The Viennese Life Science Area contains one of the leading research clusters worldwide addressing signal transmission by the Janus kinases (JAKs) and signal transducers and activators of transcription (STATs). JAKs and STATs act downstream of more than 50 cytokine and growth factor receptors to shape the chromatin architecture and reprogram cellular function by changing gene expression. Applying advanced transgenic mouse models and comparative studies with human disorders has enabled the Consortium to contribute substantially to our understanding of the molecular mechanistic and disease related functions of JAKs and STATs.

The results from Vienna and elsewhere have led to the recognition of the JAK-STAT pathway as (i) one of the key pathways in the inflammatory responses and the defense against infection as well as (ii) one of the twelve core pathways in the initiation and progression of cancer, which are governed through (iii) increasingly complex molecular mechanisms along a canonical and non-canonical route.

We shall use JAK-STAT as a paradigm to identify key players (“monarchs”) and hierarchies that shape chromatin landscapes. We focus on immune or inflammatory cells and haematopoietic cancer cells, as paradigms for cells that rapidly adapt their transcription profiles or that have had their transcription profile perturbed by disease.

Within two broad categories we aim to answer the scientific questionshow STATs and/or JAKs contribute to the dynamic chromatin dynamics associated with: (i) physiological changes in NK cells, T helper (Th) cells and macrophages under developmental and disease conditions; (ii) tumourigenesis in myeloid versus lymphoid transformation and in various forms of haematopoietic cancers and (iii) non-canonical JAK or STAT activities under (patho-)physiological conditions.

The Epigenome of JAK-STAT

Recently molecular genetics research focused on global aspects of gene control and the underlying hierarchies. Our proposed projects aim to place the interactomes of JAKs and STATs into the emerging global chromatin landscape. Genome-wide analyses integrate the various layers of RNA, DNA and protein dynamics to pinpoint key regulators of pathways and pathway hierarchies that drive or prevent disease. We aim to determine the impact of JAKs and STATs on 3D genome architecture, landscapes of chromatin modifications, DNA methylation and transcription factor binding.

The wealth of genome-scale data that will be generated in the individual subprojects creates will be bundled in a consortium-wide integrative data analysis. This creates the opportunity for developing a comprehensive computational model of JAK-STAT signalling and the associated chromatin response. Building on the consortium’s track record of cohesion and collaboration, all NGS experiments are designed with data integration in mind. This prospective approach to data syndication and integrative analysis overcomes the many issues of ex post re-analysis of existing datasets that were not generated for integrative analysis.

The consortium expects to provide the following to the scientific community:

  • Hotspots of chromatin dynamics in response to JAK-STAT signalling during normal development and/or in disease. This map will comprise genomic regions that undergo changes induced by the germline and/or tissue-specific lack of STATs 1-6 and TYK2 in splenic macrophages and T cells. Derived from the individual projects the intersection of data sets derived from infection biology and cancer will shed light on common denominators and differences between cells employing JAK-STAT for the process of transformation vs. cells preparing to fight pathogens.
  • Database of JAK-STAT epigenomics as an important reference for the wider research community. To boost accessibility and re-use, we will generate a web-accessible database hosting the primary (raw and normalized data) and secondary results (genome regions, epigenome patterns across cell types and conditions) and link this to the web portal of the SFB.
  • Correlation of JAK-STAT dependent epigenome signals to large bodies of published epigenomic data (from ENCODE, Roadmap Epigenomics, BLUEPRINT, etc.) and computational modelling of the effects of JAK-STAT signalling on the epigenomic landscape.
  • Regulatory networks encoded in chromatin: Exploiting transcription factor footprints encoded in the chromatin accessibility data, we will use the Wellington algorithm and PIQ to infer and quantitate transcription factor footprints and regulatory networks involved in JAK-STAT-dependent regulation of chromatin.