We pursue two complementary research pillars — basic science uncovering fundamental mechanisms of gene regulation, and translational research addressing neuropsychiatric and medical conditions of major public health importance.
MicroRNAs are ~22-nucleotide non-coding RNAs that post-transcriptionally regulate gene expression by binding target mRNAs. Our lab develops computational miRNA target prediction pipelines, identifies disease-relevant miRNA–target interactions, and validates them experimentally. We have characterised miRNA networks in neuronal development, cancer immunology, and social insect biology. Key tools include miR-ISH for subcellular localisation and custom prediction algorithms integrated with CLIP-seq and degradome data.
Circular RNAs are covalently closed RNA molecules with emerging roles as miRNA sponges, protein scaffolds, and translation templates. We apply computational approaches to identify circRNAs in neurological disease datasets — including RNA-seq from Alzheimer's disease and schizophrenia patient samples — and investigate their functional significance. Our work includes ORF analysis of circRNAs for putative peptide-coding capacity and their interaction networks with miRNAs in disease-relevant brain regions.
We build and analyse protein–protein interaction (PPI) networks, transcription factor networks, and co-expression networks to understand how genes function collectively in health and disease. Using graph-theoretic approaches, community detection, and permutation-based statistics, we identify convergent disease pathways and network hubs dysregulated across neuropsychiatric conditions. Our network models have demonstrated that neurodevelopmental and neuropsychiatric disorders represent an interconnected molecular system rather than discrete disease entities.
We develop pipelines for integrating genomics, transcriptomics, epigenomics, and proteomics data to achieve a comprehensive picture of molecular dysregulation in disease. Our approaches include GWAS-eQTL co-localisation, regulatory element annotation (cCREs, JASPAR TF binding sites), DNA methylation analysis across cell types, and whole transcriptome analysis. We leverage patient-derived olfactory neurosphere-derived cells and iPSCs as accessible, disease-relevant models for multi-omics profiling.
Schizophrenia affects ~1% of the global population and has a substantial genetic component. We integrate GWAS risk loci with regulatory genomics to identify functional mechanisms — including transcription factor binding disruption, non-coding variant effects, and miRNA-mediated regulation — that translate genetic risk into molecular pathology. We use patient-derived olfactory neurosphere cells (OE-SCs) as a discovery platform for biomarker identification and drug screening. Our NHMRC MRFF-funded programme directly employs patient-derived stem cells for drug discovery.
We investigate molecular mechanisms contributing to Alzheimer's disease, with a focus on neuroinflammation, microglial dysfunction, and non-coding RNA dysregulation. Our NHMRC Ideas Grant programme examines PILRB as a mediator of microglial phagocytic failure — a key event in Alzheimer's pathology. We also use patient-derived olfactory stem cell models (in collaboration with Prof. Alan Mackay-Sim and Prof. Andrew White) to identify transcriptomic signatures associated with cognitive decline, providing accessible cellular models for biomarker discovery.
Rare genetic diseases are individually uncommon but collectively affect millions, and represent major unmet therapeutic needs. Our collaboration with the "Genetic Cures for Kids" initiative focuses on Spastic Paraplegia type 52 (SPG52), using olfactory stem cells derived from affected patients to model the disease and screen candidate compounds. This patient-derived cellular approach allows direct interrogation of disease-relevant gene networks and therapeutic target identification without requiring invasive tissue sampling or animal models.
We investigate molecular mechanisms in haematological malignancies and cancer immunotherapy. Our work revealed that EBV-encoded miRNA BHRF1-2-5p targets immune-checkpoint ligands PD-L1 and PD-L2 in EBV-associated lymphoma — a key finding for understanding viral immune evasion and checkpoint therapy response. Additional programmes include development of off-the-shelf NK cell immunotherapy for paediatric blood cancers, miRNA-based biomarkers for Diffuse Large B-cell Lymphoma treatment response, and a phase 2 clinical trial (TREBL-2) for EBV-associated lymphomas.
Custom pipelines for miRNA target prediction, circRNA detection, GWAS-regulatory element integration, network analysis, and multi-omics data integration. HPC-deployed workflows.
Olfactory neurosphere-derived cells (OE-SCs), induced pluripotent stem cells (iPSCs), primary NK cells, and patient-derived lymphoma samples as disease-relevant experimental systems.
Whole genome and transcriptome sequencing, small RNA-seq, ATAC-seq, DNA methylation arrays, and single-cell approaches applied to patient-derived and model system samples.
Biomarker discovery and validation in clinical cohorts, circulating miRNA profiling (liquid biopsy), drug screening in patient-derived models, and participation in multicentre clinical trials.