Detectability of epistasis from temporal genetic data

Epistasis refers to a phenomenon wherein the occurrence of two or more mutations in the same genetic sequence has a different effect than expected from the effects of the individual mutations alone. Epistasis is common in nature and plays an important role in shaping evolution and the speed of adaptation.

In principle, the ability to detect epistasis in data is affected by genetic linkage, the chance cooccurrence of mutations on the same genetic background, and genetic recombination, the exchanges of genetic material between individuals, which acts to dilute linkage. At present, few studies have explored how epistasis can be detected, under what conditions, and which types of epistasis are detectable. Here, we inferred epistasis from simulated temporal genetic data with different types of epistasis and recombination rates. We tested multiple inference methods, including one that efficiently distinguishes linkage and epistasis. We found that different inference approaches work better in different evolutionary regimes, and we derived underlying scaling factors that constrain their accuracy.