Department of Ecology, Ethology, and Evolution, University of Illinois, Champaign, Illinois 61820.
Genetics. 1988 Nov;120(3):791-807. doi: 10.1093/genetics/120.3.791.
While the genetic consequences of inbreeding and small population size are of fundamental importance in many areas of biology, empirical research on these phenomena has proceeded in the absence of a well-developed statistical methodology. The usual approach is to compare observed means and variances with the expectations of Wright's neutral, additive genetic model for quantitative characters. If the observations deviate from the expectations more than can be accounted for by sampling variance of the parameter estimates, the null hypothesis is routinely rejected in favor of alternatives invoking evolutionary forces such as selection or nonadditive gene action. This is a biased procedure because it treats sequential samples from the same populations as independent, and because it ignores the fact that the expectations of the neutral additive genetic model will rarely be realized when only a finite number of lines are studied. Even when genes are perfectly additive and neutral, the variation among the properties of founder populations, the random development of linkage disequilibrium within lines, and the variance in inbreeding between lines reduce the likelihood that Wright's expectations will be realized in any particular set of lines. Under most experimental designs, these sources of variation are much too large to be ignored. Formulas are presented for the variance-covariance structure of the realized within- and between-line variance under the neutral additive genetic model. These results are then used to develop statistical tests for detecting the operation of selection and/or inbreeding depression in small populations. A number of recommendations are made for the optimal design of experiments on drift and inbreeding, and a method is suggested for the correction of data for general environmental effects. In general, it appears that we can best understand the response of populations to inbreeding and finite population size by studying a very large number (>100) of self-fertilizing or full-sib mated lines in parallel with one or more stable control populations.
尽管近亲繁殖和小种群规模的遗传后果在生物学的许多领域都具有重要意义,但对这些现象的实证研究却缺乏完善的统计方法。通常的方法是将观察到的平均值和方差与 Wright 关于数量性状的中性、加性遗传模型的预期值进行比较。如果观察到的结果与预期值的偏差超过了参数估计的抽样方差所能解释的范围,则通常会拒绝零假设,转而支持涉及进化力量(如选择或非加性基因作用)的替代假设。这是一种有偏的程序,因为它将来自同一群体的连续样本视为独立的,并且忽略了这样一个事实,即在只研究有限数量的系时,中性加性遗传模型的预期值很少能够实现。即使基因是完全加性和中性的,创始人种群的属性之间的变异、系内连锁不平衡的随机发展以及系间近交的方差都会降低 Wright 预期在任何特定系集中实现的可能性。在大多数实验设计中,这些变异源大到不容忽视。本文提出了在中性加性遗传模型下实现的系内和系间方差的方差-协方差结构的公式。然后,利用这些结果开发了用于检测小种群中选择和/或近交衰退作用的统计检验方法。针对漂移和近交的实验设计提出了一些建议,并提出了一种用于纠正一般环境效应数据的方法。一般来说,通过同时研究大量 (>100) 自交或全同胞交配系,并与一个或多个稳定的对照种群平行,我们似乎可以最好地了解种群对近交和有限种群大小的反应。