Research

The Zaugg group investigates the variation of molecular phenotypes among individuals with the aim of better understanding the molecular basis of complex diseases and inter-individual differences in drug response. Another focus is to understand interactions between different cell types in the context of gene regulatory mechanisms in a disease setting.

Previous and current research

The vast majority of genetic variants associated with complex traits lies in the non-coding part of the genome, it is thus likely that gene regulatory processes play an important role in biological mechanisms that are underlying complex traits and diseases. Our vision is to (i) understand how genetic and epigenetic variation across individuals affects complex traits and diseases through gene regulatory mechanisms and (ii) to make use of the variation in molecular phenotypes to better understand biological processes and disease mechanisms. On the technical side, this involves the development of computational tools to integrate data across multiple scales and types. Examples of these tools include diffTF, to estimate differential TF activity based on chromatin and gene regulatory networks, which we have recently applied to understand the epigenetic mechanisms of pulmonary arterial hypertension.

Our early findings suggest a genetic basis of chromatin states, challenging the traditional view of chromatin being an epigenetic mark. Interestingly, there is a dramatic discrepancy in variability among individuals between enhancer elements (most variable) and gene expression (least variable). We further found that regulatory elements that are variable among individuals are enriched for SNPs that have previously been found to associate with complex traits or diseases, highlighting the functional significance of studying inter-individual variation of molecular phenotypes. Currently, we are using variation across individuals to investigate gene regulatory mechanisms such as, chromatin loops in splicing, cooperative transcription factor binding, and global changes in transcription factor activity, which we are typically interpreting within the context of cell-type specific gene regulatory networks, to understand the complex relationship between gene expression, regulatory elements, and downstream complex phenotypes.

Future projects and goals

In the future we will expand our efforts to contributing to the understanding of complex traits and diseases along three lines of research:

  • We will apply our multiomics data integration methods  – in particularly our approach to devise gene regulatory networks – to understand basic and applied biological questions, focusing on (i) neuronal development and processes related to neurodegenerative diseases and (ii) the hematopoietic niche and diseases related to the misregulation of the immune system.
  • We will expand our data integration methods to include more downstream molecular phenotypes, such as protein levels and complex composition, cooperative TF binding prediction, to estimate the impact of genetic variation on biological pathway activity.
  • We will use co-culture experiments and single cell technologies to understand the impact of microenvironment (in cancer and neurodegenerative diseases) and cell-cell interactions on gene regulatory networks and chromatin
  • We are exploiting variation across individuals to derive cell-type specific gene regulatory networks that we then use to understand molecular and regulatory mechanism underlying complex traits