The molecular process that leads to multiple mRNA transcripts being produced from the same segment of DNA (aka gene) is known as alternative splicing (AS). This is a common form of regulation in higher eukaryotes, enabling the production of novel protein isoforms, which in turn are known to have a big impact on phenotype. Understanding the regulatory factors involved in AS, including epigenetic mechanisms such as DNA methylation, will offer key insights into important biological phenomena. Traditionally, AS and the detection of protein isoforms has been difficult to study due to limitations in short-read DNA sequencing technology and data-dependent proteomics workflows. Making use of recent technological advancements in the fields of Next Generation Sequencing (NGS) and Proteomics, our lab has developed a technique called DIA-Seq, which helps to address many of these issues. This project will utilise and improve upon the current DIA-Seq pipeline to study the role that epigenetic processes play in the regulation of AS and protein isoform abundance, using animal models of disease and behaviour. It is anticipated that work carried out in this project will have widespread applications across many biological disciplines.
The largest component of this project will be the utilisation of existing bioinfomatics software to improve current NGS and proteomics analysis pipelines. The development of novel bioinformatics tools may also be necessary if suitable software is deemed to be lacking. In addition, a small amount of new data may need to be generated, primarily for reproducibility and validation purposes. If so, this will involve wet-lab activities such as the preparation of tissue samples for long-read genomic sequencing and mass spectrometry-based proteomics data acquisition.
Most of the data required to successfully carry out the project will be provided. The expected outcome of this work is therefore to analyse these data in an integrated (multi-omic) manner. This will likely include machine learning and the development of new analytical software/bioinformatics pipelines. In addition, to enable data reproducibility and pipeline inter-usability, use of workflow management tools such as Common Workflow Language (CWL), as well as containerization software such as Docker, will be key components of the work. All these outcomes should lead to publications in high-ranking scientific journals.
A sound understanding of the general principles of Molecular Biology are necessary. Bioinformatics skills are essential. Laboratory-based experience is preferable, although not critical. To be competitive for a University scholarship, it is expected that applicants will be able to demonstrate high academic achievement, and ideally, will have at least one scientific publication in a related discipline.