Summer Research Program - IMB

Supervisors: Dr Harriet Lo (h.lo@imb.uq.edu.au); Dr Melanie Oey (m.oey@uq.edu.au)

Algae produce O2 and take up CO2, both needed and produced by muscle cells. In this project the participant will test the effect of algae on the growth and differentiation of muscle cells in co-culture as a test of the utility of algae to promote ‘green’ meat production.

Expected outcomes: The student will have the opportunity to gain experience the culture of algae and mammalian cells in a wet-lab setting. The project will provide experience with imaging and assays for muscle formation.

Suitability: This project is suitable for a student with a background in biology, 3^rd or 4^th  year students only, ideally with some experience in aseptic techniques.

Supervisors: Dr Kathryn Kemper (k.kemper@imb.uq.edu.au); A/Prof Loic Yengo (l.yengo@imb.uq.edu.au)

To date, the majority of human genetics studies have been conducted in individuals of European ancestry, although European ancestry only constitutes 16% of the global population. Therefore, there is a real need to improve our understanding of the genetic determinants of human traits in individuals with non-European ancestries, and also in people with mixed ancestry backgrounds. This project aims to describe and classify the genomes of a cohort of about 2000 individuals from the UK with self-reported ‘mixed’ ancestry. There are two main tasks are to be completed using publicly available programs such as STRUCTURE (Pritchard et al. 2001 Genetics 155(2):945). The tasks are to: 1. Describe and define the genomic ancestry profile of ‘mixed’ ancestry individuals. 2. Assign genomic regions of ‘mixed’ ancestry individuals to the ancestries identified in (1) . Students will gain skills in the analysis of human genomic data, and working in a HPC environment. Students will be required to comply with human ethics requirements. The project will conclude with a brief report to project supervisors and a presentation to the group. The project is suitable for students wanting to gain experience in computational biology and genome analysis. It is open to any students with an interest in the topic. Helpful background knowledge may include genetics and/or statistics. The student will be part of the PCTG (https://cnsgenomics.com/), within the Institute for Molecular Bioscience at the St Lucia campus. The PCTG is a group of around 40 researchers and PhD students. The student will have opportunity to attend seminars and other activities within the PTCG.

Supervisor: Dr Fleur Garton (f.garton@uq.edu.au) please contact Dr Garton before submitting an application

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. 

Aim: This 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.  

Approach: This is a computational project requiring variant annotation and analysis. You will be involved in comparing each of these 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 design and/or sensitivity testing for other conditions.  

Expected outcomes: As part of the Centre for Population Genetics and Disease Genomics at IMB, students will be exposed to a variety of research projects and discussions. This project is geared to gaining skills in genetic variant analysis and interpretation. This has not been done before and so there is opportunity to contribute to a publication from this work. Students may also be asked to produce a report and present at the end of their project. 

Suitability: This project is only open to applications from students trained in statistical genetics, bioinformatics and/or related fields.  

Supervisor: Dr Johannes Zuegg (j.zuegg@uq.edu.au)

The Community for Open Antimicrobial Drug Discovery (CO-ADD) is maintaining a web-based information system, build on open-source web-framework (django), database (postgresql), and analysis (python) modules. The project is to enhance the existing system with a repository, analysis and visualisation of bacterial and fungal whole genome data collected by CO-ADD and from external sources, together with bioinformatic analysis and visualisation

Required background/skills

Computer Science, Coding (python, html, sql), Database modelling, some Bioinformatic.

Supervisors: Dr Huy Hoang (h.hoang@imb.uq.edu.au); Dr Jeffrey Mak (j.mak@imb.uq.edu.au); Professor David Fairlie (d.fairlie@imb.uq.edu.au)

The histone deacetylase HDAC7 is an emerging anti-inflammatory drug target, but there remains a lack of selective inhibitors. The student will use molecular docking and molecular dynamics simulations to study the structural basis of the selectivity of our best-in-class HDAC7 inhibitors, and then design new HDAC7 compounds in silico.

