  Genetic interactions pervade every aspect of biology, from evolutionary
theory where they determine the accessibility of evolutionary paths, to
medicine where they contribute to complex genetic diseases. Until very
recently, studies on epistatic interactions have been based on a handful of
mutations, providing at best anecdotal evidence about the frequency and the
typical strength of genetic interactions. In this study we analyze the publicly
available Data Repository of Yeast Genetic INteractions (DRYGIN), which
contains the growth rates of over five million double gene knockout mutants. We
discuss a geometric definition of epistasis which reveals a simple and
surprisingly weak scaling law for the characteristic strength of genetic
interactions as a function of the effects of the mutations being combined. We
then utilize this scaling to quantify the roughness of naturally occurring
fitness landscapes. Finally, we show how the observed roughness differs from
what is predicted by Fisher's geometric model of epistasis and discuss its
consequences on the evolutionary dynamics. Although epistatic interactions
between specific genes remain largely unpredictable, the statistical properties
of an ensemble of interactions can display conspicuous regularities and be
described by simple mathematical laws. By exploiting the amount of data
produced by modern high-throughput techniques it is now possible to thoroughly
test the predictions of theoretical models of genetic interactions and to build
informed computational models of evolution on realistic fitness landscapes.
