I am a statistical geneticist. My research focuses on statistical genetic methodology with application to mental health, particularly to understanding the genetic architecture of anxiety and depression disorders.
I work at the interface of quantitative, statistical, population and human genetics and bioinformatics, aiming to understand and unravel genetic variation in disease susceptibility and endophenotypes in human populations.
Unravelling The Genetic Causes Of Bipolar Disorder: Lessons From Rare But Highly Penetrant Variants In Very Heritable Forms Of Illness
Funder
National Health and Medical Research Council
Funding Amount
$705,834.00
Summary
Bipolar disorder is a severe mood disorder affecting over 350,000 Australians, for which the causes remain largely unknown. This project will apply a powerful new technology, exome sequencing, to rare families with highly heritable forms of bipolar disorder to identify specific genetic factors which increase disease risk. A greater understanding of the genetic causes of this illness may eventually lead to improvements in diagnosis, treatment and quality of life of people suffering with this debi ....Bipolar disorder is a severe mood disorder affecting over 350,000 Australians, for which the causes remain largely unknown. This project will apply a powerful new technology, exome sequencing, to rare families with highly heritable forms of bipolar disorder to identify specific genetic factors which increase disease risk. A greater understanding of the genetic causes of this illness may eventually lead to improvements in diagnosis, treatment and quality of life of people suffering with this debilitating mental illness.Read moreRead less
I am working at the interface of quantitative, statistical, population and human genetics and bioinformatics, aiming to understand and unravel genetic variation in disease susceptibility and endophenotypes in human populations.
Many recent gene mapping efforts have focused on population based approaches instead of previously used family based approaches. One of the limiting factors with population based approaches is the cost of the technology - each participant must be evaluated (or genotyped) for hundreds of thousands of genetic markers. The cost can be reduced by using an approach which pools individuals together for genotyping, with statistical models used to deal with the problems that this creates.
Genomic Approaches To Understanding Tasmanian Devil Facial Tumor Disease
Funder
National Health and Medical Research Council
Funding Amount
$210,855.00
Summary
Devil facial tumor disease (DFTD) is an emerging infectious disease affecting Tasmanian devils. DFTD is a transmissible cancer, and results in the growth of large tumors usually on the face and mouth of affected animals. DFTD has led to the collapse of the Tasmanian devil population, and there is concern that the disease will drive devils to extinction in the wild within the next 20 years. I propose to use new genome sequencing technologies to discover genes responsible for DFTD.
Mapping Of Genetic Traits In Experimental Models Using Databases
Funder
National Health and Medical Research Council
Funding Amount
$237,750.00
Summary
The project aims to detect genes that influence human traits. These traits could be a disease such as diabetes or they may be much less sinister, representing hearing range as an example. Many of these traits are difficult to detect because they are governed by many genes which may also interact with the environment to influence the trait. In order to detect genes in these traits we would like to simplify the complex interactions by eliminating the environment as a potential cause or concentrati ....The project aims to detect genes that influence human traits. These traits could be a disease such as diabetes or they may be much less sinister, representing hearing range as an example. Many of these traits are difficult to detect because they are governed by many genes which may also interact with the environment to influence the trait. In order to detect genes in these traits we would like to simplify the complex interactions by eliminating the environment as a potential cause or concentrating on a particular population where the incidence appears to be much greater. In human populations we have no control over the environmental exposures and we cannot restrict their movements. For this reason many genetic studies have been conducted in mice. Many strains of mice have been generated. Their environment can be strictly controlled, enabling a much better identification of disease genes. Since mice and humans share much of their genome they also share many of their genes and are often afflicted by the same diseases. Thus if we identify genes in mice we have a very good chance of identifying the equivalent human genes. The completion of sequencing for the human genome is being closely followed by the completion of the mouse genome, precisely because mice have been used for over 100 years for genetic studies. The data generated from these sequencing efforts and prior genetic studies is now accumulating in vast databases. These databases of DNA information can be used to map genes for traits. The idea is to determine the trait measurement for many mice in different strains and compare these trait levels to the DNA state (genotype) of markers in the genome of the strains. If these are associated it indicates that the marker is situated close to a gene influencing the trait. This narrows the search considerably. Without this strategy we would have the daunting task of identifiying trait genes from many thousands of potential candidates.Read moreRead less
Statistical Methods for Next Generation Genome-Wide Association Studies. This project aims to develop cutting-edge statistical methods to analyse large genomic datasets and identify genetic variants associated with inter-individual differences in various human traits. Knowledge of trait-associated DNA variants is instrumental in understanding how natural selection has shaped human traits. By integrating genomic data from diverse and underrepresented populations, this project further expects to c ....Statistical Methods for Next Generation Genome-Wide Association Studies. This project aims to develop cutting-edge statistical methods to analyse large genomic datasets and identify genetic variants associated with inter-individual differences in various human traits. Knowledge of trait-associated DNA variants is instrumental in understanding how natural selection has shaped human traits. By integrating genomic data from diverse and underrepresented populations, this project further expects to contribute to the equitable use of genomic technologies in humans, regardless of geographical origins. Expected outcomes of this research include novel analysis methods and software tools, which should broadly and significantly benefit gene discovery in other species, including those of agricultural relevance.Read moreRead less