Supervisor: Dr Michael Healy (m.healy@imb.uq.edu.au)

The Commander complex is a conserved regulator of intracellular trafficking. This ancient complex consists of 15 core components as well as a number of associated proteins that can be subdivided into three (3) categories: the COMMD/Coiled coil domain containing proteins, the Retriever complex (a distant relative of the Retromer complex) and a number of associated proteins. Functionally Commander couples to Sorting Nexin 17 (SNX17) to facilitate the recycling of over 100 cell surface proteins including key receptors such as, LDLR, LRP1, p-Selectin and the amyloid precursor protein. In addition, Commander dysfunction has been linked to various disease pathologies including X-linked intellectual disability. It is therefore crucial to understand the structure, mechanism and function of this complex, an understanding that has remain largely elusive to date. 

The specific aim of this project is to act in a complementary fashion to a larger project. The aims of larger project are to resolve a high resolution structure of the 16 subunit Commander complex, both by single particle analysis of the isolated complex and analysis of the structure of the complex in-vivo using correlative light electron microscopy. However, before we can achieve this we will need to characterise a set of molecular tools generated during my PhD, this will be the focus of the proposed project. 

Aim 1: Resolve a high-resolution crystal structure of the N-terminal domain of Commd7 bound to Nanobody D12

Nanobodies are small, soluble, high affinity molecules, that can be used in a wide array of tasks including, in cell imaging, and complex purification. In previous unpublished work done in collaboration with A/Prof. Wai-Hong Tham (WEHI ) a high affinity nanobody was developed against a stable tetrameric subset of the Commd proteins (Commd-5-7-9-10). After some initial mapping experiments by ITC this nanobody (Nb D12) was found to bind selectively to the helical n-terminal domain of Commd7. However, the exact binding site/orientation of this molecule is unknown. Given this has the potential to disrupt the structure of the overall complex it is critical that we gain a better understanding of this interaction before proceeding to use this Nb to isolate the 16 subunit Commander complex. While various biochemical and cellular techniques will be performed in tandem the gold standard for assessing this interaction will be to obtain a high-resolution structure of Nb D12 bound to the HN domain of Commd7.

Aim 2: Map the binding site of several macrocyclic peptides and resolve a high-resolution structure. 
Likewise in Aim 2 we will endeavour to better understand the interaction between a semi-stable hexamer (Commd1-2-3-4-6-8) and a series of macrocyclic peptides that were developed in collaboration with Dr. Toby Passioura (University of Sydney). Currently this project is less developed and so initial experiments will focus on mapping the interaction site to a particular Commd or interface with a subsequent goal been to produce a high resolution crystal structure. 

Supervisor: Dr Jeffrey Mak (j.mak@uq.edu.au)

Background: Histone deacetylases (HDACs) are enzymes that hydrolyse acetyl groups from the lysine sidechains from histones. They are the targets of a number of known anti-cancer drugs, while some sub-classes of HDACs are emerging as promising drug targets for treating inflammatory diseases. 

Gap: Most HDAC drugs have many deleterious side effects as they are not very selective for their protein targets. There is a need to discover new compound that can confer greater selectivity. 

Approach: The research student will convert known HDAC drug SAHA into new inhibitors that exploit the enzyme’s catalytic mechanism. To our knowledge, this has not been studied before. 

Aim: Synthesise a series of SAHA derivatives to demonstrate a conceptually new way to inhibit HDACs 

Expected outcomes: 

The student will: 

1. experience conducting research in a dynamic and multidisciplinary research laboratory 

2. gain valuable skills in conducting organic synthesis, including advanced reaction techniques and compound characterisation 

3. gain exposure in the design of biologically-active molecules and appropriate synthetic routes 

4. contribute to publications, depending on project outcomes 

The students will be expected to: 

1. contribute to the synthesis of new analogues 

2. give a short oral presentation, depending on project results

Suitability: This project is for enthusiastic organic chemistry students who have completed 2nd year, and aim to study (or have already studied) CHEM3001. 

