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A central question in genetics and evolution is the extent to which the outcomes of mutations change depending on the genetic context in which they occur1-3. Pairwise interactions between mutations have been systematically mapped within4-18 and between19 genes, and have been shown to contribute substantially to phenotypic variation among individuals20. However, the extent to which genetic interactions themselves are stable or dynamic across genotypes is unclear21,22. Here we quantify more than 45,000 genetic interactions between the same 87 pairs of mutations across more than 500 closely related genotypes of a yeast tRNA. Notably, all pairs of mutations interacted in at least 9% of genetic backgrounds and all pairs switched from interacting positively to interacting negatively in different genotypes (false discovery rate < 0.1). Higher-order interactions are also abundant and dynamic across genotypes. The epistasis in this tRNA means that all individual mutations switch from detrimental to beneficial, even in closely related genotypes. As a consequence, accurate genetic prediction requires mutation effects to be measured across different genetic backgrounds and the use of higher-order epistatic terms.
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Genetic (epistatic) interactions have been extensively mapped between pairs of mutations within individual genes4-18, and also between individual alleles of many different genes19. However, the pairwise mapping of interactions only provides a limited view of genotype space, which has a vast combinatorial size22. Interactions between genes have been reported as only poorly or moderately conserved between species21. Moreover, analyses of the effects of combinations of mutations within individual genes have pointed to the importance of higher-order epistasis22-25, in which mutations interact beyond pairwise interactions to determine mutation effect.
To directly test the extent to which the effects of mutations and the interactions between mutations are stable or change depending upon the genotype in which they occur, we designed an experiment in which mutation effects and interactions are quantified across a large number of closely related genetic backgrounds. As a model system, we used the single-copy arginine-CCU tRNA (tRNA-Arg(CCU)) gene that is conditionally required for the growth of budding yeast (Extended Data Fig. 1a) and for which pairwise interactions have been previously mapped in one genetic background15. The small size of the gene allowed us to design a library that covered all 5,184 (26 x...