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.Read moreRead less
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
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
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. 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.
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
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