DMR-CODE
Decoding the Mammalian transcriptional Regulatory code in development and stimulatory responses
| Coordinatore | WEIZMANN INSTITUTE OF SCIENCE
Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie. |
| Nazionalità Coordinatore | Israel [IL] |
| Totale costo | 1˙500˙000 € |
| EC contributo | 1˙500˙000 € |
| Programma | FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | ERC-2012-StG_20111109 |
| Funding Scheme | ERC-SG |
| Anno di inizio | 2012 |
| Periodo (anno-mese-giorno) | 2012-10-01 - 2017-09-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
WEIZMANN INSTITUTE OF SCIENCE
Organization address
address: HERZL STREET 234 contact info |
IL (REHOVOT) | hostInstitution | 1˙500˙000.00 |
| 2 |
WEIZMANN INSTITUTE OF SCIENCE
Organization address
address: HERZL STREET 234 contact info |
IL (REHOVOT) | hostInstitution | 1˙500˙000.00 |
Mappa
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Obiettivo del progetto (Objective)
'Transcription factors (TF) regulate genome function by controlling gene expression. Comprehensive characterization of the in vivo binding of TF to the DNA in relevant primary models is a critical step towards a global understanding of the human genome. Recent advances in high-throughput genomic technologies provide an extraordinary opportunity to develop and apply systematic approaches to learn the underline principles and mechanisms of mammalian transcriptional networks. The premise of this proposal is that a tractable set of rules govern how cells commit to a specific cell type or respond to the environment, and that these rules are coded in regulatory elements in the genome. Currently our understanding of the mammalian regulatory code is hampered by the difficulty of directly measuring in vivo binding of large numbers of TFs to DNA across multiple primary cell types and their natural response to physiological stimuli.
Here, we overcome this bottleneck by systematically exploring the genomic binding network of 1. All relevant TFs of key hematopoietic cells in both steady state and under relevant stimuli. 2. Follow the changes in TF networks as cells differentiate 3. Use these models to engineer cell states and responses. To achieve these goals, we developed a new method for automated high throughput ChIP coupled to sequencing (HT-ChIP-Seq). We used this method to measure binding of 40 TFs in 4 time points following stimulation of dendritic cells with pathogen components. We find that TFs vary substantially in their binding dynamics, genomic localization, number of binding events, and degree of interaction with other TFs. The analysis of this data suggests that the TF network is hierarchically organized, and composed of different types of TFs, cell differentiation factors, factors that prime for gene induction, and factors that bind more specifically and dynamically. This proposal revisits and challenges the current understanding of the mammalian regulatory code.'