Supervisor: A/Prof Nathan Palpant (n.palpant@uq.edu.au)

The ability to study complex data is important in current project design due to routine high dimensional data generated by sequencing and imaging methods. This project will make use of new computational methods we have developed (see Mizikovsky et al, Nucleic Acids Research, 2022). The goal is to understand and compare data outputs of this and related methods as computational frameworks for determining relationships of objects based on large-scale phenotypic data.

Expected outcomes: The applicants will gain experience working with emerging computational pipelines involving dimensionality reduction and visualisation of complex data. The project will aim to evaluate a set of diverse and pre-selected data types using our established computational methods. We will then use these data to interpret performance accuracy against a reference ground truth. 

Suitability: The work requires applicants with strong computational bioinformatics skills suitable for 3rd-4th year students.

Supervisor: Dr Nicole Lawrence (n.lawrence@imb.uq.edu.au)

Host defence peptides can selectively recognise and kill pathogens, while leaving healthy cells unharmed. We are developing new peptide-based medicines for treating malaria that are safe and selective, and also are less likely to result in malaria parasites developing drug resistance. Design and validation of new drug candidates requires pre-screening for desirable characteristics prior to testing for antimalarial activity using in vitro assays and eventually animal studies. 

The research scholar will contribute to producing and validating some of the next generation of antimalarial peptides. 

Supervisor: Dr Daniel Hwang (d.hwang@uq.edu.au)

Eating fruits and vegetables that are rich in nutrients has been link to a positive health status. The proverb "An apple a day keeps the doctor away" suggests eating apples is beneficial for health promotion and disease prevention. This project will apply rigorous statistical methodologies to investigate the causal relationship between apple consumption and multiple health factors in large-scale genetically informative datasets. The outcome will provide scientific evidence to support or against the proverb.

Expected outcomes and deliverables: Scholars will have an opportunity to work in a research group, gain skills in data analysis and generate a publication from their research. 

Suitable for: The student should be familiar with the software R and have knowledge of human genetics and statistics.  

Supervisor: Dr Quan Nguyen (quan.nguyen@imb.uq.edu.au)

Duration: 10 weeks Description: The brain is such a complex organ that each of the many brain regions controls a distinct set of cognitive functions. Understanding of the variations between these regions at cell and gene levels is lacking. Recent genome-wide association studies (GWAS) of brain MRI images from large biobanks and consortia for >50,000 people have suggested hundreds of genes contributing to differences in areas of cortical brain regions. This opens an unprecedented opportunity to link genetic data to changes in brain morphologies across individuals in time (lifespan) and space (brain regions). However, activities of GWAS genes in each cell type in these MRI-defined regions are largely unknown. Further, little understanding exists on the roles of non-neuronal cells in the brain, i.e., glia, which make up more than half of all brain cells. Throughout life, glial cells maintain the wellbeing of neurons and are key for healthy brain aging but are also involved in various brain disorders like stroke, epilepsy, and Alzheimer’s diseases. This project aim at investigating how genetic variants associated with brain regions manifest their effects differently across genes and cells in space (brain regions) and time (young vs aged). Cutting-edge data are readily available for the student to analyse cell types and compare differences between young and old brain samples.

Expected outcomes and deliverables: Students would learn skills in big biological data analysis. There are opportunities for presenting at conferences and co-authored publications.

Suitable for: This project is open to applications from students with good analytical skills. Familiarity to R and/or Python scripting is required.

Supervisor: A/Prof Frederic Gachon (f.gachon@imb.uq.edu.au)

The circadian clock orchestrates virtually all aspects of physiology so that organisms may better anticipate predictable daily changes caused by the Earth’s rotation. Consequently, disruption of circadian rhythms, or chronodisruption, is associated with several pathological or psychological conditions. Nevertheless, most research has focussed on nocturnal rodents, with little information on diurnal animals. This project proposes to study the impact of chronodisruption on the physiology of a diurnal animal: the common Australian zebra finch (Taeniopygia guttata). In collaboration with Prof. Kate Buchanan (Deakin University), we will study the impact of light and circadian rhythms on the embryonic development of the zebra finch, opening new perspective about the impact of the environment on the development of birds.

