One approach to understanding the genetic basis of traits is to study their pattern of inheritance among offspring of phenotypically different parents. Previously, such analysis has been limited by low mapping resolution, high labor costs, and large sample size requirements for detecting modest effects. Here, we present a novel approach to map trait loci using artificial selection. First, we generated populations of 10–100 million haploid and diploid segregants by crossing two budding yeast strains of different heat tolerance for up to 12 generations. We then subjected these large segregant pools to heat stress for up to 12 d, enriching for beneficial alleles. Finally, we sequenced total DNA from the pools before and during selection to measure the changes in parental allele frequency. We mapped 21 intervals with significant changes in genetic background in response to selection, which is several times more than found with traditional linkage methods. Nine of these regions contained two or fewer genes, yielding much higher resolution than previous genomic linkage studies. Multiple members of the RAS/cAMP signaling pathway were implicated, along with genes previously not annotated with heat stress response function. Surprisingly, at most selected loci, allele frequencies stopped changing before the end of the selection experiment, but alleles did not become fixed. Furthermore, we were able to detect the same set of trait loci in a population of diploid individuals with similar power and resolution, and observed primarily additive effects, similar to what is seen for complex trait genetics in other diploid organisms such as humans.

The question of how genetic variation in a population influences phenotypic variation and evolution is of major importance in modern biology. Yet much is still unknown about the relative functional importance of different forms of genome variation and how they are shaped by evolutionary processes. Here we address these questions by population level sequencing of 42 strains from the budding yeast Saccharomyces cerevisiae and its closest relative S. paradoxus. We find that genome content variation, in the form of presence or absence as well as copy number of genetic material, is higher within S. cerevisiae than within S. paradoxus, despite genetic distances as measured in single-nucleotide polymorphisms being vastly smaller within the former species. This genome content variation, as well as loss-of-function variation in the form of premature stop codons and frameshifting indels, is heavily enriched in the subtelomeres, strongly reinforcing the relevance of these regions to functional evolution. Genes affected by these likely functional forms of variation are enriched for functions mediating interaction with the external environment (sugar transport and metabolism, flocculation, metal transport, and metabolism). Our results and analyses provide a comprehensive view of genomic diversity in budding yeast and expose surprising and pronounced differences between the variation within S. cerevisiae and that within S. paradoxus. We also believe that the sequence data and de novo assemblies will constitute a useful resource for further evolutionary and population genomics studies.

A large fraction of human complex trait heritability is due to a high number of variants with small marginal effects and their interactions with genotype and environment. Such alleles are more easily studied in model organisms, where environment, genetic makeup, and allele frequencies can be controlled. Here, we examine the effect of natural genetic variation on heritable traits in a very large pool of baker's yeast from a multiparent 12th generation intercross. We selected four representative founder strains to produce the Saccharomyces Genome Resequencing Project (SGRP)-4X mapping population and sequenced 192 segregants to generate an accurate genetic map. Using these individuals, we mapped 25 loci linked to growth traits under heat stress, arsenite, and paraquat, the majority of which were best explained by a diverging phenotype caused by a single allele in one condition. By sequencing pooled DNA from millions of segregants grown under heat stress, we further identified 34 and 39 regions selected in haploid and diploid pools, respectively, with most of the selection against a single allele. While the most parsimonious model for the majority of loci mapped using either approach was the effect of an allele private to one founder, we could validate examples of pleiotropic effects and complex allelic series at a locus. SGRP-4X is a deeply characterized resource that provides a framework for powerful and high-resolution genetic analysis of yeast phenotypes and serves as a test bed for testing avenues to attack human complex traits.T HE strong tendency for progeny to closely resemble their parents has turned out to be difficult to understand in detail. Nearly all traits, including lifetime risk for many common diseases, have a complex genetic basis that is determined by multiple quantitative trait loci (QTL) (Donnelly 2008;Manolio et al. 2009). The first step toward accurate models of trait variability, and a prerequisite for predicting and modulating them, is characterization of the underlying genetic factors in the context of rest of the genome and their external environment. Research in model systems has led the way in this effort and produced powerful experimental and computational approaches for genetic mapping (Nordborg and Weigel 2008;Flint and Mackay 2009;Mackay et al. 2009).A traditional, well-controlled approach for finding the QTL underlying natural phenotypic variation is to analyze a large number of progenies from two-parent crosses (Brem et al. 2002;Simon et al. 2008). Studies using this design have improved our understanding of complex traits and provided concrete evidence of natural segregating variants ), but have been limited in their scope with regard to the extent of genetic variation between the two parents. Mapping populations of popular model organisms ranging from fruit flies (King et al. 2012) (Churchill et al. 2004;Durrant et al. 2011) to plants (Kover et al. 2009;Gan et al. 2011;Huang et al. 2011) has recently expanded the genetic and phenotypic diversity available to study by ...

