Indian Institute of Science Education and Research Pune, Pune, 411008 Maharashtra, India.
Institut des Sciences de l'Evolution - Montpellier (ISEM), Université de Montpellier, CNRS, IRD, 34095 Montpellier, France.
Proc Natl Acad Sci U S A. 2022 Aug 2;119(31):e2121858119. doi: 10.1073/pnas.2121858119. Epub 2022 Jul 27.
Contemporary evolution has the potential to significantly alter biotic responses to global change, including range expansion dynamics and biological invasions. Models predicting range dynamics often make highly simplifying assumptions about the genetic architecture underlying relevant traits. However, genetic architecture defines evolvability and higher-order evolutionary processes, which determine whether evolution will be able to keep up with environmental change or not. Therefore, we here study the impact of the genetic architecture of dispersal and local adaptation, two central traits of high relevance for range expansions, on the dynamics and predictability of invasion into an environmental gradient, such as temperature. In our theoretical model we assume that dispersal and local adaptation traits result from the products of two noninteracting gene-regulatory networks (GRNs). We compare our model to simpler quantitative genetics models and show that in the GRN model, range expansions are accelerating and less predictable. We further find that accelerating dynamics in the GRN model are primarily driven by an increase in the rate of local adaptation to novel habitats which results from greater sensitivity to mutation (decreased robustness) and increased gene expression. Our results highlight how processes at microscopic scales, here within genomes, can impact the predictions of large-scale, macroscopic phenomena, such as range expansions, by modulating the rate of evolution.
当代进化有可能显著改变生物对全球变化的反应,包括范围扩张动态和生物入侵。预测范围动态的模型通常对相关特征的遗传结构做出高度简化的假设。然而,遗传结构定义了可进化性和更高阶的进化过程,这决定了进化是否能够跟上环境变化。因此,我们在这里研究了扩散和局部适应这两个对范围扩张具有高度相关性的核心特征的遗传结构对入侵环境梯度(如温度)的动态和可预测性的影响。在我们的理论模型中,我们假设扩散和局部适应特征是由两个非相互作用的基因调控网络(GRN)的产物决定的。我们将我们的模型与更简单的数量遗传学模型进行了比较,并表明在 GRN 模型中,范围扩张正在加速且更难以预测。我们进一步发现,GRN 模型中加速的动态主要是由于对新栖息地的局部适应性的提高,这是由于对突变的敏感性增加(稳健性降低)和基因表达增加所致。我们的研究结果强调了微观尺度上的过程(此处指基因组内)如何通过调节进化速度来影响范围扩张等大规模宏观现象的预测。