Gianni LitiInstitut de recherche sur le cancer et le vieillissement, Nice (IRCAN) - CNRS / Inserm / Université de Nice Sophia Antipolis
Mes recherches
I studied biology and obtained my PhD in 2000 from the University of Perugia (Italy). In 2001, I moved to the UK (first to Leicester then to Nottingham) and worked on genome evolution, population genomics and telomere biology using the budding yeasts, S. cerevisiae and other closely related species, as model organisms. In 2011, I moved to Nice (France) as CNRS researcher where I established the ATIP-Avenir team “Population genomics and complex traits”. Our research focuses on evolutionary and quantitative genomics. My team uses genetics and genomics to understand the evolutionary processes that shape natural variation at the population level. Current focus includes the characterization of the pangenome of multiple bacterial and yeast species. Our studies aim to investigate the origins and fate of accessory genes, their functional implications and how the species pangenome is shaped by interactions with human and environment. Over the years, our research has been cross-disciplinary and collaborative.
Mon projet ATIP-Avenir
Understanding the genetic mechanisms underlying quantitative traits
Most human traits, including many diseases, are regulated by multiple interacting quantitative trait loci (QTLs). Although human association studies have already identified hundreds of common risk variants, they fail to explain much of the heritability and we are unable to make predictions from the genetic and environmental interactions characterised thus far. Dissecting the genetic mechanisms underlying this phenotypic variation is a major challenge. This is due to the complex genetic architecture with many loci contributing to phenotypic effects, low penetrance, gene-gene, and gene-environment interactions.
In order to advance our understanding of complex traits there is a need for a suitable genetic system that can be used in high-throughput studies. I propose to use the budding yeast, Saccharomyces cerevisiae, to dissect the genetic architecture of multiple medically relevant complex traits and to determine how they vary across natural populations. The objectives are relevant for human health in two ways: the first consists of modelling complex traits in a simple eukaryotic genetic system; the second aims to dissect medically relevant traits.