Periodic Reporting for period 4 - FIT2GO (A toolbox for fitness landscapes in evolution)
Berichtszeitraum: 2023-09-01 bis 2024-08-31
Quantifying how populations adapt to new environments is at the heart of evolutionary research. The possibility to adapt and the speed at which this is possible has direct implications for conservation and the response of populations to the climate crisis.
A factor that is often ignored when looking at genetic adaptation is the interaction of genes (epistasis), which may result in a different effect of two genetic variants that appear together from the effect of each individual variant. How frequent such interactions are is contentious. If they are frequent, this crucially affects the predictability of evolution. In addition, epistasis constrains the adaptive paths that populations can take to improve their fitness in a new environment.
The concept of fitness landscapes, which are mappings of genotypes or phenotypes to fitness, has frequently been used to study the consequences of epistasis. There exists a rich body of theory, and recently, technological advances have allowed for increasingly large experimental assessments of fitness landscapes.
In this project, we build on the theory of fitness landscapes to understand the prevalence of epistasis across levels of biological organization (e.g. protein, pathway, population levels) and across environments (e.g. hot, cold, in the presence of an antimicrobial treatment). Combining models and experiments, we evaluate whether the change of epistasis across environments is predictable, and how strongly epistasis affects adaptation upon environmental change.
A factor that is often ignored when looking at genetic adaptation is the interaction of genes (epistasis), which may result in a different effect of two genetic variants that appear together from the effect of each individual variant. How frequent such interactions are is contentious. If they are frequent, this crucially affects the predictability of evolution. In addition, epistasis constrains the adaptive paths that populations can take to improve their fitness in a new environment.
The concept of fitness landscapes, which are mappings of genotypes or phenotypes to fitness, has frequently been used to study the consequences of epistasis. There exists a rich body of theory, and recently, technological advances have allowed for increasingly large experimental assessments of fitness landscapes.
In this project, we build on the theory of fitness landscapes to understand the prevalence of epistasis across levels of biological organization (e.g. protein, pathway, population levels) and across environments (e.g. hot, cold, in the presence of an antimicrobial treatment). Combining models and experiments, we evaluate whether the change of epistasis across environments is predictable, and how strongly epistasis affects adaptation upon environmental change.
Throughout the course of this project, we made significant strides in understanding evolutionary processes through the study of fitness landscapes. Our research aimed to quantify how mutations, hybridization, and other mechanisms affect adaptation and speciation across biological scales and environmental conditions. This work, which spanned both theoretical and empirical approaches, has resulted in substantial contributions to the field of evolutionary biology, culminating in a total of 25 peer-reviewed publications related to the project, and more than 60 talks and 10 posters with which the PI and her team members presented the work at seminars and conferences.
The project focused on four main aims, each of which was integral to advancing our understanding of evolutionary dynamics. These aims covered a wide spectrum of topics, from quantifying the fitness effects of mutations to studying hybridization dynamics and non-standard forms of adaptation.
Aims 1 and 2: Fitness Landscapes Across Biological Levels and Environments
Our first focus was to quantify fitness landscapes across biological scales and environmental conditions. In this context, we examined the distribution of fitness effects of new mutations in the heat-shock protein Hsp90 under various environmental conditions (Cote-Hammarlof, Fragata et al., MBE, 2021; Flynn et al., eLife, 2020). Notably, our work revealed that regions of the protein showing fitness effects from mutations did not necessarily align with known structural features, such as active sites. This finding emphasizes the complexity of fitness landscapes and the potential for unexpected mutational effects.
We also explored the fitness effects of antimicrobial resistance mutations in E. coli under different genetic backgrounds and environmental conditions. This research uncovered a significant degree of epistasis, especially in non-standard environments (Hinz et al., MBE, 2024), while showing relatively little epistasis across temperature gradients (Ghenu et al., Phil Trans B, 2023). Additionally, we developed mathematical theory that critically assesses microbial growth models and inference methods (Ghenu, Marrec, et al., Frontiers in Ecology and Evolution, 2024; Marrec et al., Ecology and Evolution, 2023).
Aim 3: Mechanisms of Adaptation
In this Aim of the project, we explored different adaptation mechanisms, including modifiers of epistasis and mutation rates, to quantify how they may influence evolutionary dynamics. A noteworthy empirical finding was that the mutational load of bacteria in the mouse gut remains low even in the presence of mutator genotypes, indicating that weak selection dominates during the adaptation of bacteria in the mouse gut (Ramiro et al., Plos Biology, 2020). We also discovered that epigenetic mechanisms in yeast can provide a selective advantage in fluctuating environments (Stajic et al., GBE, 2021).
Our theoretical work extended to models of chromosomal inversions, demonstrating that small-effect deleterious mutations can accumulate rapidly in inversions, potentially leading to recessive lethal systems (Berdan et al., Plos Genetics, 2021). Furthermore, we developed and analyzed models of how populations under high mutation pressure could avoid extinction through evolutionary rescue mechanisms (Bank et al., Frontiers in Virology, 2023).
Aim 4: Hybridization Dynamics
The consequences of epistasis during hybridization were the final central theme of this project. Here, we developed new models to understand how hybridization influences evolutionary trajectories. For instance, we demonstrated that cryptic epistasis in fitness landscapes could enable speciation even in the presence of gene flow (Blanckaert et al., Phil Trans B, 2020). We also examined the extinction probability of hybrid populations, showing that genomic architecture plays a critical role in hybrid survival (Blanckaert et al., Evolution, 2023).
