Discovery Early Career Researcher Award - Grant ID: DE130100614
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Novel statistical algorithms and methods to quantify and partition pleiotropy between complex traits in populations. A fundamental question in biology is how common genetic effects are shared between traits or groups. For example, is cognition or human behaviour genetically identical across genders or across human population groups? This project will address these questions using multiple independent genome-wide association studies.
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
Discovery Early Career Researcher Award - Grant ID: DE220101210
Funder
Australian Research Council
Funding Amount
$451,634.00
Summary
Deciphering molecular genetic mechanisms underlying chromatin interactions. This project aims to generate the high confidence map of enhancer-promoter links in 61 tissues and cells through robust integration of novel machine learning tools with genomic and epigenomic datasets. Understanding which key elements in the genome may be important to fine-tune gene expression is essential for understanding biological pathways. The expected outcomes include i) New tools to robustly identify true chromati ....Deciphering molecular genetic mechanisms underlying chromatin interactions. This project aims to generate the high confidence map of enhancer-promoter links in 61 tissues and cells through robust integration of novel machine learning tools with genomic and epigenomic datasets. Understanding which key elements in the genome may be important to fine-tune gene expression is essential for understanding biological pathways. The expected outcomes include i) New tools to robustly identify true chromatin pairs; ii) Comperehensive maps of regulatory interactomes in 61 tissues & cells, which will provide a roadmap for interpreting & prioritising noncoding variants.
This should provide significant benefit to Australia's capacity for cutting-edge genomics research through fundamental understanding of gene regulation mechanism.Read moreRead less
Identifying Target Genes For Novel Anti-epileptic Therapies In The Mouse
Funder
National Health and Medical Research Council
Funding Amount
$469,802.00
Summary
Epilepsy is a disease which affects 2-4% of the population. There are a wide range of drugs available to treat the condition but there is consistently 30-40% of patients who do not respond well to any of these drugs and who continue to have seizures. The reason that there are no drugs available for these people is that most of the drugs available have been designed along the same principles. A new set of principles is needed to develop new drugs which will be able to treat those people not respo ....Epilepsy is a disease which affects 2-4% of the population. There are a wide range of drugs available to treat the condition but there is consistently 30-40% of patients who do not respond well to any of these drugs and who continue to have seizures. The reason that there are no drugs available for these people is that most of the drugs available have been designed along the same principles. A new set of principles is needed to develop new drugs which will be able to treat those people not responding to current therapy. This project is designed to identify new biologic pathways which may be interrupted with drugs to prevent seizures in people with epilepsy. This project uses a procedure to induce mutations into genes in mice and then screens for mice which do not seize when challenged with a drug which generates seizures in mice. Genetic studies will identify the mutated genes and these will be used as potential targets for new therapies or will identify new biological pathway which should expand the use of future anti-epileptic drugs.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.
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
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.