Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations.
Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations.
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DOI：
10.1371/journal.pgen.1004149
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发表时间：
2014-02
期刊：
影响因子：
4.5
通讯作者：
Marx CJ
中科院分区：
文献类型：
--
作者：
Chou HH;Delaney NF;Draghi JA;Marx CJ
适应性种群如何在基因表达的成本和基因产物的利益之间的紧张关系中导航，以同时优化许多基因的水平？在这里，我们结合了独立产生的有益突变，这些突变改变了扭脱甲基杆菌中心代谢中的酶水平，以揭示由基因表达水平定义的适应性景观。我们发现这些有益突变之间存在强烈的拮抗作用和上位性。具有最大个体益处的突变与其他突变的相互作用最具对抗性，我们也通过分析其他模型系统的数据集发现了这一趋势。然而，这些有益的突变以倍增方式相互作用（即，无上位性）。通过生成一个模型，从酶的水平预测健身，我们可以解释观察到的符号上位性的结果，超过了最佳定义的酶催化效益和健身成本之间的平衡。知识的表型景观也照亮，虽然健身高峰是表型远离祖先的状态，它不是遗传遥远。单个有益突变直接跳向全局最佳值，而不是受限于以遗传结构预期的相关方式改变表达表型。考虑到自然界的适应通常是优化基因表达的结果，这些结论可以广泛适用于其他生物和选择性条件。影响基因表达的个别有益等位基因之间的相互作用差，因此可能会损害适应过程中性别的好处，并促进遗传分化。在进化的谱系中，一系列适应性步骤的速度和结果取决于不同的有益突变相互叠加的程度。我们发现，影响代谢途径基因表达的独立有益突变不能很好地协同工作，并且通常是联合有害的。最有益的突变与其他突变的相互作用最差，这是我们在其他生物系统中发现的常见趋势。通过生成一个模型，占酶的好处和表达成本，我们发现，这种拮抗作用是由一个表型，健身映射，有一个中间峰。这使我们能够预测双突变体的适应性效应，并发现单个获胜突变倾向于在一个步骤中直接移动到峰值。这些发现证明了考虑表型变化的重要性，表型变化会导致适应性突变之间的非线性相互作用，从而影响种群的进化。
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. The pace and outcome of a series of adaptive steps in an evolving lineage depends upon how well different beneficial mutations stack on top of each other. We found that independent beneficial mutations that affected gene expression for a metabolic pathway did not work well together, and were often jointly deleterious. The most beneficial mutations interacted the most poorly with others, which was a trend we found common in other biological systems. Through generating a model that accounted for enzymatic benefits and expression costs, we uncovered that this antagonism was caused by a phenotype to fitness mapping that had an intermediate peak. This allowed us to predict the fitness effect of double mutants and to uncover that the single winning mutations tended to move straight to the peak in a single step. These findings demonstrate the importance of considering the phenotypic changes that cause nonlinear interactions between mutations upon fitness, and thus influence how populations evolve.
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影响因子：
3.3
作者：
Draghi, Jeremy A.;Parsons, Todd L.;Plotkin, Joshua B.
通讯作者：
Plotkin, Joshua B.
影响因子：
64.8
作者：
Dekel, E;Alon, U
通讯作者：
Alon, U
影响因子：
56.9
作者：
Chistoserdova, L;Vorholt, JA;Lidstrom, ME
通讯作者：
Lidstrom, ME
DOI：
10.1098/rspb.2012.1449
发表时间：
2012-10-22
影响因子：
4.7
作者：
Chiu, Hsuan-Chao;Marx, Christopher J.;Segre, Daniel
通讯作者：
Segre, Daniel
影响因子：
3.2
作者：
DONG, HJ;NILSSON, L;KURLAND, CG
通讯作者：
KURLAND, CG