The complexity by which genotypes modulate phenotypic variation has been a major obstacle in understanding the basis of inter-individual differences. In the particular case of disease susceptibility, enormous efforts have been conducted among large consortia of quantitative geneticists, and a recent wealth of results showed both victories and frustrations. Victories because many genetic factors could successfully be linked to diabetes, heart failure, cancer, infectivity, and many other common diseases. Frustrations as it is becoming more and more apparent that genetic dissections are far from completion, with many unsolved questions especially regarding gene x environment interactions and incomplete penetrance. In this context, I propose to revisit the molecular basis of phenotypic diversity by addressing fundamental questions in a simple and powerful model organism: the yeast S. cerevisiae.Combining experimental biology and bioinformatics into a ‘systems’ approach, I propose 1) To reconsider our current view of genetic determinism. By examining the effect of genetic variation on single-cells, we will visualise how they shape probability laws underlying phenotypic outcomes. This will prepare us to the upcoming era of generalized single-cell analysis. 2) To investigate how chromatin epigenotypes affect phenotypic variations. We will characterize nucleosomal epi-polymorphisms and study their impact on transcriptional and phenotypic responses to environmental changes. This will establish whether and how individual epigenomes should be considered when planning trait dissections.This ambitious project is grounded on solid preliminary results and can be achieved thanks to my dual expertise in numerical science and experimental genetics. The questions addressed are fundamental for our understanding of living systems and the innovative methodology will help us integrate upcoming technologies into the construction of personalized medicine.