Performance of marker-based relatedness estimators in natural populations of outbred vertebrates

Abstract

Knowledge of relatedness between pairs of individuals plays an important role in many research areas including evolutionary biology, quantitative genetics, and conservation. Pairwise relatedness estimation methods based on genetic data from highly variable molecular markers are now used extensively as a substitute for pedigrees. Although the sampling variance of the estimators has been intensively studied for the most common simple genetic relationships, such as unrelated, half- and full-sib, or parent-offspring, little attention has been paid to the average performance of the estimators, by which we mean the performance across all pairs of individuals in a sample. Here we apply two measures to quantify the average performance: first, misclassification rates between pairs of genetic relationships and, second, the proportion of variance explained in the pairwise relatedness estimates by the true population relatedness composition (i.e., the frequencies of different relationships in the population). Using simulated data derived from exceptionally good quality marker and pedigree data from five long-term projects of natural populations, we demonstrate that the average performance depends mainly on the population relatedness composition and may be improved by the marker data quality only within the limits of the population relatedness composition. Our five examples of vertebrate breeding systems suggest that due to the remarkably low variance in relatedness across the population, marker-based estimates may often have low power to address research questions of interest.

Figure 1.—

Sampling distributions of the most common pedigree-based relationships in five natural populations when pairwise relatedness is calculated using the Queller and Goodnight (1989) (QG) or the Lynch and Ritland (1999) (LR) estimators. Each density curve is based on 10,000 simulated pairs of a given genetic relationship. Observed population allele frequencies were used. The plotted relationships were the most common in the observed pedigrees.

Figure 2.—

Proportion of variance explained in the marker-based relatedness estimates by true relatedness as a function of the number of loci. Populations were simulated on the basis of the observed relatedness composition and allele frequencies of five natural population samples, of which the two extremes, the great reed warbler and Soay sheep, are shown. For each number of loci five different loci were drawn from the available set of markers, which consisted of 62 loci for the great reed warbler and 101 for the Soay sheep. Relatedness was estimated using the Lynch and Ritland (1999) estimator.

Figure 3.—

Proportion of variance explained in the marker-based relatedness estimates by true relatedness as a function of the level of polymorphism expressed as the mean number of alleles at five randomly selected loci. Populations were simulated on the basis of the observed relatedness composition and allele frequencies of five natural population samples. Loci were drawn from the available set of markers, which consisted of 62 loci for the great reed warbler and 101 for the Soay sheep. Relatedness was estimated using the Lynch and Ritland (1999) estimator.