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Field of Research : Genetics
Status : Active
Australian State/Territory : VIC
Research Topic : VESTIBULAR DISEASE
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Genetics (3)
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP220101947

    Funder
    Australian Research Council
    Funding Amount
    $463,121.00
    Summary
    Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to gen .... Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to generate new knowledge on the roles of natural selection in shaping the genetic variation in traits and identify key factors that drive the differentiation of human populations. These outcomes will significantly improve our understanding on the evolution of human traits and adaptation of populations to changing environments.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190101818

    Funder
    Australian Research Council
    Funding Amount
    $487,000.00
    Summary
    The transgenerational effect of thermosensing in plants. This project aims to understand how thermosensing mechanisms in plants result in transgenerational change, and potentially adaptation to climate. Exploiting the recent discovery of the thermosensor phytochrome B, this project will decipher the molecular cascade which, either through long-distance communication or through persistence of an epigenetic state in the cell lineage, could lead to a trans generational memory in plants helping with .... The transgenerational effect of thermosensing in plants. This project aims to understand how thermosensing mechanisms in plants result in transgenerational change, and potentially adaptation to climate. Exploiting the recent discovery of the thermosensor phytochrome B, this project will decipher the molecular cascade which, either through long-distance communication or through persistence of an epigenetic state in the cell lineage, could lead to a trans generational memory in plants helping with climate adaptation. This project will unravel novel molecular mechanisms, which have the potential to pave the way for designing new climate-proofing solutions to cope with temperature uncertainty.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200100499

    Funder
    Australian Research Council
    Funding Amount
    $415,000.00
    Summary
    Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is un .... Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is unknown. This is useful for selecting the best parents for breeding in agriculture and for predicting the future phenotype of animals, crops and people. The proposed method uses data on very many traits to identify sequence variants that have a function and to predict the traits affected by each variant.
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