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Grant: Discovery Grants Program - Individual

Carleton University

$40,000.00

Population size and the limits of natural selection

EF 2018-19

Résumé
Evolutionary biologists are centrally concerned with understanding and predicting how populations change over time. A wide range of population features and processes can influence evolutionary responses, including genetics, environmental variation, and migration. Under this proposal, we will investigate the influence of population size on the speed and direction of evolution: population size is crucial in determining both the input of variation (that is, mutations) into a population, and in the fate of mutations once they have arisen.*We will test important predictions concerning the influence of population size on rates and patterns of evolution. Theory predicts that evolution in small populations should lead to more varied outcomes than in large populations. Moreover, in large populations, genetic exchange between individuals is expected to increase the rate of adaptation. We will test these predictions by experimentally evolving populations of the bacterium Escherichia coli in the laboratory. Use of bacteria for these experiments will allow us to directly control population size and to follow evolution in many replicate populations. We will be able to track evolution both by measuring fitness of the evolved populations, and by sequencing their genomes so as to identify the genetic basis of evolution. Computational analyses of sequenced bacterial genomes will allow us to test additional theoretical predictions. Regions of the genome with low levels of genetic exchange are expected to harbor less genetic variation than regions with high levels of exchange. This prediction has previously been tested in animals, but not in bacteria. *Our proposed work will address key gaps in our understanding of the relationship between population size and the evolutionary process. Beyond its relevance to evolutionary theory, our work can inform other evolutionary scenarios where demographic processes are thought to be important, such as pathogen evolution, disease transmission and evolution at range margins.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2018-05340
Name nom
Wong, Alex
Department département
Biology
Organization id
23
Institution établissement
Carleton University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
40000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1503
Committee name en
Evolution and Ecology
Committee name fr
Évolution et écologie
Area of application code
1201
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Life sciences (including biotechnology)
Area of application fr
Sciences de la vie (y compris biotechnologie)
Research subject code
5005
Research subject group en
Genetics
Research subject group fr
Génétique
Research subject en
Evolutionary genetics
Research subject fr
Génétique évolutive
Partie
1
Nb partie
5
Application title
Population size and the limits of natural selection
Keyword
NSERC
Application summary
Evolutionary biologists are centrally concerned with understanding and predicting how populations change over time. A wide range of population features and processes can influence evolutionary responses, including genetics, environmental variation, and migration. Under this proposal, we will investigate the influence of population size on the speed and direction of evolution: population size is crucial in determining both the input of variation (that is, mutations) into a population, and in the fate of mutations once they have arisen.*We will test important predictions concerning the influence of population size on rates and patterns of evolution. Theory predicts that evolution in small populations should lead to more varied outcomes than in large populations. Moreover, in large populations, genetic exchange between individuals is expected to increase the rate of adaptation. We will test these predictions by experimentally evolving populations of the bacterium Escherichia coli in the laboratory. Use of bacteria for these experiments will allow us to directly control population size and to follow evolution in many replicate populations. We will be able to track evolution both by measuring fitness of the evolved populations, and by sequencing their genomes so as to identify the genetic basis of evolution. Computational analyses of sequenced bacterial genomes will allow us to test additional theoretical predictions. Regions of the genome with low levels of genetic exchange are expected to harbor less genetic variation than regions with high levels of exchange. This prediction has previously been tested in animals, but not in bacteria. *Our proposed work will address key gaps in our understanding of the relationship between population size and the evolutionary process. Beyond its relevance to evolutionary theory, our work can inform other evolutionary scenarios where demographic processes are thought to be important, such as pathogen evolution, disease transmission and evolution at range margins.