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
Developing methods for the analysis of massively parallel sequencing data in family studies. This project will develop analytical methods to use the latest, high-throughput method of generating sequencing data, i.e. the letters of the human genome alphabet. These tools will be used to identify the causal mutations in families with inherited disorders, leading to diagnostic tests for these families.
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
Solving the puzzle of complex disease - genes and their interactions with the environment. Many human diseases are caused by the interplay of genetic predisposition (nature) and the environment (nurture); but their causes remain a mystery, since much past research has focused on these aspects in isolation. This project will aim to better understand these complex diseases using a multi-factorial approach that brings both nature and nurture together.
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
Genome-wide determination of Puccinia psidii s.l. rust resistance in eucalypts. Recently, guava rust was detected in Australia, posing significant risks to native flora, plantations, and timber exports. Scientists from The University of Melbourne and Victorian Department of Primary Industries together with tree breeders, forest growers and forest managers aim to use tree genomics rust resistance breeding to enable management and operational responses and inform policy development.
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.
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