Although microorganisms are traditionally used to investigate unicellular processes, the yeast Saccharomyces cerevisiae has the ability to form colonies with highly complex, multicellular structures. Colonies with the "fluffy" morphology have properties reminiscent of bacterial biofilms and are easily distinguished from the "smooth" colonies typically formed by laboratory strains. We have identified strains that are able to reversibly toggle between the fluffy and smooth colony-forming states. Using a combination of flow cytometry and high-throughput restriction-site associated DNA tag sequencing, we show that this switch is correlated with a change in chromosomal copy number. Furthermore, the gain of a single chromosome is sufficient to switch a strain from the fluffy to the smooth state, and its subsequent loss to revert the strain back to the fluffy state. Because copy number imbalance of six of the 16 S. cerevisiae chromosomes and even a single gene can modulate the switch, our results support the hypothesis that the state switch is produced by dosage-sensitive genes, rather than a general response to altered DNA content. These findings add a complex, multicellular phenotype to the list of molecular and cellular traits known to be altered by aneuploidy and suggest that chromosome missegregation can provide a quick, heritable, and reversible mechanism by which organisms can toggle between phenotypes. colony morphology | copy number variation | phenotypic switching | bet-hedging

SUMMARY Modern transportation networks have facilitated the migration and mingling of previously isolated populations of plants, animals, and insects. Human activities can also influence the global distribution of microorganisms. The best understood example is yeasts associated with winemaking. Humans began making wine in the Middle East over 9,000 years ago [1, 2]. Selecting favorable fermentation products created specialized strains of Saccharomyces cerevisiae [3, 4] that were transported along with the grapevines. Today, S. cerevisiae strains residing in vineyards around the world are genetically similar, and their population structure suggests a common origin that followed the path of human migration [3–7]. Like wine, coffee and cacao depend on microbial fermentation [8, 9] and have been globally dispersed by humans. Theobroma cacao originated in the Amazon and Orinoco Basins of Colombia and Venezuela [10], was cultivated in Central America by the Mesoamerican peoples, and introduced to Europeans by Cortés in 1530 [11]. Coffea, native to Ethiopia, was disseminated by Arab traders throughout the Middle East and North Africa in the 6th century and was introduced to European consumers in the 17th century [12]. Here, we test whether the yeasts associated with coffee and cacao are genetically similar, crop-specific populations or genetically diverse, geography-specific populations. Our results uncovered populations that, while defined by niche and geography, also bear signatures of admixture between major populations in events independent of the transport of the plants. Thus, human-associated fermentations and migration may have affected the distribution of yeast involved in the production of coffee and chocolate.

Systems-level genetic studies in humans and model systems increasingly involve both high-resolution genotyping and multi-dimensional quantitative phenotyping. We present a novel method to infer and interpret genetic interactions that exploits the complementary information in multiple phenotypes. We applied this approach to a population of yeast strains with randomly assorted perturbations of five genes involved in mating. We quantified pheromone response at the molecular level and overall mating efficiency. These phenotypes were jointly analyzed to derive a network of genetic interactions that mapped mating-pathway relationships. To determine the distinct biological processes driving the phenotypic complementarity, we analyzed patterns of gene expression to find that the pheromone response phenotype is specific to cellular fusion, whereas mating efficiency was a combined measure of cellular fusion, cell cycle arrest, and modifications in cellular metabolism. We applied our novel method to global gene expression patterns to derive an expression-specific interaction network and demonstrate applicability to global transcript data. Our approach provides a basis for interpretation of genetic interactions and the generation of specific hypotheses from populations assayed for multiple phenotypes.

Aneuploidy, a state in which the chromosome number deviates from a multiple of the haploid count, significantly impacts human health. The phenotypic consequences of aneuploidy are believed to arise from gene expression changes associated with the altered copy number of genes on the aneuploid chromosomes. To dissect the mechanisms underlying altered gene expression in aneuploids, we used RNA-seq to measure transcript abundance in colonies of the haploid Saccharomyces cerevisiae strain F45 and two aneuploid derivatives harboring disomies of chromosomes XV and XVI. F45 colonies display complex “fluffy” morphologies, while the disomic colonies are smooth, resembling laboratory strains. Our two disomes displayed similar transcriptional profiles, a phenomenon not driven by their shared smooth colony morphology nor simply by their karyotype. Surprisingly, the environmental stress response (ESR) was induced in F45, relative to the two disomes. We also identified genes whose expression reflected a nonlinear interaction between the copy number of a transcriptional regulatory gene on chromosome XVI, DIG1, and the copy number of other chromosome XVI genes. DIG1 and the remaining chromosome XVI genes also demonstrated distinct contributions to the effect of the chromosome XVI disome on ESR gene expression. Expression changes in aneuploids appear to reflect a mixture of effects shared between different aneuploidies and effects unique to perturbing the copy number of particular chromosomes, including nonlinear copy number interactions between genes. The balance between these two phenomena is likely to be genotype- and environment-specific.