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
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.
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.
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.
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
Characterising inheritance patterns of whole genome DNA methylation. This project aims to characterise epigenetic diversity and inheritance patterns in whole genome sequencing data from a unique human population. The project will employ the well-characterised Norfolk Island genetic isolate, cost-effective whole genome bisulphite sequencing technologies and advanced bioinformatics pipelines and statistical models. It will involve cross-discipline collaboration between human geneticists, epigeneti ....Characterising inheritance patterns of whole genome DNA methylation. This project aims to characterise epigenetic diversity and inheritance patterns in whole genome sequencing data from a unique human population. The project will employ the well-characterised Norfolk Island genetic isolate, cost-effective whole genome bisulphite sequencing technologies and advanced bioinformatics pipelines and statistical models. It will involve cross-discipline collaboration between human geneticists, epigeneticists, statistical geneticists and bioinformaticians. This project will advance our understanding of the interaction of genetics and epigenetics and their relationship to diversity and inheritance in humans.Read moreRead less
The genetics of ageing in human populations. This project aims to test whether genetic differences among individuals influence changes in cognition and physiological function in later life. Differences among individuals, in terms of distinct changes in their physiology as they age, lead to differences in their susceptibility to negative later-life outcomes and ultimately to differences in lifespan. Using a combination of genomic techniques, novel data analysis methods, and the largest dataset of ....The genetics of ageing in human populations. This project aims to test whether genetic differences among individuals influence changes in cognition and physiological function in later life. Differences among individuals, in terms of distinct changes in their physiology as they age, lead to differences in their susceptibility to negative later-life outcomes and ultimately to differences in lifespan. Using a combination of genomic techniques, novel data analysis methods, and the largest dataset of its kind, the project intends to identify the genomic regions and biochemical pathways associated with these changes, and to test for genetic associations between early-life reproduction and later-life outcomes. This is crucial to understanding, predicting and managing transitions across different human life stages.Read moreRead less
The nature of standing genetic variation. This project aims to expand understanding of the genetic variation underlying phenotypic differences among individuals. The nature of genetic variation has broad consequences across biology, from the detection of causal genetic variants to the adaptation of natural populations. This project will take a novel experimental approach to test several long-standing assumptions about the effects of new mutations on individual traits and their joint pleiotropic ....The nature of standing genetic variation. This project aims to expand understanding of the genetic variation underlying phenotypic differences among individuals. The nature of genetic variation has broad consequences across biology, from the detection of causal genetic variants to the adaptation of natural populations. This project will take a novel experimental approach to test several long-standing assumptions about the effects of new mutations on individual traits and their joint pleiotropic effect on fitness. By expanding our understanding of how mutation, selection and drift interact, this project could provide significant improvements in our understanding of the genetic basis of phenotypes, and our ability to predict phenotypic evolution.Read moreRead less