UC Berkeley

The causal link between genotype and phenotype is one of the fundamental principles of modern biology; yet there remain significant challenges to successfully identifying and validating the effect of a specific genetic variant on an organism. Much of the tremendous diversity observed in nature, even among individuals of the same species, remains unexplained. Here, we used the model eukaryote, Saccharomyces cerevisiae, to investigate naturally occurring variation and employ a candidate gene approach, through a combination of genome sequence analysis and mining functional gene annotations, to identify genetic determinants of the phenotypes observed. First, we took a look at morphological variation, a major source of biological diversity, in an environmental isolate of S. cerevisiae and found that its allele of CDC28 underlies multiple phenotypes: linearly arranged spores after meiosis, elongated cell shape during mitosis, and branching filaments during filamentous growth. Second, we studied a wild yeast population, using a comparative transcriptomics approach, which revealed divergence in iron metabolism that exhibited itself as slow growth in a high iron environment. We again identified two of the genetic determinants, YAP5 and CCC1, both essential for resistance to iron toxicity, that contribute to the phenotype and show evidence that genes involved in iron homeostasis have undergone non-neutral evolution. Our work illustrates the viability of using genomic data to successfully predict the genes responsible for phenotypes of interest as well as the power of yeast a model system for investigating natural variation.