Industrial Transformation Research Hubs - Grant ID: IH130200013
Funder
Australian Research Council
Funding Amount
$4,979,922.00
Summary
ARC Research Hub for advanced breeding to transform prawn aquaculture. ARC Research Hub for advanced breeding to transform prawn aquaculture. This Research Hub aims to bring together world-leading animal geneticists, research and service providers, and Australia's largest prawn farm to gather the genomic resources, commercial phenotypic data, and apply cutting-edge genetic and genomic selection methodologies, leading to the transformative improvement program for a black tiger prawn aquaculture s ....ARC Research Hub for advanced breeding to transform prawn aquaculture. ARC Research Hub for advanced breeding to transform prawn aquaculture. This Research Hub aims to bring together world-leading animal geneticists, research and service providers, and Australia's largest prawn farm to gather the genomic resources, commercial phenotypic data, and apply cutting-edge genetic and genomic selection methodologies, leading to the transformative improvement program for a black tiger prawn aquaculture species globally.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120100390
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Characterisation of collagenous lectins and their roles in ovine infectious diseases. Specific proteins involved in immunity against infections will be studied in sheep to enhance their immune response against specific infections, such as ovine Johne's disease and footrot. This may lead to selective breeding of sheep that are more resistant to disease, minimising production losses and use of medications.
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.Read moreRead less
Increasing amphibian immunity to combat disease causing mass extinction. This project aims to increase amphibian survival to combat the devastating chytrid fungus by identifying resistance genes and increasing their frequency in the host population. The project is interdisciplinary and uses targeted genetic manipulation techniques developed for agriculture to improve disease resistance in wildlife for the first time. Expected outcomes include 1) enhanced international collaborations in comparati ....Increasing amphibian immunity to combat disease causing mass extinction. This project aims to increase amphibian survival to combat the devastating chytrid fungus by identifying resistance genes and increasing their frequency in the host population. The project is interdisciplinary and uses targeted genetic manipulation techniques developed for agriculture to improve disease resistance in wildlife for the first time. Expected outcomes include 1) enhanced international collaborations in comparative immunology, 2) a comprehensive understanding of immunity to chytridiomycosis, and 3) disease resistant amphibians. The anticipated benefit is ability to apply the optimal method to improve conservation of wildlife threatened by emerging disease, such as marker assisted selective breeding or genetic engineering.Read moreRead less
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.
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.Read moreRead less
Targeting TGF-beta proteins to control animal reproduction. This project aims to develop a suite of novel biologics to control fertility in female mammals. This project expects to demonstrate that targeting a single class of ovarian proteins will enhance or inhibit egg production. The expected outcomes of this project are to (1) transform the breeding of livestock animals, which should provide significant benefits to the agricultural industry, through increased herd/flock sizes, and (2) provide ....Targeting TGF-beta proteins to control animal reproduction. This project aims to develop a suite of novel biologics to control fertility in female mammals. This project expects to demonstrate that targeting a single class of ovarian proteins will enhance or inhibit egg production. The expected outcomes of this project are to (1) transform the breeding of livestock animals, which should provide significant benefits to the agricultural industry, through increased herd/flock sizes, and (2) provide a non-surgical method of contraception in companion/feral species, which should address the large unmet need for fertility control in these animals.
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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.Read moreRead less
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.Read moreRead less
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.Read moreRead less