Estimating indirect genetic effects: precision of estimates and optimum designs.

Social interactions among individuals are abundant both in natural and domestic populations. Such social interactions cause phenotypes of individuals to depend on genes carried by other individuals, a phenomenon known as indirect genetic effects (IGE). Because IGEs have drastic effects on the rate and direction of response to selection, knowledge of their magnitude and relationship to direct genetic effects (DGE) is indispensable for understanding response to selection. Very little is known, however, of statistical power and optimum experimental designs for estimating IGEs. This work, therefore, presents expressions for the standard errors of the estimated (co)variances of DGEs and IGEs and identifies optimum experimental designs for their estimation. It also provides an expression for optimum family size and a numerical investigation of optimum group size. Designs with groups composed of two families were optimal and substantially better than designs with groups composed at random with respect to family. Results suggest that IGEs can be detected with ∼1000-2000 individuals and/or ∼250-500 groups when using optimum designs. Those values appear feasible for agriculture and aquaculture and for the smaller laboratory species. In summary, this work provides the tools to optimize and quantify the required size of experiments aiming to identify IGEs. An R-package SE.IGE is available, which predicts SEs and identifies optimum family and group sizes.