Detecting directional and non-directional epistasis in bi-parental populations using genomic data

Epistasis, commonly defined as interaction effects between alleles of different loci, is an important genetic component of the variation of phenotypic traits in natural and breeding populations. In addition to its impact on variance, epistasis can also affect the expected performance of a population and is then referred to as directional epistasis. Before the advent of genomic data, the existence of epistasis (both directional and non-directional) was investigated based on complex and expensive mating schemes involving several generations evaluated for a trait of interest. In this study, we propose a methodology to detect the presence of epistasis based on simple inbred bi-parental populations, both genotyped and phenotyped, ideally along with their parents. Thanks to genomic data, parental proportions as well as shared parental proportions between inbred individuals can be estimated. They allow the evaluation of the directionality of epistasis through a test of the expected performance and/or the variance of genetic values. This methodology was applied to two large multi-parental populations, i.e., the American maize and soybean nested association mapping populations, evaluated for different traits. Results showed significant epistasis, especially for the test of directional epistasis, e.g., the increase in anthesis to silking interval observed in most maize inbred progenies or the decrease in grain yield observed in several soybean inbred progenies. In general, the effects detected suggested that shuffling allelic assocations of both elite parents had a detrimental effect on the performance of their progeny. This methodology is implemented in the EpiTest R-package and can be applied to any inbred bi-/multi-parental population evaluated for a trait of interest. Author summary The genetic architecture of complex traits involves the actions of several loci whose allele effects can depend on the presence of specific alleles at other loci. This phenomenon is commonly referred to as epistasis and can affect both the variation and the average performance of a population. We propose a new methodology to detect the presence of epistasis in bi-parental inbred progeny, a very common type of population in plant genetics. It relies on the evaluation of the progeny for a trait of interest as well as on its characterization for genomic variants. Epistasis affecting the phenotypic variation of the trait and/or in the average performance of the bi-parental population can be detected. We applied this methodology to large multi-parental populations of maize and soybean and identified the presence of epistasis in several traits, affecting in particular in the average performance of the progeny. For instance, soybean populations often displayed lower grain yield than expected based on the performance of their elite parents. This methodology will help geneticists to better characterize the role of epistasis in the trait genetic architectures of their species of interest.