Genetic Drift and Simulations

Abstract

Genetic drift is a random process that can lead to the fixation of alleles, but at the cost of losing alleles, especially those with low frequencies, and to increased homozygosity in the population. This process is described for an idealised population and its effect illustrated on different population sizes. The founder effect, a similar random process, is also described. The conditions of the idealised population are rarely met in real populations. Therefore, in order to estimate genetic drift it is necessary to make adjustments, for example by estimating effective population size (N e ). Methods to estimate N e in populations with unequal sex–ratio in breeders, e.g. herd species, and with unequal family sizes, are provided. Problems in estimating genetic drift due to generation overlap are also discussed. Effective population size can also be estimated from pedigrees. This method is illustrated with the Nepalese red panda as example. Computer programs that simulate Mendelian segregation in pedigrees (gene dropping) estimate the expected genetic drift and are not hindered by unequal sex–ratio, unequal family size or generation overlap. The general methodology of gene dropping is described. Software implementations can differ in complexity, e.g. from single locus (two alleles) to multiple loci (multiple alleles) on chromosomes and crossing over. The effects of simple and complex models on genetic loss in the wolverine population were evaluated in the context of model selection. Effective population sizes are estimated in Nepalese red pandas from expected genetic drift between census intervals.