Natural populations harbour complex levels of cellular regulation, which are usually directly or indirectly influenced by environmental factors. The variance of a trait in a population can therefore be explained by its underlying diverse interconnection of those regulation levels, which are based on the corresponding genetic background.
In an aim of discovering the genetic architecture and molecular mechanisms of complex traits, we use several approaches to associate phenotype with genotype. One way of casual linking the genotype to phenotype is in using the quantitative trait locus (QTL) analysis and its extensions.
Using such an analysis, accumulation of lipid storage in the common yeast S. cerevisiae has been determined as a quantitative, complex trait. Among proposed causative candidate genes, PIG1 had the highest QTL prediction power of the phenotype based on different loci of quantitative traits [1]. Its allelic polymorphic variance between the commonly used laboratory BY4741 strain and the AWRI1631 wine strain is higher than 2% and allows for altered interactome and its consequential divergent functionality.
In the scope of investigating the role of PIG1 in lipid metabolism, we aimed to complement its interaction profiles by determining new genetic and protein interaction partners, based on the allelic variant of the PIG1 gene. Thus, we wanted to analyse the importance of perturbation of the interactome, which depends on the underlying genetic background.
To determine genetic interactions, we performed a cell growth test in the presence of rapamycin. Two new interactions of the PIG1 were identified, namely a negative interaction with RML2 and a positive interaction with PHO23. We found that the combination of the AWRI1631 strain alleles in the BY4741 genetic background causes hybrid incompatibility with a yet unknown genetic factor.
The interactome divergence between studied stains was supported by a high-throughput variant of the yeast two-hybrid method. With this so-called barcode-fused yeast two-hybrid method we were able to identify new candidate protein interactors of Pig1 variants. With the follow-up classical approaches, we were only able to confirm the previously known protein interaction with Gsy2.
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