Why is most of the genetic variance for complex traits undetected by large powerful screens of common variants? The genomics revolution has made it possible to measure thousands of DNA variants in individuals. These variants have been associated with phenotypic outcomes in a range of species. Paradoxically, even very large studies have only accounted for a fraction of the resemblance between relatives that we know exist. Our study will test three specific hypotheses to explain this paradox. A be ....Why is most of the genetic variance for complex traits undetected by large powerful screens of common variants? The genomics revolution has made it possible to measure thousands of DNA variants in individuals. These variants have been associated with phenotypic outcomes in a range of species. Paradoxically, even very large studies have only accounted for a fraction of the resemblance between relatives that we know exist. Our study will test three specific hypotheses to explain this paradox. A better understanding about the genetic architecture for complex traits will improve the efficiency of gene mapping methods, including applications in humans for traits related to productive ageing and a healthy start to life, will lead to more efficient selection programs in agricultural populations and will inform us with respect to past evolutionary events.Read moreRead less
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
Identification of nuclear reprogramming factors in oocyte cytoplasm. The mature oocyte contains dominant factors that are capable of erasing tissue specific gene expression profiles of somatic cells. These reprogramming factors would be valuable for dedifferentiation of cells and for nuclear transfer in animal cloning. The research involves determination of reprogramming factors present in active cytoplasm following enucleation of the germinal vesicle, blockage of transcription and translation, ....Identification of nuclear reprogramming factors in oocyte cytoplasm. The mature oocyte contains dominant factors that are capable of erasing tissue specific gene expression profiles of somatic cells. These reprogramming factors would be valuable for dedifferentiation of cells and for nuclear transfer in animal cloning. The research involves determination of reprogramming factors present in active cytoplasm following enucleation of the germinal vesicle, blockage of transcription and translation, and timed cultures. The assays will involve maintenance of reprogramming ability and erasure of somatic gene transcription. By subtractive elimination the function of isolated proteins which are involved in reprogramming will be identified for potential recombinant production.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
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