Supervisor: Dr Zyta Ziora (z.ziora@imb.uq.edu.au)

Growing industrialization and various other human activities have led to the reducing of clean water resources. The ever-increasing demand for hygienic water has prompted the development of technologies that can be used for treating polluted water. Many water-borne diseases are a result of blooming microbial populations in water. Over the years, conventional methods for water purification that prevent microbial growth, such as chlorination, ozonation etc., have limitations owing to the formation of disinfection by-products which are carcinogenic in nature. It is therefore vital to develop effective and low-cost technologies that address the problem. Hypothesis: Various silver products can be applied and use as an antimicrobial agent to improve the water quality. Aim: To identify an effective concentration of silver ion solutions against common microbes in wastewater. Approach: A model consisting of artificial sweat mixture liquid and sterile water will be used for sampling of three common wastewater bacteria, P. aeruginosa, E. coli, and S. aureus, fungi Candida Albicans, and biofilms. Samples will be collected immediately after the addition of silver, and 2, 4, and 24 hours afterwards. This study will demonstrate the practical use of silver ions as potential disinfection agents in managing water quality.

Expected outcomes and deliverables: The applicant is expected to produce a report and give an oral presentation. There is a possibility to continue this research as a PhD study in the joint project with the industry. The generated results from this research can be included in the planned publication in the reputable peer review journal.

Suitable for: This project is open to applications from students with a background in chemistry, inorganic chemistry, and microbiology, 3-4-year students.

Supervisor: Dr Melanie Oey (m.oey@uq.edu.au)

IVF is an emotionally and physically challenging journey and the success rates are accordingly important. We will use Zebrafish as model organism to evaluate whether IVF success rates can be improved using photosynthetically active microalgae.

Required background/skills

We are looking for third year students with a background and an interest in cell and molecular biology. Basic laboratory experience in cell and molecular biology required.

Supervisor: Dr Daniel Hwang (d.hwang@uq.edu.au)

Disturbed sensory perception is commonly observed among individuals with mental health issues, such as Parkinson's disease, schizophrenia, and bipolar disorder. This winter research project will be a follow-up study of our recent discovery of a novel association between the supertaster gene and bipolar disorder. The student will investigate the role of taste and olfactory receptor genes in mental disorders using a range of online platforms and existing tools.

Required background/skills

A background in statistics, nutrition, genetics, epidemiology, or medicine is preferred. Expertise in computer languages (e.g. R) is an add-up. 

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

Handedness refers to the preferential use of one hand over the other. Conversely, ambidexterity refers to the ability to perform the same action equally well with both hands. Hand preference is first observed during gestation as embryos begin to exhibit single arm movements. The prevalence of left-handedness in modern western cultures is approximately 9% and is greater in males than females. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we recently conducted the world’s largest genetic study of handedness in over 1.7 million individuals (Cuellar-Partida et al 2020). We found 41 genetic loci associated with left-handedness and 7 associated with ambidexterity (P < 5 × 10−8). We would now like to take this work forward and use this resource to investigate possible causal relationships between handedness and a variety of life outcomes including mortality and common complex diseases using a statistical genetics technique called Mendelian randomization.

Expected outcomes and deliverables: Scholars will have an opportunity to work in a research group, gain skills in data analysis and generate a publication from their research. 

Suitable for: The student should be familiar with the software R and have knowledge of human genetics and statistics. 

