TAXi-ch SIGNED
Determination of transcription factor cooperativity driving expression from the inactive X chromosome
Total Cost €
0EC-Contrib. €
0Partnership
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0TAXi-ch project word cloud
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Project "TAXi-ch" data sheet
The following table provides information about the project.
| Coordinator |
EUROPEAN MOLECULAR BIOLOGY LABORATORY
Organization address contact info |
| Coordinator Country | Germany [DE] |
| Total cost | 162˙806 € |
| EC max contribution | 162˙806 € (100%) |
| Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
| Code Call | H2020-MSCA-IF-2019 |
| Funding Scheme | MSCA-IF-EF-ST |
| Starting year | 2020 |
| Duration (year-month-day) | from 2020-03-01 to 2022-02-28 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | EUROPEAN MOLECULAR BIOLOGY LABORATORY | DE (HEIDELBERG) | coordinator | 162˙806.00 |
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Project objective
Transcription factor (TF) cooperativity controls gene expression and is essential to establish transcriptional programs during development. One of the hallmarks of development in female mammals is the inactivation of one of the two X chromosomes to achieve dosage compensation of X-linked genes. Although the inactive X (Xi) chromosome is a heterochromatin environment, a small fraction of genes is expressed from this chromosome. However, the exact mechanisms regulating their expression and the possible similarities in regulation between these genes and genes from the active X chromosome are unknown. TAXi-ch aims to determine the TFs driving the expression of genes from the Xi chromosome, as well as, the contribution of each TF to this process and their cooperativity. Specifically, an interdisciplinary approach based on functional genomics techniques, machine learning algorithms and genome editing tools will be applied to: 1) predict TFs that bind regulatory regions in the X chromosomes and generate their binding profiles, 2) assess the contribution of TFs to gene expression through classification models and targeted depletion of TFs, 3) infer regulatory networks of X-linked genes in the Xi chromosome, 4) model the transcriptional effect of abolishing binding of different combinations of TFs using 2 selected networks, and 5) experimentally validate the modelling predictions. The research is innovative, as this question has not previously been addressed using integration of allele-specific multi-omics data, and timely, considering the current interest to understand TF cooperativity. Furthermore, the results of this project will be important to the study of X-linked disorders. The dual expertise on data analysis and molecular biology of the experienced researcher ensures the feasibility of the project, and its implementation will hone her technical and transferable skills to facilitate her future establishment as an independent leader in the European Research Area.
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