Ochs Ian E, Desai Michael M
Department of Organismic and Evolutionary Biology, Department of Physics, and FAS Center for Systems Biology, Harvard University, Cambridge, 02138, MA, USA.
BMC Evol Biol. 2015 Mar 26;15:55. doi: 10.1186/s12862-015-0334-0.
On rugged fitness landscapes where sign epistasis is common, adaptation can often involve either individually beneficial "uphill" mutations or more complex mutational trajectories involving fitness valleys or plateaus. The dynamics of the evolutionary process determine the probability that evolution will take any specific path among a variety of competing possible trajectories. Understanding this evolutionary choice is essential if we are to understand the outcomes and predictability of adaptation on rugged landscapes.
We present a simple model to analyze the probability that evolution will eschew immediately uphill paths in favor of crossing fitness valleys or plateaus that lead to higher fitness but less accessible genotypes. We calculate how this probability depends on the population size, mutation rates, and relevant selection pressures, and compare our analytical results to Wright-Fisher simulations.
We find that the probability of valley crossing depends nonmonotonically on population size: intermediate size populations are most likely to follow a "greedy" strategy of acquiring immediately beneficial mutations even if they lead to evolutionary dead ends, while larger and smaller populations are more likely to cross fitness valleys to reach distant advantageous genotypes. We explicitly identify the boundaries between these different regimes in terms of the relevant evolutionary parameters. Above a certain threshold population size, we show that the probability that the population finds the more distant peak depends only on a single simple combination of the relevant parameters.
在存在普遍符号上位性的崎岖适应度景观中,适应通常涉及个体有益的“上坡”突变,或者更复杂的涉及适应度低谷或高原的突变轨迹。进化过程的动态决定了进化在各种相互竞争的可能轨迹中选择任何特定路径的概率。如果我们要理解适应在崎岖景观中的结果和可预测性,理解这种进化选择至关重要。
我们提出一个简单模型来分析进化避开直接的上坡路径而选择跨越适应度低谷或高原(这些路径通向更高适应度但可达性较低的基因型)的概率。我们计算这种概率如何取决于种群大小、突变率和相关选择压力,并将我们的分析结果与赖特 - 费希尔模拟进行比较。
我们发现跨越低谷的概率非单调地取决于种群大小:中等规模种群最有可能遵循获取直接有益突变的“贪婪”策略,即使这些突变会导致进化死胡同,而较大和较小的种群更有可能跨越适应度低谷以达到遥远的有利基因型。我们根据相关进化参数明确确定了这些不同状态之间的边界。在某个阈值种群大小以上,我们表明种群找到更遥远峰值的概率仅取决于相关参数的一个简单组合。