  Epistasis refers to the phenomenon in which phenotypic consequences caused by
mutation of one gene depend on one or more mutations at another gene. Epistasis
is critical for understanding many genetic and evolutionary processes,
including pathway organization, evolution of sexual reproduction, mutational
load, ploidy, genomic complexity, speciation, and the origin of life.
Nevertheless, current understandings for the genome-wide distribution of
epistasis are mostly inferred from interactions among one mutant type per gene,
whereas how epistatic interaction partners change dynamically for different
mutant alleles of the same gene is largely unknown. Here we address this issue
by combining predictions from flux balance analysis and data from a recently
published high-throughput experiment. Our results show that different alleles
can epistatically interact with very different gene sets. Furthermore, between
two random mutant alleles of the same gene, the chance for the allele with more
severe mutational consequence to develop a higher percentage of negative
epistasis than the other allele is 50-70% in eukaryotic organisms, but only
20-30% in bacteria and archaea. We developed a population genetics model that
predicts that the observed distribution for the sign of epistasis can speed up
the process of purging deleterious mutations in eukaryotic organisms. Our
results indicate that epistasis among genes can be dynamically rewired at the
genome level, and call on future efforts to revisit theories that can integrate
epistatic dynamics among genes in biological systems.
