Pairwise and higher order genetic interactions during the evolution of a tRNA

A central question in genetics and evolution is the extent to which mutations have outcomes that change depending on the genetic context in which they occur. Pairwise interactions between mutations have been systematically mapped within and between genes, and contribute substantially to phenotypic variation amongst individuals. However, the extent to which genetic interactions themselves are stable or dynamic across genotypes is unclear. Here we quantify >45,000 genetic interactions between the same 87 pairs of mutations across >500 closely related genotypes of a yeast tRNA. Strikingly, 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 (FDR<0.1). Higher order interactions are also abundant and dynamic across genotypes. The epistasis in this molecule means that all individual mutations switch from detrimental to beneficial in even 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.遗传学与进化领域的核心议题之一，是突变的效应在多大程度上取决于其所处的遗传背景（genetic context）。突变间的成对互作已在基因内与基因间被系统解析，并极大地贡献于个体间的表型变异。然而，遗传互作本身在不同基因型间究竟是稳定还是动态变化，目前仍不明确。本研究针对酵母转运RNA（tRNA）的500余个近缘基因型，定量分析了同一组87对突变间的逾45000个遗传互作。值得注意的是，所有突变对在至少9%的遗传背景中均能检测到互作，且所有突变对在不同遗传背景中均会从正向互作转变为负向互作（错误发现率（False Discovery Rate，FDR）<0.1）。高阶遗传互作同样广泛存在且随基因型动态变化。该tRNA分子中的上位性（epistasis）表明，即便在近缘基因型中，所有单个突变的效应也会从有害转为有益。因此，要实现精准的遗传预测，需要在不同遗传背景中测定突变效应，并引入高阶上位性项。