Estimating Realized Heritability in Panmictic Populations

Abstract

Abstract Narrow sense heritability (h2) is a key concept in quantitative genetics, as it expresses the proportion of the observed phenotypic variation that is transmissible from parents to offspring. h2 determines the resemblance among relatives, and the rate of response to artificial and natural selection. Classical methods for estimating h2 use random samples of individuals with known relatedness, as well as response to artificial selection, when it is called realized heritability. Here, we present a method for estimating realized h2 based on a simple assessment of a random-mating population with no artificial manipulation of the population structure, and derive SE of the estimates. This method can be applied to arbitrary phenotypic segments of the population (for example, the top-ranking p parents and offspring), rather than random samples. It can thus be applied to nonpedigreed random mating populations, where relatedness is determined from molecular markers in the p selected parents and offspring, thus substantially saving on genotyping costs. Further, we assessed the method by stochastic simulations, and, as expected from the mathematical derivation, it provides unbiased estimates of h2. We compared our approach to the regression and maximum-likelihood approaches utilizing Galton’s dataset on human heights, and all three methods provided identical results.