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Research Topic : gene array
Socio-Economic Objective : Dairy Cattle
Australian State/Territory : VIC
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Animal Breeding (2)
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  • Funded Activity

    Discovery Projects - Grant ID: DP160101056

    Funder
    Australian Research Council
    Funding Amount
    $338,300.00
    Summary
    The extent, causes and implications of pleiotropy among complex traits. The project seeks to understand how a DNA mutation can affect many characters or traits. Many traits are called complex because they are controlled by a very large number of genes, most of which have small effects. Complex traits include traits important in medicine (such as susceptibility to heart disease) and in agriculture (such as tenderness of meat). Because there are many genes affecting each trait, most genes have sma .... The extent, causes and implications of pleiotropy among complex traits. The project seeks to understand how a DNA mutation can affect many characters or traits. Many traits are called complex because they are controlled by a very large number of genes, most of which have small effects. Complex traits include traits important in medicine (such as susceptibility to heart disease) and in agriculture (such as tenderness of meat). Because there are many genes affecting each trait, most genes have small effects which makes them hard to identify. The fact that a mutation that has a small effect on a complex trait also has a larger effect on a less complex trait may help us to identify the mutation and use it in agriculture or medicine.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP230101352

    Funder
    Australian Research Council
    Funding Amount
    $541,818.00
    Summary
    Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statis .... Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statistical methods provide the opportunity to close this gap. The outcome will be identification of many genomic variants causing variation in complex traits. This will benefit scientific understanding of complex traits and the ability to predict traits for individuals from their genome sequence.
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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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