-01
期刊：
影响因子：
3.3
通讯作者：
Garcia-Dorado, Aurora
中科院分区：
文献类型：
--
作者：
Caballero, Armando;Garcia-Dorado, Aurora
遗传变异通常是根据基于群体基因频率的统计数据进行经验估计的，但基于等位基因多样性(等位基因类型的数量)的替代统计数据可以提供补充信息。然而，缺乏关于等位基因多样性测量的进化影响的知识，特别是在结构化种群中。在这篇文章中，我们模拟了单一和结构化群体的多个场景，其中受稳定选择约束的数量性状适应不同的适应度最优。通过强制对最优进行全局改变，我们评估了哪些多样性变量与对新最优的短期和长期适应更密切相关。我们发现，性状的数量遗传方差分量和基因频率多样性度量通常与选择的短期反应更密切相关，而等位基因多样性度量与长期和总体选择反应更相关。因此，等位基因多样性变量比基因频率变量更能预测长期适应。这一观察结果也扩展到无关联的中性标记，因为它们传达了关于人口历史的信息。在无限等位基因中性突变模型下，给出了有限岛模型中等位基因多样性度量的扩散近似。
Genetic variation is usually estimated empirically from statistics based on population gene frequencies, but alternative statistics based on allelic diversity (number of allelic types) can provide complementary information. There is a lack of knowledge, however, on the evolutionary implications attached to allelic-diversity measures, particularly in structured populations. In this article we simulated multiple scenarios of single and structured populations in which a quantitative trait subject to stabilizing selection is adapted to different fitness optima. By forcing a global change in the optima we evaluated which diversity variables are more strongly correlated with both short- and long-term adaptation to the new optima. We found that quantitative genetic variance components for the trait and gene-frequency-diversity measures are generally more strongly correlated with short-term response to selection, whereas allelic-diversity measures are more correlated with long-term and total response to selection. Thus, allelic-diversity variables are better predictors of long-term adaptation than gene-frequency variables. This observation is also extended to unlinked neutral markers as a result of the information they convey on the demographic population history. Diffusion approximations for the allelic-diversity measures in a finite island model under the infinite-allele neutral mutation model are also provided.