Reference number : GC-2017-Q1-01626, amendment number : , agreement type : G, recipient legal name : Yeaman, Samuel (University of Calgary), recipient country : CA, recipient province : nan, recipient city : Alberta, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Adaptation is central to evolution, but we are only beginning to answer fundamental questions about how it works: How commonly do species adapt to the same kind of environment in different ways? Why does this occur? What maintains the capacity of a species to adapt to changes in its environment? My research program uses computational approaches to explore how genetics can affect the outcome of evolution, and then seeks to test hypotheses that arise from this work using empirical datasets to answer these fundamental questions. In particular, my research program explores how populations adapt to heterogeneous environments, in which fitness trade-offs often prevent one phenotype from being optimal in all possible conditions. In such cases, the tension between divergent natural selection, migration, and recombination can greatly alter the genetic architecture that evolves: in some conditions, architectures tend to be characterized by fewer, larger, and more tightly clustered alleles, whereas in other conditions, they tend to be characterized by many small alleles distributed throughout the genome. This interplay between ecology and genetics can greatly affect the predicted outcome and repeatability of evolution, as well as the evolvability of a species. 
 I propose to explore how differences in the way that genotypes give rise to phenotypes and phenotypes translate into fitness can affect the architecture of local adaptation. We will use individual-based simulations to explore how redundancy in the mapping of genotype to phenotype and deleterious side-effects of phenotypic changes (i.e. pleiotropy) affect the outcome of adaptation, in terms of the kind of architecture that evolves and the repeatability of the genetic basis of adaptation. This will provide the theoretical groundwork for us to develop and extend statistical tests to compare genetic architectures found in different species adapting to similar stresses. By comparing the similarity of genetic architectures underlying adaptation, we will learn whether such responses are shaped by genetic or selective constraints. Finally, we will collect novel datasets on adaptation to temperature in two species of fish: tubesnout and tidepool sculpin and compare them to existing datasets for threespine stickleback, deploying the tests we develop to study the repeatability of adaptation. Taken together, this research will extend theoretical understanding of how evolution works and improve statistical tools for testing predictions about adaptation using empirical data, as well as providing a case study illustrating how to test how genetics and ecology shape patterns of adaptation in the genome., program purpose french : Adaptation is central to evolution, but we are only beginning to answer fundamental questions about how it works: How commonly do species adapt to the same kind of environment in different ways? Why does this occur? What maintains the capacity of a species to adapt to changes in its environment? My research program uses computational approaches to explore how genetics can affect the outcome of evolution, and then seeks to test hypotheses that arise from this work using empirical datasets to answer these fundamental questions. In particular, my research program explores how populations adapt to heterogeneous environments, in which fitness trade-offs often prevent one phenotype from being optimal in all possible conditions. In such cases, the tension between divergent natural selection, migration, and recombination can greatly alter the genetic architecture that evolves: in some conditions, architectures tend to be characterized by fewer, larger, and more tightly clustered alleles, whereas in other conditions, they tend to be characterized by many small alleles distributed throughout the genome. This interplay between ecology and genetics can greatly affect the predicted outcome and repeatability of evolution, as well as the evolvability of a species. 
 I propose to explore how differences in the way that genotypes give rise to phenotypes and phenotypes translate into fitness can affect the architecture of local adaptation. We will use individual-based simulations to explore how redundancy in the mapping of genotype to phenotype and deleterious side-effects of phenotypic changes (i.e. pleiotropy) affect the outcome of adaptation, in terms of the kind of architecture that evolves and the repeatability of the genetic basis of adaptation. This will provide the theoretical groundwork for us to develop and extend statistical tests to compare genetic architectures found in different species adapting to similar stresses. By comparing the similarity of genetic architectures underlying adaptation, we will learn whether such responses are shaped by genetic or selective constraints. Finally, we will collect novel datasets on adaptation to temperature in two species of fish: tubesnout and tidepool sculpin and compare them to existing datasets for threespine stickleback, deploying the tests we develop to study the repeatability of adaptation. Taken together, this research will extend theoretical understanding of how evolution works and improve statistical tools for testing predictions about adaptation using empirical data, as well as providing a case study illustrating how to test how genetics and ecology shape patterns of adaptation in the genome., agreement title english : How constrained is evolution? The importance of genetic redundancy in local adaptation, agreement title french : How constrained is evolution? The importance of genetic redundancy in local adaptation, agreement number : RGPIN, agreement value : 165000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada