  We investigate the relationship between the average fitness decay due to
single mutations and the strength of epistatic interactions in genetic
sequences. We observe that epistatic interactions between mutations are
correlated to the average fitness decay, both in RNA secondary structure
prediction as well as in digital organisms replicating in silico. This
correlation implies that during adaptation, epistasis and average mutational
effect cannot be optimized independently. In experiments with RNA sequences
evolving on a neutral network, the selective pressure to decrease the
mutational load then leads to a reduction of the amount of sequences with
strong antagonistic interactions between deleterious mutations in the
population.
