Definition of a genetic network involved in congenital heart disease.
Coordinator: Antonio BALDINI
Project Number: 223463
EC contribution: € 2,680,000.00
Project website: http://www.cardiogenet.eu/
This application focuses on transcriptional networks that govern the development of a heart region commonly affected by congenital heart disease (CHD). The major goal is to provide the clinical and basic science research communities with a validated list of interconnected genes required for normal heart development. To achieve this goal, we have recruited 6 European groups of scientists strongly committed to CHD research. The participants bring to the consortium significant resources and credible synergy. The entry point for the interrogation and perturbation of cardiogenic gene networks will be the transcription factor Tbx1, the major gene for 22q11.2 deletion syndrome, a common genetic cause of CHD. The project has three specific aims:
- To define the roles and interactions of T-box transcription factors in cardiac outflow tract (OFT) development. Our hypothesis is that a critical balance of Tbx1, 2, and 3 is required to regulate homeostasis of a specific population of cardiac progenitors and their interactions with non-cardiogenic cells.
- To define gene networks perturbed in OFT developmental defects. Innovative approaches will identify the transcriptional targets and protein interactors of Tbx1. Candidate genes will be validated in vitro and in vivo using mouse and zebrafish models. In addition, we will perform extensive transcriptome analyses using biopsy material from CHD patients in order to integrate animal and patient data.
- To integrate gene expression, cell lineage distribution and phenotype data. Normal heart morphology is achieved through a concerted gene expression program and the integration of molecular signals and tissue interactions.
Aided by 3-dimensional reconstruction of gene expression patterns and phenotypic information, we will integrate different types of data to develop models of CHD pathogenesis. Teamwork will be enhanced by shared technologies that provide homogeneity and comparability of data between the participating labs.