Exploring adaptation routes to cold temperatures in the Saccharomyces genus. - Javier Pinto; Laura Natalia Balarezo-Cisneros; Daniela Delneri (PLoS Genetics)
The identification of traits that affect adaptation of microbial species to external abiotic factors, such as temperature, is key for our understanding of how biodiversity originates and can be maintained in a constantly changing environment. The Saccharomyces genus, which includes eight species with different thermotolerant profiles, represent an ideal experimental platform to study the impact of adaptive alleles in different genetic backgrounds. Previous studies identified a group of adaptive genes for maintenance of growth at lower temperatures. Here, we carried out a genus-wide assessment of the role of genes partially responsible for cold-adaptation in all eight Saccharomyces species for six candidate genes. We showed that the cold tolerance trait of S. kudriavzevii and S. eubayanus is likely to have evolved from different routes, involving genes important for the conservation of redox-balance, and for the long-chain fatty acid metabolism, respectively. For several loci, temperature- and species-dependent epistasis was detected, underscoring the plasticity and complexity of the genetic interactions. The natural isolates of S. kudriavzevii, S. jurei and S. mikatae had a significantly higher expression of the genes involved in the redox balance compared to S. cerevisiae, suggesting a role at transcriptional level. To distinguish the effects of gene expression from allelic variation, we independently replaced either the promoters or the coding sequences (CDS) of two genes in four yeast species with those derived from S. kudriavzevii. Our data consistently showed a significant fitness improvement at cold temperatures in the strains carrying the S. kudriavzevii promoter, while growth was lower upon CDS swapping. These results suggest that transcriptional strength plays a bigger role in growth maintenance at cold temperatures over the CDS and supports a model of adaptation centred on stochastic tuning of the expression network.