Academic journal article Genetics

Oxidative Stress Survival in a Clinical Saccharomyces Cerevisiae Isolate Is Influenced by a Major Quantitative Trait Nucleotide

Academic journal article Genetics

Oxidative Stress Survival in a Clinical Saccharomyces Cerevisiae Isolate Is Influenced by a Major Quantitative Trait Nucleotide

Article excerpt

ABSTRACT

One of the major challenges in characterizing eukaryotic genetic diversity is the mapping of phenotypes that are the cumulative effect of multiple alleles. We have investigated tolerance of oxidative stress in the yeast Saccharomyces cerevisiae, a trait showing phenotypic variation in the population. Initial crosses identified that this is a quantitative trait. Microorganisms experience oxidative stress in many environments, including during infection of higher eukaryotes. Natural variation in oxidative stress tolerance is an important aspect of response to oxidative stress exerted by the human immune system and an important trait in microbial pathogens. A clinical isolate of the usually benign yeast S. cerevisiae was found to survive oxidative stress significantly better than the laboratory strain. We investigated the genetic basis of increased peroxide survival by crossing those strains, phenotyping 1500 segregants, and genotyping of high-survival segregants by hybridization of bulk and single segregant DNA to microarrays. This effort has led to the identification of an allele of the transcription factor Rds2 as contributing to stress response. Rds2 has not previously been associated with the survival of oxidative stress. The identification of its role in the oxidative stress response here is an example of a specific trait that appears to be beneficial to Saccharomyces cerevisiae when growing as a pathogen. Understanding the role of this fungal-specific transcription factor in pathogenicity will be important in deciphering how fungi infect and colonize the human host and could eventually lead to a novel drug target.

Continuous phenotypic variation is the norm rather than the exception for most eukaryotic traits. Unlike Mendelian traits that are governed by a single gene, quantitative traits are controlled by multiple genes, typically unlinked, described as quantitative trait loci (QTL) (Geldermann 1975). Locating these QTL and pinpointing the responsible genes (QTGs) and nucleotides (QTNs) are central challenges of genetics that are being pursued with sophisticated genotyping and mapping methods. Selective genotype data for progeny with one of the two extreme phenotypes have been found to be most informative (Lander and Botstein 1989). Individuals can be genotyped separately via single segregant analysis (SSA) or by pooling their genomic DNA and performing bulk segregant analysis (BSA) (Arnheim et al 1985; Michelmore et al. 1991; Quarrie et al. 1999). Once a QTL has been located in the genome, the next level of analysis is the identification of the responsible QTG and QTN, which are typically verified by the homologous replacement of the candidate gene or polymorphism between both parental strains using site-directed mutagenesis (Sinha et al 2008b).

Microbial QTL that modulate virulence are of particular scientific interest due to their impact on human health. Virulence-associated QTL have been identified in the parasites Toxoplasma gondii (Su et al 2002) and Trypanosoma brucei (Morrison et al. 2009) and the opportunistic pathogen S. cerevisiae (Steinmetz et al. 2002), which has rapidly become an exquisite model system for the study of quantitative genetics. Successfully mapped S. cerevisiae quantitative traits include sporulation efficiency (Deutschbauer and Davis 2005; Ben-Ari et al 2006), regulation of gene expression (Brem et al 2002), DNA damage repair (Demogines et al. 2008), cell morphology (Brauer et al. 2006), genetic changes in experimentally evolved populations (Segre et al. 2006), and ethanol tolerance (Hu et al. 2007).

The level of resolution to which S. cerevisiae quantitative traits have been mapped varies. Some traits, like resistance to small molecules and ethanol, have been mapped to the level of candidate QTL without independent marker verification for this region (Perlstein et al 2006; Hu et al. 2007). For others, such as sporulation efficiency (Deutschbauer and Davis 2005), high-temperature growth (Sinha et al 2008a), and DNA damage repair (Demogines et al 2008), the causative QTNs have been experimentally validated. …

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