Supervisor: Dr Sally Mortlock (s.mortlock@imb.uq.edu.au)

Endometriosis is a debilitating gynaecological disorder affecting 11% of women of reproductive age in Australia. Endometriosis occurs when tissue similar to that of the endometrium is present outside its usual location in the uterus. The disease is associated with menstrual pain, chronic pelvic pain and reduced fertility. The endometriosis research group at IMB are part of world class research on the genetics and genomics of endometriosis alongside national and international collaborators. Our goal is to increase understanding of the genetic and functional pathways of endometriosis risk and pathogenesis. A total of 49 independent genetic risk loci have been associated with endometriosis including loci implicating genes involved in oestrogen responsiveness, cellular adhesion and sex steroid hormone signalling and function. Our goal now is to comprehensively review the evidence for target genes at these risk loci to better understand the disease biology. 

Approach: Review current scientific literature for evidence of the role of target genes in health and disease. Summarise molecular evidence for target genes from online databases including GTEx, OpenTargets, UniProt and EpiMap. Characterise the expression of target genes in endometrial tissue and cell types using locally available and publicly available RNA-seq and single-cell RNA-seq datasets. 

Required background/skills

This project is open to applications from students with a basic background in molecular biology and/or genetics. Any experience in statistical computing software (eg. R) and bioinformatics would also be beneficial.

Supervisor: Dr Daisy Crick (uqdcrick@uq.edu.au)

Handedness or hand preference is one of the most overt forms of lateralization seen in humans. It is linked to differences in the susceptibility to psychopathy and even with certain personality traits. Research has identified that there is a genetic influence on handedness, however most of the variation appears to come from environmental factors. For example, low birthweight and being part of a multiple birth, both appear to increase the susceptibility to being left-handed. However, as with many studies, these associations may be confounded. For example, low birthweight and being part of a multiple birth are also associated with a difficult birth experience and the infant’s poor health immediately after birth. 

This study aims to disentangle this relationship. We will look at associations between the infant’s health at birth and hand preference. We will use both classic epidemiological and genetic methodology to help infer the causality of this relationship. 

Required background/skills

The student should be familiar with the software R and have some knowledge of genetics and statistics. 

Supervisor: Dr Zeinab Khalil (z.khalil@uq.edu.au)

Microbes have been a new promising source of modern medicines, including antibiotics (e.g. penicillin) and immunosuppressants (e.g. sirolimus) and well as agents to treat cancer (e.g. adriamycin) and cardiovascular (e.g. statins) disease, as well as many more. Recent advances in genomics offer the prospect of exciting new approaches to discovering the next generation of medicines hidden within the Australian microbiome.

To this end in 2020 we launched Soils for Science (S4S) as an Australia wide citizen science initiative, designed to engage the public, to collect 10's of thousands of soil samples from backyards across the nation, from which we will isolate 100's thousands of unique Australian microbes. 

This project will annotate the S4S microbe library to prioritize those that are genetically and chemically unique. These will be subjected to cultivation profiling, and fermentation, followed by chemical analysis to isolate, identify and evaluate new classes of chemical diversity. 

The successful candidate will join a multi-disciplinary team where, supported by microbiological and genomic sciences, they will gain skills and experience in analytical, spectroscopic and medicinal chemistry – to inform and inspire the discovery of future medicines.

Applicants must have a strong background with outstanding grades in organic chemistry, and with an interest in learning multidisciplinary biosciences. 

Supervisor: Dr Melanie Oey (m.oey@uq.edu.au)

In Australia light exposure is often considered a danger. We want to explore light effect on animal and plant cells to improve photosynthetic oxygen production with the end-goal of developing medical therapies and alternative food production systems.

Required background/skills

Third year students with background and an interest in cell and molecular biology.

Supervisor: Dr Melanie Oey (m.oey@uq.edu.au)

Stroke is the second leading cause of death world wide. We aim to recombinantly produce stroke medication in microalgae.

Required background/skills

Third year students with background and an interest in cell and molecular biology.

Supervisor: A/Prof Frederic Gachon (f.gachon@imb.uq.edu.au)

While most of blood proteins are secreted by the liver, how they are secreted is still not clear, as well as the regulation of this secretion. Our previous experiments showed that liver protein secretion is rhythmic and regulated by feeding rhythms in both mouse and human. Using newly generated animal model and experiments in cultured cells, this project will decipher the mechanisms involved and the consequences of the perturbation of this rhythmic secretion on animal physiology.

