Date(s) - 10/09/2018
11 h 30 min - 12 h 30 min
Catégories Pas de Catégories
Blood cells arise from a common set of hematopoietic stem cells that differentiate into more specific progenitors, ultimately leading to different functional lineages. This process relies on the activation and repression of different genes modules, controlled by transcription factors (TFs). Novel high-throughput technologies allow the characterisation of cell-specific regulatory elements by studying chromatin state and TFs binding sites, in conjunction with gene expression. Proper integration and analysis of these data enable the delineation of novel regulatory interactions, which can be modelled and analysed using formal methods, thereby fostering our understanding of the mechanisms controlling cell fate at a system level, and enabling the prediction of the effects of molecular perturbations in silico.
Combining public and novel data from molecular genetic experiments (qPCR, western blot, EMSA) or genome-wide assays (RNA-seq, ChIP-seq), we have assembled a comprehensive regulatory network encompassing the main transcription factors and signalling components involved in myeloid and lymphoid development. Using a multilevel logical framework, we built a dynamical model allowing us to simulate cells differentiation, commitment and reprogramming in silico.
To improve the accuracy of our model, we performed a meta-analysis of all available TF ChIP-seq datasets in myeloid and lymphoid cells, confirming previously known regulations or confirming new ones (26 confirmed and 66 predicted regulations). We then iteratively added some predicted regulations to our model, performed static or dynamical analysis (stables states analysis or differentiation/reprogramming simulations), and compared the results with data (phenotypes or gene expression). We therefore predicted several important, previously unknown regulations that we could confirmed experimentally.