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Field of Research : Genetics
Research Topic : Breeding Programs
Field of Research : Animal Breeding
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  • Funded Activity

    Linkage Projects - Grant ID: LP160101626

    Funder
    Australian Research Council
    Funding Amount
    $420,000.00
    Summary
    Novel genomic technologies to improve fertility in northern beef cattle. This project aims to develop new genomic technologies to enable accelerated improvement of cow fertility. Increased global demand for beef is driving northern Australian beef enterprises to develop innovative ways to increase productivity. A substantial industry challenge is poor fertility of cows, with weaning rates frequently less than 40%. The expected outcomes of this project are an improvement in weaning rates to enabl .... Novel genomic technologies to improve fertility in northern beef cattle. This project aims to develop new genomic technologies to enable accelerated improvement of cow fertility. Increased global demand for beef is driving northern Australian beef enterprises to develop innovative ways to increase productivity. A substantial industry challenge is poor fertility of cows, with weaning rates frequently less than 40%. The expected outcomes of this project are an improvement in weaning rates to enable accelerated genetic gain for fertility in these enterprises by delivering a low cost array, which assays thousands of DNA variants affecting fertility simultaneously. This should provide significant benefits such as a new genomic prediction method informed by gene expression data from a unique resource of Brahman cattle with exceptionally high fertility, generating significant industry benefits.
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    Funded Activity

    Discovery Projects - Grant ID: DP200103734

    Funder
    Australian Research Council
    Funding Amount
    $480,234.00
    Summary
    Genetic Basis of Variable Expression of Glycan Xeno-Autoantigens by Cattle. Meat and dairy products from cattle contain sugar structures (glycans) that are not made by humans. These structures can be recognised by the immune system and lead to allergic reactions, inflammation and potentially cancer. These non-human structures are called xeno-autoantigens or XAs. We have discovered individual cattle that do not produce one of these XAs. We will study the gene required to make XA in the XA-free ca .... Genetic Basis of Variable Expression of Glycan Xeno-Autoantigens by Cattle. Meat and dairy products from cattle contain sugar structures (glycans) that are not made by humans. These structures can be recognised by the immune system and lead to allergic reactions, inflammation and potentially cancer. These non-human structures are called xeno-autoantigens or XAs. We have discovered individual cattle that do not produce one of these XAs. We will study the gene required to make XA in the XA-free cattle to find the underlying mutation. The same approach will be used to look for natural XA-free individuals in other food species. This knowledge may enable us to create a test to facilitate the natural breeding of non-GMO, XA-free livestock to benefit Australian primary producers and provide safer food for consumers.
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    Funded Activity

    Linkage Projects - Grant ID: LP100100880

    Funder
    Australian Research Council
    Funding Amount
    $280,000.00
    Summary
    Methods to infer dense genomic information from sparsely genotyped populations. Prediction of phenotype based on DNA polymorphisms or sequence has important applications such as prediction of disease risk in human medicine and prediction of genetic value in plant or animal breeding. This project will enhance precision and lower the cost of association studies leading to substantial increase in accuracy of such predictions. This will allow more effective genetic improvement, particularly of diff .... Methods to infer dense genomic information from sparsely genotyped populations. Prediction of phenotype based on DNA polymorphisms or sequence has important applications such as prediction of disease risk in human medicine and prediction of genetic value in plant or animal breeding. This project will enhance precision and lower the cost of association studies leading to substantial increase in accuracy of such predictions. This will allow more effective genetic improvement, particularly of difficult but important traits such as disease resistance, reduced green-house gas emissions and product quality. The same methods can be extended to improve genetic improvement in plants and better prediction of human disease risk.
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    Funded Activity

    Linkage Projects - Grant ID: LP0775187

    Funder
    Australian Research Council
    Funding Amount
    $222,000.00
    Summary
    Breeding for the future - Alpaca genetics. The Australian alpaca industry is recognised as an international leader. Alpaca fleece provides an annual national economic benefit of $1 million and has enormous potential for growth. This project will use a novel molecular mapping approach to generate a genetic test for desirable Suri fleece - the single biggest factor in developing a purebreeding suri line whilst retaining variation in other traits and avoiding inbreeding. This will quickly increase .... Breeding for the future - Alpaca genetics. The Australian alpaca industry is recognised as an international leader. Alpaca fleece provides an annual national economic benefit of $1 million and has enormous potential for growth. This project will use a novel molecular mapping approach to generate a genetic test for desirable Suri fleece - the single biggest factor in developing a purebreeding suri line whilst retaining variation in other traits and avoiding inbreeding. This will quickly increase the industry value, providing opportunity for rural communities to diversify farming enterprises and maximise income, and offering further employment in regional areas. This project will ensure Australian breeders retain a competitive edge in the face of alpaca research beginning in the USA.
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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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    Funded Activity

    Discovery Projects - Grant ID: DP130100542

    Funder
    Australian Research Council
    Funding Amount
    $246,000.00
    Summary
    Evolution, selection and estimation of polygenic epistatic networks in quantitative traits. Traits observed in organisms, such as height, are the result of an individual's genes and how they relate to the environment. But genes do not act alone; they work together in complex interactions. This project aims to understand these interactions and their role in animal production and human disease.
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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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    Funded Activity

    Discovery Projects - Grant ID: DP160102126

    Funder
    Australian Research Council
    Funding Amount
    $331,600.00
    Summary
    Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and meth .... Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and methods and an efficient algorithm implemented in software, which would broadly benefit the field of complex trait genetics. Methods to estimate genotype–environment interaction effects at the genomic level would help elucidate complex biological systems, including human genetic response to changing environmental factors and the potential adaptation of animals to changing environmental conditions.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190100766

    Funder
    Australian Research Council
    Funding Amount
    $404,000.00
    Summary
    Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key featur .... Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key feature in biology, which relates to dissecting the complex mechanism of association and interaction. The proposed statistical model implemented in a context of a novel design based on multiple GWAS data sets is a paradigm shifting-tool with applications to multiple industries.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT160100229

    Funder
    Australian Research Council
    Funding Amount
    $719,313.00
    Summary
    Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, populat .... Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, population samples or from different populations (e.g. multi-ethnicities or multi-breeds). The expected outcome is to better understand the dynamic architecture of complex traits and develop methods with improved power, precision and accuracy in genomic analyses.
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