Supervisor: Dr Nchafatso Obonyo (g.obonyo@uq.edu.au)

To characterise resuscitation-associated endothelial injury in a novel ovine septic shock model.

Required background/skills

Basic statistics.

Supervisor: Dr Zeinab Khalil (z.khalil@uq.edu.au)

Microbes have been a new promising source of modern medicines, including antibiotics (e.g. penicillin) and immunosuppressants (e.g. sirolimus) as well as agents to treat cancer (e.g. adriamycin) and cardiovascular (e.g. statins) disease, as well as many more. Recent advances in genomics offer exciting new approaches to discovering the next generation of medicines hidden within the Australian microbiome. 

To this end, in 2020, we launched Soils for Science (S4S) as an Australia broad citizen science initiative designed to engage the public to collect 10's of thousands of soil samples from backyards across the nation, from which we will isolate 100's thousands of unique Australian microbes.  

Hypothesis: Knowledge of microbial metabolites would lead to molecular tools that could be used to access new metabolites with therapeutic potential. 

Aims: This project will include the following; 

(1) analysing the soil microbiome by growing microbes in different media. (2) culturing/photographing communities of microbes.  

(3) isolating/cryopreserving pure microbes.  

(4) uploading images to the S4S Image gallery.  

(5) extracting the pure microbial isolates for chemical analysis to prioritise those genetically and chemically unique. 

Expected outcomes: The successful candidate will join a multi-disciplinary team where, supported by microbiological and genomic sciences, they will gain skills and experience in microbiology, analytical and medicinal chemistry – to inform and inspire the discovery of future medicines. The successful candidate will be asked to produce a report and/or oral presentation at the end of the project to highlight the outcomes.

Suitability: This project is open to applications from students with a background in organic chemistry and/or microbiology or 3rd – 4th year students only, and with an interest in learning multidisciplinary biosciences.

Supervisors: Dr Evans Cheruiyot (e.cheruiyot@imb.uq.edu.au); Prof Allan McRae (a.mcrae@imb.uq.edu.au)

The commonly used threshold for genome-wide association studies (GWAS) in humans is 5 x 10-8. This was developed based on samples sizes and marker densities available in the early days of GWAS. We now work with much larger samples sizes and use denser SNP marker panels covering a wider minor allele frequency range. This project will use 
simulation to assess appropriate statistical thresholds for analysis in the UK Biobank, a large-scale biomedical resource containing genetic and health information from half a million people.

Expected outcomes: The student will gain significant hand-on knowledge in: 
     1. Genome-wide association studies 
     2. Handling large complex datasets 
     3. Using high-throughput computing and Linux

Suitability: The project is particularly suitable for honours/master students who are interested in pursuing career research in the biological sciences (e.g., bioinformatics and genetics) 

Supervisors: Dr Timothy Hill (t.hill@imb.uq.edu.au), Dr Jeffrey Mak (j.mak@imb.uq.edu.au); Professor David Fairlie (d.fairlie@imb.uq.edu.au)

PROTACs are compounds that use specialised motifs to mediate target protein degradation, but the linkage points (exit vectors) for such motifs require strategic positioning. In this project, the student will synthesise new PROTACs with state-of-the-art exit vectors towards new anti-inflammatory drugs.

Supervisors: Dr Harriet Lo (h.lo@uq.edu.au); Mr James Rae (j.rae@imb.uq.edu.au)

Tardigrades are one of the toughest creatures on earth. In this project we will study the cellular adaptations that allow tardigrades to survive in extreme conditions.  

Expected outcomes: The student will learn how to study tardigrades using state-of-the-art microscopy techniques. Practically they will learn wet laboratory skills including hands on experience in tardigrade culture and techniques for imaging. 

Suitability: This project is suited to applications with a background in cell and molecular biology (3rd or 4th year) who are interested in undertaking postgraduate studies in their future education (Honours, Masters, PhD).

