NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States.
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.
Elife. 2021 Mar 29;10:e64740. doi: 10.7554/eLife.64740.
Epistasis between mutations can make adaptation contingent on evolutionary history. Yet despite widespread 'microscopic' epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increase between replicate lines. Recent work shows that this consistency is driven in part by global patterns of diminishing-returns and increasing-costs epistasis, which make mutations systematically less beneficial (or more deleterious) on fitter genetic backgrounds. However, the origin of this 'global' epistasis remains unknown. Here, we show that diminishing-returns and increasing-costs epistasis emerge generically as a consequence of pervasive microscopic epistasis. Our model predicts a specific quantitative relationship between the magnitude of global epistasis and the stochastic effects of microscopic epistasis, which we confirm by reanalyzing existing data. We further show that the distribution of fitness effects takes on a universal form when epistasis is widespread and introduce a novel fitness landscape model to show how phenotypic evolution can be repeatable despite sequence-level stochasticity.
突变之间的上位性会使适应取决于进化历史。然而，尽管涉及的突变之间存在广泛的“微观”上位性，但微生物进化实验显示出在重复系之间适应性增加的一致模式。最近的工作表明，这种一致性部分是由逐渐减少的回报和成本增加的上位性驱动的，这使得突变在适应性更强的遗传背景下系统地降低了适应性（或增加了有害性）。然而，这种“全局”上位性的起源仍然未知。在这里，我们表明，随着微观上位性的普遍存在，回报减少和成本增加的上位性会普遍出现。我们的模型预测了全局上位性的幅度和微观上位性的随机效应之间的特定定量关系，我们通过重新分析现有数据来验证了这一点。我们进一步表明，当上位性广泛存在时，适应度效应的分布呈现出一种普遍的形式，并引入了一种新的适应度景观模型，以展示尽管存在序列水平的随机性，表型进化如何可以具有重复性。
