Centre for Population and Disease Genomics

Decoding the Genome: Investigating how regions of the genome controlling cell identity in development and disease

Supervisor: Dr Nathan Palpant (n.palpant@uq.edu.au)

This project focuses on understanding how regions of the genome control cell identity and their connections with complex traits, development, disease, and drug responses. Utilizing cutting-edge computational methods, the project will study genomic regions responsible for influencing phenotype manifestations, including both complex traits and disease pathology. We aim to link this information to drug databases to develop a deeper understanding of how the genome responds to drugs in different diseases. Integrating applications to genome-wide association studies (GWAS) and multi-omic technologies, this research will not only contribute to the existing body of genetic knowledge but also help develop innovative methodologies that could impact approaches towards the diagnosis, prevention, and treatment of diseases.

Generation of micro organospheres for patient-derived drug screening assays

Influence of COVID-19 vaccinations on long-COVID symptoms

Investigating the genetic basis of left-handedness

Supervisor: Professor David Evans (d.evans1@uq.edu.au)

This project will involve latent class analysis of handedness, footedness and ocular dominance data in 10,000 children from the Avon Longitudinal Study of Parents and Children. The student will then investigate the genetic aetiology of these latent classes including how known variants for left handedness and ambidexterity relate to them.

Investigation of cell types found in patient-derived organoids

Large scale neuroimaging study of Alzheimers’ disease

Supervisors: Dr Baptiste Couvy-Duchesne (uqbcouvy@uq.edu.au)

This project will involve the analysis of a large neuroimaging cohort from the US, which contains more than 10,000 individuals imaged using MRI. Our lab develops statistical methods for the analysis of fine-grained brain images, which will be applied to analyse this cohort. The results will contribute to our current large-scale initiative that combines results from all continents, to create a high-resolution map of the brain regions associated with Alzheimer’s disease status and risk. The methods and software we use are shared with the field of genetics/genomics, meaning the student will acquire highly transferrable skills and knowledge. In addition, the dynamic environment of the program in complex trait genomics (PCTG), will support the student to to enrich theirknowledge in the fast-paced / rapidly-evolving field of neuroimaging and human genetics.

We encourage applicants with a scientific background, but most importantly with a strong inclination for problem solving and computational work. We recognise the richness of Indigenous cultures and the unique knowledge Aboriginal and Torres Strait Islander employees bring to our workplace. We welcome and encourage applications from Aboriginal and Torres Strait Islander people. We encourage applications from individuals with disabilities, culturally and linguistically diverse individuals, and individuals from the LGBTIQA+ community. If you have accessibility requirements, please note them in your application and we will endeavour to make any reasonable adjustments.

Mapping cell decisions over time: building tools to track genome-wide changes controlling stepwise decisions of differentiating cells

Supervisor: Dr Nathan Palpant (n.palpant@uq.edu.au)

This project utilizes computational genetic prediction algorithms to build tools that can monitor genome-wide alterations governing the sequential choices made by differentiating cells. By employing single-cell data to analyze cell differentiation, the project seeks to provide granular insights into the complex mechanisms that guide cellular transformations. The implications of this research will help reveal the genetics underpinning development, congenital diseases, and organ morphogenesis. Furthermore, the study will help identify novel methods to control cell differentiation, potentially establishing new strategies in cellular manipulation and offering significant contributions to both developmental biology and medical science.

Navigating the genetic landscape of neurodegenerative disease: Evaluating Variant Prioritisation Tools for Precision Medicine

Supervisor: Dr Fleur Garton (f.garton@imb.uq.edu.au)

Amyotrophic Lateral Sclerosis is a fatal neurodegenerative condition with a complex genetic architecture. Whole genome and exome sequencing supports the identification of both common and rare variants contributing to disease. Rare variants in known ALS genes have often not been seen before and are labelled as variants of uncertain significance. As more samples are analysed this number becomes larger and prioritising the variants to follow-up is necessary. In-silico prediction tools exist for this purpose. They use empirical data to predict their likelihood to be deleterious but their sensitivity for ALS has not yet been explored.

The project will test the sensitivity known pathogenic ALS and benign ALS variants across a range of in-silico tools. We hypothesise that certain tools have better sensitivity at detecting pathogenicity, and these are the tools that the community should be used to prioritise variants of unknown significance.

This is a computational project that will require you to understand human genome nomenclature. It will involve variant annotation and analysis. You will be involved in comparing tools using a range of software tools and packages with analyses performed in R. You will use a variety of statistical methods to make conclusions. This may reveal future opportunities for variant interpretation (i.e. critical assessment of proposed oligogenic genetic architecture) and/or sensitivity testing for other conditions.

Within the dynamic environment of the program in complex trait genomics (PCTG), you will be supported and encouraged to enrich your knowledge in the fast-paced / rapidly-evolving field of human genetics.