Supervisor: Dr Alesha Hatton (a.hatton@uq.edu.au)

Genome-wide association studies measure the degree of association between genetic variants and observed traits and provide insights into the genetic basis of complex traits and disease. However, observed variables are often imperfect measurements of underlying biological mechanisms. A latent variable is one that is not directly measured but is inferred from other observed variables. We can study the genetic basis of such latent variables using a technique called genomic structural equation modelling (genomic SEM). The intrauterine environment is a prime candidate to study using this approach and has been implicated in fetal growth restriction and an increased future risk of disease. 

Aim: This project will investigate indicators that capture different elements of the intrauterine environment using genomic SEM in order to better understand favourable fetal growth.

The student will gain hands-on knowledge in genome-wide association studies, genomic structural equation modelling, handling large complex datasets, using high throughput computing and linux.

Required background/skills

This will be a computational project. The student should be familiar with the software R (or similar and willing to learn), and have knowledge of statistics and/or genetics. 

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

The gold standard for demonstrating causal relationships in the epidemiological sciences is the randomized controlled trial. However, these sorts of studies are not always possible due to practical and/or ethical considerations. Nevertheless, in some cases data from genetically related individuals can be used to inform causality in non-experimental (observational) data. The aim of this project is to implement a statistical model we have devised that is capable of distinguishing causal relationships from correlational ones using data from genetically related individuals in non-experimental situations. The successful applicant will use a technique called “structural equation modelling” to construct the model and then test its performance using a mixture of simulated and real genome-wide data from twins/sibling pairs. 

Expected outcomes: Scholars will learn structural equation modelling, data simulation and statistical power analysis. The deliverable will be an R script that implements the model and tests its utility in simulated data. 

Suitability: This project is open to 2nd and 3rd year students who have a statistics major, experience with the R statistics package and/or previous experience in structural equation modelling. The candidate will need to demonstrate outstanding grades in statistics related courses. 

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

This project aims to investigate whether this phenomenon may be occurring in other MND risk loci. The UNC13A splicing event has been shown to occur due to mislocalisation of TDP-43 (an important regulator of RNA-splicing). UNC13A is not the only gene targeted by TDP-43 and we know of at least one other gene in a MND genetic risk locus, that may also be affected by TDP-43 mislocalisation. 
 
By leveraging off these recent discoveries in the field, this project aims to further explore cryptic exon splicing as a mechanism of MND. Computational integration of genetic and transcript data will be required. It will involve the use of in-house (human muscle) and publicly available (human iPSC- derived motor neurons) transcriptome data (RNA-seq) to look for evidence of cryptic splicing events in MND cases and controls. 
 
The overall aim of this project is to identify genetic links with the molecular mechanisms associated with MND. The long-term goal of this research is to use this detailed understanding of genetic risk of MND to help define novel therapeutic avenues. 

Expected outcomes: Applicants can expect to gain experience and knowledge in QC and processing of transcriptomic (RNA-seq) data, together with genetic data. Students may also be asked to produce a report or oral presentation at the end of their project.

Suitable for: This project is open to applications from students with a strong interest in molecular genetics, genetic and genomics, year 3 undergraduate and postgraduate students.

Other important details: Interested students must contact the supervisor/s, prior to submitting an application. Evidence of supervisor support is required to be uploaded as part of the application process. Students are also welcome to contact the supervisor if they are
interested in a related project area.

Supervisor: Dr Johannes Zuegg (j.zuegg@uq.edu.au)

The Community for Open Antimicrobial Drug Discovery (CO-ADD) is maintaining a web-based information system, build on open-source web-framework (django), database (postgresql), and analysis (python) modules. The project is to enhance the existing system with a repository, analysis and visualisation of chemical information, both from data generated within CO-ADD as well as data from external sources (like ChEMBL).

Required background/skills

Computer Science, Coding (python, django, html, sql), Database modelling, some Chemoinformatic.