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Field of Research : Molecular Evolution
Field of Research : Biological Adaptation
Australian State/Territory : VIC
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    Discovery Projects - Grant ID: DP210100505

    Funder
    Australian Research Council
    Funding Amount
    $605,516.00
    Summary
    Defining the Molecular Targets of Evolution. With significant advances in next-generation sequencing technologies we now have the genomes of hundreds vertebrate species, but understanding how the differences and similarities within these genomes control species diversity is largely unknown. The similarity in skull shape between the thylacine and dogs coupled with their deep ancestry, having last shared a common ancestor over 160 million years ago, provides an unprecedented opportunity to examine .... Defining the Molecular Targets of Evolution. With significant advances in next-generation sequencing technologies we now have the genomes of hundreds vertebrate species, but understanding how the differences and similarities within these genomes control species diversity is largely unknown. The similarity in skull shape between the thylacine and dogs coupled with their deep ancestry, having last shared a common ancestor over 160 million years ago, provides an unprecedented opportunity to examine how evolution works at the DNA level. This proposal will determine if animals that develop identical skull shapes, also show identical changes in their DNA. The findings will define new developmental genes and explain how selection, adaptation and evolution works at the DNA level.
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    Funded Activity

    Discovery Projects - Grant ID: DP180102161

    Funder
    Australian Research Council
    Funding Amount
    $398,794.00
    Summary
    Experimental co-evolution of Yeast and E. coli. This project aims to measure the rates and genetic mechanisms of adaptation for individual species within a microbial community. Expected outcomes of this interdisciplinary project include the first genomic and phenotypic dataset of a model microbial community, and novel tools for the analysis of meta-genomic datasets. This project has the potential to transform understanding of microbial adaptation.
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