Please use this identifier to cite or link to this item:http://hdl.handle.net/20.500.12105/12435
Deciphering regulatory elements as determinants of cardiovascular diseases
The non-coding genome harbors cis-regulatory elements (CRE) that control gene expression in time and space. A tight control of transcription is of great importance, especially during development, and CRE disruption may lead to malformations and other congenital diseases. Genome-wide association studies (GWAS) have identified common polymorphisms associated to multifactorial disorders in humans such as cardiovascular diseases. The vast majority of these associations lay in non-coding regions. Whether these thousands of risk loci affect CREs and have a functional role in the context of disease is unknown. Cardiovascular diseases (CVDs) are common human diseases with the highest prevalence and death rate worldwide. To date, GWAS have linked hundreds of loci to a higher risk of developing two major CVD: Atrial Fibrillation (AF) and Atherosclerosis. CVDs are not an exception and for most risk loci we lack mechanistic insights into the nature of GWAS associations. Although enhancer-reporter assays (ERAs) are a powerful tool to characterize risk-associated enhancers, these experiments are time-consuming and the throughput is very limited. This is in stark contrast with the outgrowing number of new polymorphisms associated to human diseases. In this thesis, we optimized current mouse ERA technology to achieve ~59% efficiency of transgenesis, thus enabling the scaleup of CRE discovery. We systematically interrogated a dozen risk loci strongly associated to AF in the search for disease-risk enhancers. Interestingly, we showed that the PB-ERA system that we developed is able to identify negative regulators such as silencers or insulators. Together with 3D chromatin analysis and CRISPR-mediated perturbations, we identified the targets of AF-CREs and involved new genes in arrhythmia susceptibility. Furthermore, we integrated transcriptomic data from an ovine model of AF chronification. We found that GWAS and chronification data converge on the TBX5-GJA1 axis and identified AF-enhancers regulating the cardiac expression of both genes. These enhancers are controlled by TBX5 itself in what might be a key feedback-loop for atrial remodeling. Last but not least, we applied our approach to a second CVD to validate it as an effective framework to understand the genetic contribution to human diseases. We interrogated the locus of the pro-atherosclerotic gene PCSK9 and describe a dual regulation for this gene in liver and cerebellum.
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