Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford OX1 3PU, UK.
Faculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, UK.
Mol Biol Evol. 2024 Jun 1;41(6). doi: 10.1093/molbev/msae085.
Modeling the rate at which adaptive phenotypes appear in a population is a key to predicting evolutionary processes. Given random mutations, should this rate be modeled by a simple Poisson process, or is a more complex dynamics needed? Here we use analytic calculations and simulations of evolving populations on explicit genotype-phenotype maps to show that the introduction of novel phenotypes can be "bursty" or overdispersed. In other words, a novel phenotype either appears multiple times in quick succession or not at all for many generations. These bursts are fundamentally caused by statistical fluctuations and other structure in the map from genotypes to phenotypes. Their strength depends on population parameters, being highest for "monomorphic" populations with low mutation rates. They can also be enhanced by additional inhomogeneities in the mapping from genotypes to phenotypes. We mainly investigate the effect of bursts using the well-studied genotype-phenotype map for RNA secondary structure, but find similar behavior in a lattice protein model and in Richard Dawkins's biomorphs model of morphological development. Bursts can profoundly affect adaptive dynamics. Most notably, they imply that fitness differences play a smaller role in determining which phenotype fixes than would be the case for a Poisson process without bursts.
模拟群体中适应表型出现的速度是预测进化过程的关键。考虑到随机突变,这个速度应该用简单的泊松过程来建模,还是需要更复杂的动力学?在这里,我们使用显式基因型-表型图上进化群体的分析计算和模拟来表明,新表型的引入可能是“突发”或过度离散的。换句话说,一种新的表型要么在短时间内多次出现,要么在许多代中根本不会出现。这些突发是由基因型到表型映射中的统计波动和其他结构从根本上引起的。它们的强度取决于种群参数,对于突变率低的“同质”种群最高。它们还可以通过基因型到表型映射中的附加非均匀性来增强。我们主要使用 RNA 二级结构的研究良好的基因型-表型图来研究突发的影响,但在晶格蛋白模型和理查德·道金斯(Richard Dawkins)的形态发育生物形态模型中发现了类似的行为。突发会深刻地影响适应性动态。最值得注意的是,它们意味着在确定哪种表型固定时,适应度差异在决定因素中的作用比没有突发的泊松过程小。