Estimating the additive genetic variance for relative fitness from changes in allele frequency

The rate of adaptation is equal to the additive genetic variance for relative fitness (VA) in the population. Estimating VA typically involves obtaining suitable measures of fitness on a large number of individuals with known pairwise relatedness. Such data are hard to collect and the results are often sensitive to the definition of fitness used. Here, we present a new method for estimating VA that does not involve making measurements of fitness on individuals, but instead tracks changes in the genetic composition of the population. First, we show that VA can readily be expressed as a function of the genome-wide diversity/linkage disequilibrium matrix and genome-wide expected change in allele frequency due to selection. We then show how independent experimental replicates can be used to infer the expected change in allele frequency due to selection and then estimate VA via a linear mixed model. Finally, using individual-based simulations, we demonstrate that our approach yields precise and accurate estimates over a range of biologically plausible scenarios. Article summaryConventional approaches for estimating the heritable component of fitness variation (VA) have steep methodological, statistical, and even definitional challenges. Here, the authors present a new method that overcomes many of these issue by modelling VA using selection-induced changes to a populations genetic composition. The authors develop novel mathematical theory and an inference approach that uses independent experimental populations derived from the same ancestral population. Individual based simulations show that this method provides unbiased and precise estimates of VA. This opens the door for future studies investigating the genomic distribution of VA, a key factor driving Darwinian evolution.