Estimation of non-additive genetic variance for complex traits using genome-wide single nucleotide polymorphyisms and sequence data. Finding genes for traits of importance in agriculture, ecology and human health depends on understanding the genetic basis of these traits. This project will investigate whether variation in traits in humans, cattle and wild sheep are influenced by gene-gene interactions.
The genetic architecture and evolution of quantitative traits. Most important traits are controlled by many genes and by the environment, however there is little knowledge of how many genes are involved in these complex traits and what their effects are. This project will describe the number of genes and their effects for complex traits in humans and livestock and explain how these genes evolve.
The genomics of adaptation in Wolbachia pipientis, an emerging biocontrol agent. Australians are increasingly exposed to insect-transmitted diseases such as dengue fever. Novel biocontrol methods using the bacterium Wolbachia aim to control insect populations to reduce disease transmission. Our research will be the first to investigate genomic variation and the process of adaptation to new insect hosts in Wolbachia. The novel data and understanding of evolutionary processes we generate will be c ....The genomics of adaptation in Wolbachia pipientis, an emerging biocontrol agent. Australians are increasingly exposed to insect-transmitted diseases such as dengue fever. Novel biocontrol methods using the bacterium Wolbachia aim to control insect populations to reduce disease transmission. Our research will be the first to investigate genomic variation and the process of adaptation to new insect hosts in Wolbachia. The novel data and understanding of evolutionary processes we generate will be critical for screening bacterial biocontrol candidates and designing biocontrol release strategies. It will also strengthen the position of Australian research as a world-leader in the fusion of post-genomics and applied microbiology. Read moreRead less
Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to gen ....Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to generate new knowledge on the roles of natural selection in shaping the genetic variation in traits and identify key factors that drive the differentiation of human populations. These outcomes will significantly improve our understanding on the evolution of human traits and adaptation of populations to changing environments.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
The role of X-chromosome inactivation in quantitative trait variation. This project aims to develop methods and software that can be applied to genetic and genomic studies in animal breeding, wildlife protection, and humans. X-chromosome inactivation (XCI) is an important biological phenomenon but its effect on quantitative trait variation remains largely unknown. This project aims to develop novel statistical methods to estimate the X-linked genetic variance and the proportion that escapes XCI, ....The role of X-chromosome inactivation in quantitative trait variation. This project aims to develop methods and software that can be applied to genetic and genomic studies in animal breeding, wildlife protection, and humans. X-chromosome inactivation (XCI) is an important biological phenomenon but its effect on quantitative trait variation remains largely unknown. This project aims to develop novel statistical methods to estimate the X-linked genetic variance and the proportion that escapes XCI, and identify trait-associated genetic variants affected and not affected by XCI. The methods would then be applied to large datasets from genome-wide association studies for a large number of traits. Project outcomes may enable us to better understand the role of XCI in quantitative trait variation and gene expression in humans and animals.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