DrUlf Schmitz

Alternative splicing and the epigenome in Chronic Myeloid Leukaemia

In this project, we are investigating gene regulatory processes in leukaemia. The third biggest cause of cancer death in all Australians is blood cancers (leukaemia), which are diagnosed 35 times each day. Using a multi-omics approach, we examine alternative splicing and epigenetic changes blood samples from chronic myeloid leukaemia (CML) patients before and after treatment with tyrosine kinase inhibitors.

Find out more:Schmitz et al,bioRxiv2020

Cooperating microRNAs for cancer therapy

In this project, we use a systems medicine approach to find new avenues for overcoming chemotherapy resistance in aggressive tumour cells. Our results suggest that pairs of cooperating microRNAs could be used as potential RNA therapeutics to reduce E2F1-related chemoresistance.

Find out more:Lai X, Gupta SK, Schmitz U et al,Theranostics2018

Cross-talk between post-transcriptional gene regulation mechanisms

Combining computational predictions and in vitro assays we elucidate the cross-talk between post-transcriptional gene regulation mechanisms. More specifically, we focus in interactions between microRNA molecules and intron-retaining mRNA transcripts and try to identify networks of interconnected gene regulation. Using a systems biology approach we will model competitive post-transcriptional gene regulation through iterative cycles of time course experiments and model simulations.

Intron retention regulation in haematopoietic cells

There is growing evidence that alternative splicing, including IR, is regulated on at least two levels: locally, through a network of interacting trans-acting splicing regulators with cis-acting regulatory elements, and globally, through the chromatin structure. In this project, we explore a global regulation of IR in haematopoietic cells – we use statistical analysis to better understand IR regulation using information derived from the epigenetic factors that govern chromatin organisation, namely nucleosome assembly, DNA methylation and histone modifications. The main challenge here is to integrate multiple layers of ‘-omics’ into a single computational model which produces biologically interpretable results.

Find out more: Schmitz et al, Genome Biology 2017