The effects of genetics, mutation and selection on Evolutionary Rescue in complex environments

复杂环境中遗传、突变和选择对进化救援的影响

基本信息

批准号：
BB/R003882/1
负责人：
Max Reuter
金额：
$ 60.44万
依托单位：
University College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FR003882%2F1
关键词：
effects genetics mutation selection Evolutionary

项目摘要

The past 150 years of modern evolutionary biology have provided us with a good understanding of how natural populations adapt to the constant changes that they experience in their environment. One important case that remains poorly understood, however, is that of evolutionary rescue (ER), where populations rely on adaptation to escape decline and extinction due to large, abrupt environmental shifts. Understanding the factors that allow or limit ER is fundamental and urgent in both basic and applied contexts. Human interventions such as antibiotic or pesticide treatments aim to impose unsurmountable adaptive challenges on the targeted species, and understanding the limits of ER is essential for maximising the efficacy of these interventions. Conversely, understanding the factors that favour ER is crucial when managing species threatened by rapid climate change.Given its importance, it is crucial to gain a better understanding of what determines a population's capacity for ER. Previous work has demonstrated that the capacity for ER is limited by the supply in advantageous genetic variants and increases with the amount of standing variation, the input of new variants (via mutation and immigration) and pre-adaptation from previous exposure to similar selection pressures. One significant limitation, however, is that previous work on ER has largely focussed on simple environments and changes in the mean of a single environmental variable. This is not realistic, because organisms live and evolve in complex environments, and using univariate environments fails to capture the complexity of multivariate evolution, where adaptive responses can be significantly affected (positively or negatively) by genetic correlations between responses to different variables.The aim of this project is to gain a detailed understanding of ER in multivariate environments. In order to do so, we investigate how the capacity of a population to show ER relates to the different forces that shape the genetic (co)variation for responses to different environmental variables, namely the size and topology of the genetic pathways underlying environmental responses, random genetic mutation, and past selective pressures that shape the amount and orientation of mutational variation.Our project uses the highly malleable fission yeast system and exploits a combination of powerful phenotypic and genetic high-throughput approaches. Using highly replicated growth assays across gradients of three environmental variables, the concentrations of potassium and magnesium chloride and temperature, we will determine the genes and pathways underlying responses to these variables and the degree to which they overlap. Using mutation accumulation, we will then study how random mutations interact with the size, structure and overlap of these pathways to generate covariation in environmental responses. Further, using experimental evolution under different regimes of multivariate environmental fluctuations, we will generate populations with different selective histories. Finally, we will assess ER in these evolved populations, alongside others assembled from selected wild strains, when subjected to changes in the means, variances and covariances of environmental variables.The data collected during the course of our project will allow us to generate a much better understanding of ER in complex environments, thus filling a major gap in our understanding of adaptive evolution. At the same time, we will have created a uniquely complete case study of multivariate evolution that ranges from the genetics underlying the genotype-phenotype map over mutation and selection to evolutionary change in multivariate trait space.Importantly, these insights into the factors determining ER will also be immediately exploitable in several areas of applied science, including the management of endangered species and the design of drug and pesticide treatments (see Impact).

过去 150 年的现代进化生物学让我们更好地了解自然种群如何适应环境中不断发生的变化。然而，人们对进化救援 (ER) 的了解仍然知之甚少，即种群依靠适应来避免因环境突变而导致的衰退和灭绝。在基础和应用环境中，了解允许或限制 ER 的因素至关重要且紧迫。抗生素或杀虫剂治疗等人类干预措施旨在给目标物种带来难以克服的适应性挑战，而了解 ER 的局限性对于最大限度地提高这些干预措施的功效至关重要。相反，在管理受快速气候变化威胁的物种时，了解有利于 ER 的因素至关重要。鉴于其重要性，更好地了解决定种群 ER 能力的因素至关重要。先前的研究表明，ER 的能力受到有利遗传变异的供应的限制，并随着长期变异的数量、新变异的输入（通过突变和移民）以及先前暴露于类似选择压力的预适应而增加。然而，一个重要的限制是，先前关于 ER 的工作主要集中在简单的环境和单个环境变量平均值的变化上。这是不现实的，因为生物体在复杂的环境中生存和进化，并且使用单变量环境无法捕捉多变量进化的复杂性，其中适应性反应可能会受到对不同变量的反应之间的遗传相关性的显着影响（正面或负面）。该项目的目的是详细了解多元环境中的 ER。为了做到这一点，我们研究了一个群体表现出 ER 的能力如何与影响不同环境变量反应的遗传（共）变异的不同力量相关，即环境反应背后的遗传途径的大小和拓扑结构，随机基因突变，以及过去影响突变变异数量和方向的选择压力。我们的项目使用高度可塑性的裂殖酵母系统，并利用强大的表型和遗传高通量方法的组合。通过对三个环境变量、氯化钾和氯化镁的浓度以及温度的梯度进行高度重复的生长测定，我们将确定对这些变量做出反应的基因和途径以及它们重叠的程度。然后，我们将利用突变积累来研究随机突变如何与这些途径的大小、结构和重叠相互作用，从而产生环境反应的共变。此外，利用多元环境波动的不同机制下的实验进化，我们将产生具有不同选择历史的种群。最后，当环境变量的平均值、方差和协方差发生变化时，我们将评估这些进化种群以及由选定野生菌株组装的其他种群的 ER。在我们的项目过程中收集的数据将使我们能够生成更多更好地理解复杂环境中的 ER，从而填补了我们对适应性进化理解的一个重大空白。同时，我们将创建一个独特的完整的多元进化案例研究，范围从突变和选择的基因型-表型图谱背后的遗传学到多元性状空间中的进化变化。重要的是，这些对决定 ER 因素的见解将也可以立即在应用科学的几个领域中利用，包括濒危物种的管理以及药物和杀虫剂治疗的设计（参见影响）。