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.
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.