Drew Neavin

Bipolar Genetics: Population-scale brain organoids for bipolar disorder and drug response

Although 70-90% of the chance of developing bipolar disorder is inherited, characterising the molecular mechanisms driving disease development and response to therapies has been challenging. This project will leverage induced pluripotent stem cell-derived mini brain organoids exposed to different bipolar therapies to identify genetic variations that alter therapeutic response.

This PhD project includes working with the Neavin stem cell wet lab team to design and carry out large-scale stem cell experiments before capturing with single-cell technologies and analysis of the single-cell data. As a result, the successful candidate will gain critical cross-training in wet lab techniques and computational analyses making them highly sought after for future positions. Being located in teh Centre for Population and Disease Genomics will provide a rigorous statistical environment to support additional learning and skills development

Stem cell villages for population-scale stem cell modelling

Population genomics work have identified thousands of genomic regions associated with human traits. However, it's been challenging to link these genetic regions to genes since >90% of these associated regions are outside of genes suggesting they impact gene expression but making it challenging to identify the specific gene impacting the trai. In addition, genetic regions do not regulate gene expression the same way in all cell types meaning that the relevant cell type is important to understanding the impact of these genetic regions on different human traits.

The Neavin Group uses stem cell models differentiated into specific cell types across hundreds of donors to identify variants that impact gene expression to link genetic regions to specific genes regulating gene expression to link them to human traits. However, stem cell culture is expensive and time-consuming so we and others have developed 'village-in-a-dish' approaches that co-culture stem cell lines from different individuals in one dish to scale stem cell models without increasing cost. While effective, there are still limitations with these models that can be optimised.

This project will build on the village system to develop approaches to make these co-culture approaches more robust and reveal line-specific characteristics that result in cell culture dominance. The successful PhD candidate will learn stem cell culture techniques and work with the Neavin wet lab team to carry out stem cell village experiments. This project also includes analysis of the resulting data providing the PhD student with a diverse skillset across wet lab and dry lab approaches.

Revealing the impact of biological variables on molecular phenotypes

Genetic effects are shaped by biological context, including ancestry, sex, cellular state, and environmental exposure. To assess this at scale, we leverage single-cell data from >100 million cells and >10k individuals to understand how genetic effects are altered.

This PhD project builds on previous work Drew did understanding the diversity of single-cell atlases and the impact on biological signals. This PhD student will process publicly available data using an established pipeline and combine and anlyse the results giving the student a strong foundation in large-scale analyses, single-cell analysis and statistical genetics.

Diverse pharmacogenomic functional validation

Multiple genes are known to have a large impact on response to therapies, known as pharmacogenomics, with >99% of individuals estimated to have a drug altering genetic allele. Most pharmacogenomic studies have been carried out in European ancestries but these genes are known to be highly polymorphic across populations so characterisation of genetic alleles in non-European populations is critical.

This PhD project is part of a large collaborative project across Australia to characterise novel pharmacogenomic allele function using stem cell-derived ccells. This PhD student will work with other researchers in the network to identify likely-impactful variants and test them with stem cell models. This PhD student will gain a strong basis in stem cell modelling and have the opportunity to work as part of a large collaborative network.