Our methodological innovations in this Aim extended to statistical approaches. We developed a method to detect hybrid incompatibilities using genomic data, which we applied to studies of fish hybrid populations (Li et al., Plos Genetics, 2022). Our new method overcomes the limitations of previous approaches by distinguishing between linkage disequilibrium from physical linkage and from hybrid incompatibilities, providing a promising tool for the identification of intrachromosomal hybrid incompatibilities.
The project focused on four main aims, each of which was integral to advancing our understanding of evolutionary dynamics. These aims covered a wide spectrum of topics, from quantifying the fitness effects of mutations to studying hybridization dynamics and non-standard forms of adaptation.
Aims 1 and 2: Fitness Landscapes Across Biological Levels and Environments
Our first focus was to quantify fitness landscapes across biological scales and environmental conditions. In this context, we examined the distribution of fitness effects of new mutations in the heat-shock protein Hsp90 under various environmental conditions (Cote-Hammarlof, Fragata et al., MBE, 2021; Flynn et al., eLife, 2020). Notably, our work revealed that regions of the protein showing fitness effects from mutations did not necessarily align with known structural features, such as active sites. This finding emphasizes the complexity of fitness landscapes and the potential for unexpected mutational effects.
We also explored the fitness effects of antimicrobial resistance mutations in E. coli under different genetic backgrounds and environmental conditions. This research uncovered a significant degree of epistasis, especially in non-standard environments (Hinz et al., MBE, 2024), while showing relatively little epistasis across temperature gradients (Ghenu et al., Phil Trans B, 2023). Additionally, we developed mathematical theory that critically assesses microbial growth models and inference methods (Ghenu, Marrec, et al., Frontiers in Ecology and Evolution, 2024; Marrec et al., Ecology and Evolution, 2023).
Aim 3: Mechanisms of Adaptation
In this Aim of the project, we explored different adaptation mechanisms, including modifiers of epistasis and mutation rates, to quantify how they may influence evolutionary dynamics. A noteworthy empirical finding was that the mutational load of bacteria in the mouse gut remains low even in the presence of mutator genotypes, indicating that weak selection dominates during the adaptation of bacteria in the mouse gut (Ramiro et al., Plos Biology, 2020). We also discovered that epigenetic mechanisms in yeast can provide a selective advantage in fluctuating environments (Stajic et al., GBE, 2021).
Our theoretical work extended to models of chromosomal inversions, demonstrating that small-effect deleterious mutations can accumulate rapidly in inversions, potentially leading to recessive lethal systems (Berdan et al., Plos Genetics, 2021). Furthermore, we developed and analyzed models of how populations under high mutation pressure could avoid extinction through evolutionary rescue mechanisms (Bank et al., Frontiers in Virology, 2023).
Aim 4: Hybridization Dynamics
The consequences of epistasis during hybridization were the final central theme of this project. Here, we developed new models to understand how hybridization influences evolutionary trajectories. For instance, we demonstrated that cryptic epistasis in fitness landscapes could enable speciation even in the presence of gene flow (Blanckaert et al., Phil Trans B, 2020). We also examined the extinction probability of hybrid populations, showing that genomic architecture plays a critical role in hybrid survival (Blanckaert et al., Evolution, 2023).
Our methodological innovations in this Aim extended to statistical approaches. We developed a method to detect hybrid incompatibilities using genomic data, which we applied to studies of fish hybrid populations (Li et al., Plos Genetics, 2022). Our new method overcomes the limitations of previous approaches by distinguishing between linkage disequilibrium from physical linkage and from hybrid incompatibilities, providing a promising tool for the identification of intrachromosomal hybrid incompatibilities.
One notable breakthrough of the project was the development of our new method for inferring hybrid incompatibilities from hybrid genomes (Li et al., Plos Genetics, 2022). This approach, unlike traditional methods that rely on associations of alleles (linkage disequilibrium), can differentiate between LD caused by physical proximity and LD resulting from hybrid incompatibilities of the Donzhansky-Muller type. This innovation paves the way for a better understanding of the genomic architecture of species barriers and the dynamics of hybridization.
Additionally, our work on eco-evolutionary fitness landscapes (Amado and Bank, Journal of Physics A, 2024) represents the first step towards a new eco-evolutionary fitness landscape theory. Our simulation study of a model that combines an epistatic fitness landscape with ecological interactions between genotypes demonstrates the complexity of eco-evolutionary dynamics in a discrete and epistatic genotype space with frequency-dependent selection.
Finally, our study on the challenges and pitfalls of inferring microbial growth rates exemplifies the benefits of interdisciplinary collaboration, highlighting how joining theoretical and experimental viewpoints is crucial to developing robust methods and addressing fundamental challenges in biology (Ghenu, Marrec et al., Frontiers in Ecology and Evolution, 2024).
Additionally, our work on eco-evolutionary fitness landscapes (Amado and Bank, Journal of Physics A, 2024) represents the first step towards a new eco-evolutionary fitness landscape theory. Our simulation study of a model that combines an epistatic fitness landscape with ecological interactions between genotypes demonstrates the complexity of eco-evolutionary dynamics in a discrete and epistatic genotype space with frequency-dependent selection.
Finally, our study on the challenges and pitfalls of inferring microbial growth rates exemplifies the benefits of interdisciplinary collaboration, highlighting how joining theoretical and experimental viewpoints is crucial to developing robust methods and addressing fundamental challenges in biology (Ghenu, Marrec et al., Frontiers in Ecology and Evolution, 2024).