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

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).

Understanding evolutionary rescue is fundamental for basic science and applications in medicine, agriculture and conservation. The aim of this project is to build on previous studies of ER in response to single environmental parameters and investigate ER in the realistic setting of multivariate environmental shifts. This case is more complex, because the evolutionary response of populations is constrained by genetic correlations between the responses to individual environmental variables. Our aim is to study how the genetics of environmental responses (studies in Obj. 1) interacts with random mutational input to shape covariation between environmental responses (Obj. 2), how this (co)variation is further altered by selection due to the fluctuating environmental conditions that populations have experienced in the past (Ob.j 4), and how the resulting genetic (co)variation determines the capacity of populations for ER in response to shifts in the means and/or (co)variations of environmental variables.

Our project uses the highly malleable fission yeast system and applies a combination of powerful, reliable approaches to analyse growth in response to variation in the concentrations of KCl and MgCl2 and temperature. Phenotypic assays for Objs. 1, 2, 4 will employ high through-put techniques to measure growth under tightly controlled environments. Colonies will be robot-plated in high replication and growth rate parameters inferred in an automated fashion from time series of plate photographs. For Objs. 1 and 2, growth measurements across strains will be analysed using quantitative genetics approaches, as well as statistical genetic analyses (GWAS). Obj. 2 involves highly replicated mutation accumulation, which will be performed by single colony transfers. Objs. 3 and 4 use experimental evolution via robot-transfers. Finally, Obj. 4 will employ pooled sequencing to assay sequence polymorphism of evolved populations and infer frequency change during ER.

Understanding the factors that determine the capacity for evolutionary rescue has direct implications in several fields of applied biology, including the conservation and management of natural populations and ecosystems, the treatment of pathogens in a medical setting and the control of pests in agriculture. Accordingly, there is potentially a wide range of beneficiaries of this research. We propose to work with potential users across fields, specifically researchers and policy makers in conservation, public health and agriculture, as well as the general public. We propose three activities that are tailored to best meet the particular needs of these end user groups.

A Scientific Workshop aims at maximising the impact of our research on evolutionary rescue by ensuring that its findings are generalisable, adaptable and applicable across potential user uses. The broad event will bring together relevant scientists from evolutionary biology, conservation, biomedical sciences, epidemiology and agricultural research to foster communication and knowledge exchange across sectors, explore generalities and idiosyncrasies of different systems and to identify key questions for future theoretical and empirical research.

The research-focussed Scientific Workshop will be complemented by a Prediction and Policy Workshop that will bring together selected basic scientist and representatives from government agencies and end user groups. The aim here is to define the sets of variables necessary to successfully predict the behaviour of a system (be it the population of an endangered species, that of an agricultural pest or a pathogen infection) and to recommend clear strategies of action.

Finally, we will reach out to the general public in order to engage and inform interested laymen. We will present our work at open science exhibitions, publish in dedicated UCL publications and engage with interested school children via the in2science programme.