Abstract

Transcriptomes are the most basic functional output of the genome and sequencing technologies have allowed us to explore transcriptomes in great detail. However this detail has been underutilised using traditional analysis methods. We can use transcriptomes to get information not only about expression levels but also about the structure of transcripts. We also now have the capability to measure transcriptomes in single cells within tissues.

In this talk I will cover topics on identifying the complexity in cancer transcriptomes and single-cell RNA-seq analysis. In particular, I will show how we can use cancer transcriptomes to discover clinically relevant structural variants including fusion genes and more complex events. In addition I will show the utility of using RNA-seq as a fist line genomic assay in pediatric acute lymphoblastic leukemia. I will also show how we have been analysing scRNA-seq data with application to exploring the composition and variability of kidney organoids in comparison to fetal kidney tissue and mouse fetal kidneys.

About the Speaker

Alicia Oshlack has been at the forefront of bioinformatics research for more than 15 years. She has recently started a new role as the (co)Head of the Computational Biology Program at the Peter MacCallum Cancer Centre after leading the Bioinformatics group at the Murdoch Children’s Research Institute for more than 8 years. She is best known for her large body of work on transcriptional analysis. In addition, Oshlack is internationally recognised for her development of bioinformatics methods for a range of applications including single cell RNA-seq, methylation and genomic analysis. Oshlack is involved in many cutting edge collaborative projects related to disease and development. She has published more than 90 papers and developed more than a dozen software packages. Oshlack has been recognised by several awards including the Australian Academy of Science, Gani Medal for Human Genetics (2011) and the Georgina Sweet Award for Women in Quantitative Biomedical research (2016).