利用自然树木种群的开放授粉子代测试进行定量遗传分析的偏差

J. Gauzere, S. Oddou‐Muratorio, C. Pichot, F. Lefèvre, E. Klein
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引用次数: 13

摘要

摘要在植物非原位定量遗传研究中,由于每个个体产生的大量种子促进了开放授粉后代试验的使用。在随后的分析中,在同一株母株上采集的种子被认为是同父异母的。自20世纪60年代以来,人们一直使用模拟方法和最近使用基于分子的实验方法来研究在后代测试中偏离同父异母假设的后果。本文旨在综合这些模拟和实证研究的结果和结论。我们的重点是树种,在这些树种中,控制杂交很难在实验中进行,而且在自然种群中经常发生与半同胞假设的背离。首先,在许多树木种群中,母系后代的亲缘关系平均水平高于同父异母的兄弟姐妹。这是由于每只雌性的有效花粉供体数量少、雄性繁殖成功率不平等和/或自交造成的非随机交配的结果。因此,对数量性状的遗传变异和遗传力的估计可能是向上偏倚的。另外,近交抑制、显性效应和雄性配子池在雌性中的异质性往往被忽视,这可能导致性状的遗传力被低估。基于后代之间的平均遗传亲缘关系和父母之间的亲缘关系的校正通常用于补偿这些偏差。然而,这种修正不能准确地调整估计的情况下,家庭之间的遗传亲缘关系的变化水平,优势效应或近亲繁殖抑制存在于后代。另一种有前途的方法是使用“动物模型”方法,该方法优化了分子数据和父系信息的使用,以更准确地估计遗传力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biases in quantitative genetic analyses using open-pollinated progeny tests from natural tree populations
Abstract In plant quantitative genetic studies conducted ex situ, the large number of seeds produced per individual has promoted the use of open-pollinated progeny tests. In subsequent analyses, seeds collected on the same mother-plant are assumed to be half-sibs. The consequences of the departure from half-sib assumption in progeny tests have been investigated since the 1960s using simulation approaches and, more recently, using molecular-based experimental approaches. This review aims to synthesize the results and conclusions of these simulation and empirical studies. We focus on tree species, where controlled crosses are difficult to carry out experimentally and departures from half-sib assumptions occur frequently in natural populations. First, the average level of relatedness expected within maternal progeny for many tree populations is higher than that of half-sibs. This is the consequence of non-random mating resulting from the small number of effective pollen donors per female, unequal male reproductive success and/or selfing. As result, estimates of genetic variance and heritability for quantitative traits may be upward biased. Alternatively, inbreeding depression, dominance effects and the heterogeneity of the male gamete pool among females are often neglected, which may lead to underestimation of the heritability of traits. A correction based on the mean genetic relatedness between offspring and the relatedness between parents is often used to compensate those biases. However, such correction cannot accurately adjust the estimates in situations where variable levels of genetic relatedness among families, dominance effects or inbreeding depression exist within the progeny. An alternative and promising approach is the use of the “animal model” approach, which optimizes the use of molecular data and paternal information to estimate heritability more accurately.
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