Rapid mapping of genes for complex traits. This project will develop a new resource that will allow rapid identification of genes controlling complex traits. This world-leading resource will improve knowledge of diseases like diabetes and neurological diseases.
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
Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statis ....Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statistical methods provide the opportunity to close this gap. The outcome will be identification of many genomic variants causing variation in complex traits. This will benefit scientific understanding of complex traits and the ability to predict traits for individuals from their genome sequence.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
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.
Mutational genetic variance and the fitness optimum. Mutation and selection are ubiquitous forces in nature, but we do not understand how genetic variation produced by mutation is maintained in the presence of selection that depletes it. The recent discovery of apparent stabilising selection on traits with high levels of genetic variation provides a new approach to understanding this paradox.
A genomic approach to understanding the maintenance of genetic variation under sexual selection. Using a model Australian species, this project will dissect the linkages between DNA sequence variation, gene expression, phenotypic traits and fitness in a natural population. Data will facilitate powerful tests of evolutionary processes thought to maintain genetic variation in complex traits.
The contribution of pleiotropic mutation to genetic variation and evolution. This project aims to provide an in-depth characterization of pleiotropic effects across many traits, including fitness, in an outbred population of the fly, Drosophila serrata. The potential for one gene to affect many traits, pleiotropy, has been recognised for over 100 years. Pleiotropy is expected to underlie diverse biological phenomena, including evolution and age-related human diseases. Despite this, the contribut ....The contribution of pleiotropic mutation to genetic variation and evolution. This project aims to provide an in-depth characterization of pleiotropic effects across many traits, including fitness, in an outbred population of the fly, Drosophila serrata. The potential for one gene to affect many traits, pleiotropy, has been recognised for over 100 years. Pleiotropy is expected to underlie diverse biological phenomena, including evolution and age-related human diseases. Despite this, the contribution of pleiotropy to variation among individuals in appearance and in fitness remains poorly understood. By measuring the extent of pleiotropy and its fitness consequences, this project aims to advance understanding of how mutation and selection shape genetic variation and evolutionary potential in natural populations.Read moreRead less