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In somatic cells, recombination between the homologous chromosomes followed by equational segregation leads to loss of heterozygosity events (LOH), allowing the expression of recessive alleles and the production of novel allele combinations that are potentially beneficial upon Darwinian selection. However, inter-homolog recombination in somatic cells is rare, thus reducing potential genetic variation. Here, we explored the property of S. cerevisiae to enter the meiotic developmental program, induce meiotic Spo11-dependent double-strand breaks genome-wide and return to mitotic growth, a process known as Return To Growth (RTG). Whole genome sequencing of 36 RTG strains derived from the hybrid S288c/SK1 diploid strain demonstrates that the RTGs are bona fide diploids with mosaic recombined genome, derived from either parental origin. Individual RTG genome-wide genotypes are comprised of 5 to 87 homozygous regions due to the loss of heterozygous (LOH) events of various lengths, varying between a few nucleotides up to several hundred kilobases. Furthermore, we show that reiteration of the RTG process shows incremental increases of homozygosity. Phenotype/genotype analysis of the RTG strains for the auxotrophic and arsenate resistance traits validates the potential of this procedure of genome diversification to rapidly map complex traits loci (QTLs) in diploid strains without undergoing sexual reproduction.

Optogenetic switches permit accurate control of gene expression upon light stimulation. These synthetic switches have become a powerful tool for gene regulation, allowing modulation of customized phenotypes, overcoming the obstacles of chemical inducers, and replacing their use by an inexpensive resource: light. In this work, we implemented FUN-LOV, an optogenetic switch based on the photon-regulated interaction of WC-1 and VVD, two LOV (light-oxygen-voltage) blue-light photoreceptors from the fungus Neurospora crassa. When tested in yeast, FUN-LOV yields light-controlled gene expression with exquisite temporal resolution and a broad dynamic range of over 1,300-fold, as measured by a luciferase reporter. We also tested the FUN-LOV switch for heterologous protein expression in Saccharomyces cerevisiae, where Western blot analysis confirmed strong induction upon light stimulation, surpassing by 2.5 times the levels achieved with a classic GAL4/galactose chemical-inducible system. Additionally, we utilized FUN-LOV to control the ability of yeast cells to flocculate. Light-controlled expression of the flocculin-encoding gene FLO1, by the FUN-LOV switch, yielded flocculation in light (FIL), whereas the light-controlled expression of the corepressor TUP1 provided flocculation in darkness (FID). Altogether, the results reveal the potential of the FUN-LOV optogenetic switch to control two biotechnologically relevant phenotypes such as heterologous protein expression and flocculation, paving the road for the engineering of new yeast strains for industrial applications. Importantly, FUN-LOV’s ability to accurately manipulate gene expression, with a high temporal dynamic range, can be exploited in the analysis of diverse biological processes in various organisms.

Saccharomyces cerevisiae is the main microorganism responsible for wine alcoholic fermentation. The oenological phenotypes resulting from fermentation, such as the production of acetic acid, glycerol, and residual sugar concentration are regulated by multiple genes and vary quantitatively between different strain backgrounds. With the aim of identifying the quantitative trait loci (QTLs) that regulate oenological phenotypes, we performed linkage analysis using three crosses between highly diverged S. cerevisiae strains. Segregants from each cross were used as starter cultures for 20-day fermentations, in synthetic wine must, to simulate actual winemaking conditions. Linkage analysis on phenotypes of primary industrial importance resulted in the mapping of 18 QTLs. We tested 18 candidate genes, by reciprocal hemizygosity, for their contribution to the observed phenotypic variation, and validated five genes and the chromosome II right subtelomeric region. We observed that genes involved in mitochondrial metabolism, sugar transport, nitrogen metabolism, and the uncharacterized ORF YJR030W explained most of the phenotypic variation in oenological traits. Furthermore, we experimentally validated an exceptionally strong epistatic interaction resulting in high level of succinic acid between the Sake FLX1 allele and the Wine/European MDH2 allele. Overall, our work demonstrates the complex genetic basis underlying wine traits, including natural allelic variation, antagonistic linked QTLs and complex epistatic interactions between alleles from strains with different evolutionary histories.