Data from: Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations

How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis) at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.适应中的种群如何在基因表达成本与基因产物收益之间的权衡矛盾中寻求平衡，以同时优化众多基因的表达水平？本研究结合了在扭脱甲基杆菌（Methylobacterium extorquens）中心代谢途径中改变酶水平的独立起源有益突变，以解析由基因表达水平所定义的适应度景观（fitness landscape）。我们发现这些有益突变之间存在强烈的拮抗互作与符号上位性（sign epistasis）。个体收益最大的突变与其他突变的拮抗互作程度最强，这一趋势我们也通过对其他模式生物数据集的分析得到了验证。然而，在酶表达层面，这些有益突变之间呈乘性互作（即无上位性效应）。通过构建从酶水平预测适应度的模型，我们可将观测到的符号上位性解释为突破了由酶催化收益与适应度成本之间平衡所定义的最优值。对表型景观（phenotypic landscape）的认知还揭示出：尽管适应度峰值在表型层面与祖先状态相去甚远，但在遗传层面却并不遥远。单个有益突变会直接朝着全局最优值演化，而非受限于遗传结构所预期的相关模式来改变表达表型。鉴于自然界中的适应通常源于基因表达的优化，这些结论可广泛应用于其他生物与选择条件中。因此，影响基因表达的单个有益等位基因之间的不良互作，可能会在适应过程中削弱有性生殖的收益，并推动遗传分化。