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
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
Creation of a non-venomous honey bee. On average, two Australians die from bee stings each year. Our goal is produce honey bees that do not have a dangerous sting.
Proteomic and genetic analysis of subfertile bull spermatozoa. This project aims to identify protein changes on spermatozoa that are highly correlated with the fertility status of bulls. Bull fertility has approached an all-time low as breeding practice has focused predominately on milk production and beef tenderness. This project aims to understand the genetic causes that underpin bull and cattle infertility, and investigate better methods to predict the fertility status of bulls. This project ....Proteomic and genetic analysis of subfertile bull spermatozoa. This project aims to identify protein changes on spermatozoa that are highly correlated with the fertility status of bulls. Bull fertility has approached an all-time low as breeding practice has focused predominately on milk production and beef tenderness. This project aims to understand the genetic causes that underpin bull and cattle infertility, and investigate better methods to predict the fertility status of bulls. This project expects to contribute to better clinical management of cattle. This information can then be used for the development of a better diagnostic assay for both the dairy and beef industry.Read moreRead less
Maximizing male fertility: the role of CRISP proteins. This project aims to investigate the function of cysteine rich secretory protein (CRISP) family members in fertility. It is expected to generate new knowledge on the role CRISP1 and 4 play in sperm competition in vivo, and thus, evolutionary processes; to define the role seminal plasma CRISPs play in fertility; and identify the mechanism underpinning their biological activities. This will be achieved using a range of innovative, state-of-the ....Maximizing male fertility: the role of CRISP proteins. This project aims to investigate the function of cysteine rich secretory protein (CRISP) family members in fertility. It is expected to generate new knowledge on the role CRISP1 and 4 play in sperm competition in vivo, and thus, evolutionary processes; to define the role seminal plasma CRISPs play in fertility; and identify the mechanism underpinning their biological activities. This will be achieved using a range of innovative, state-of-the-art approaches. Expected outcomes and benefits include an enhanced knowledge of the mechanisms underpinning fertility and infertility, enhanced collaboration and research knowhow, and an evidence base for future applied projects aimed enhancing fertility in agricultural species.Read moreRead less
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.Read moreRead less