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      Genetic Dissection of Ethanol Tolerance in the Budding Yeast Saccharomyces cerevisiae

      , , , , , , ,
      Genetics
      Genetics Society of America

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          Abstract

          Uncovering genetic control of variation in ethanol tolerance in natural populations of yeast Saccharomyces cerevisiae is essential for understanding the evolution of fermentation, the dominant lifestyle of the species, and for improving efficiency of selection for strains with high ethanol tolerance, a character of great economic value for the brewing and biofuel industries. To date, as many as 251 genes have been predicted to be involved in influencing this character. Candidacy of these genes was determined from a tested phenotypic effect following gene knockout, from an induced change in gene function under an ethanol stress condition, or by mutagenesis. This article represents the first genomics approach for dissecting genetic variation in ethanol tolerance between two yeast strains with a highly divergent trait phenotype. We developed a simple but reliable experimental protocol for scoring the phenotype and a set of STR/SNP markers evenly covering the whole genome. We created a mapping population comprising 319 segregants from crossing the parental strains. On the basis of the data sets, we find that the tolerance trait has a high heritability and that additive genetic variance dominates genetic variation of the trait. Segregation at five QTL detected has explained approximately 50% of phenotypic variation; in particular, the major QTL mapped on yeast chromosome 9 has accounted for a quarter of the phenotypic variation. We integrated the QTL analysis with the predicted candidacy of ethanol resistance genes and found that only a few of these candidates fall in the QTL regions.

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          Most cited references30

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          Searching for genetic determinants in the new millennium.

          N Risch (2000)
          Human genetics is now at a critical juncture. The molecular methods used successfully to identify the genes underlying rare mendelian syndromes are failing to find the numerous genes causing more common, familial, non-mendelian diseases. With the human genome sequence nearing completion, new opportunities are being presented for unravelling the complex genetic basis of non-mendelian disorders based on large-scale genome-wide studies. Considerable debate has arisen regarding the best approach to take. In this review I discuss these issues, together with suggestions for optimal post-genome strategies.
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            Dissecting the architecture of a quantitative trait locus in yeast.

            Most phenotypic diversity in natural populations is characterized by differences in degree rather than in kind. Identification of the actual genes underlying these quantitative traits has proved difficult. As a result, little is known about their genetic architecture. The failures are thought to be due to the different contributions of many underlying genes to the phenotype and the ability of different combinations of genes and environmental factors to produce similar phenotypes. This study combined genome-wide mapping and a new genetic technique named reciprocal-hemizygosity analysis to achieve the complete dissection of a quantitative trait locus (QTL) in Saccharomyces cerevisiae. A QTL architecture was uncovered that was more complex than expected. Functional linkages both in cis and in trans were found between three tightly linked quantitative trait genes that are neither necessary nor sufficient in isolation. This arrangement of alleles explains heterosis (hybrid vigour), the increased fitness of the heterozygote compared with homozygotes. It also demonstrates a deficiency in current approaches to QTL dissection with implications extending to traits in other organisms, including human genetic diseases.
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              Finding genes that underlie complex traits.

              Phenotypic variation among organisms is central to evolutionary adaptations underlying natural and artificial selection, and also determines individual susceptibility to common diseases. These types of complex traits pose special challenges for genetic analysis because of gene-gene and gene-environment interactions, genetic heterogeneity, low penetrance, and limited statistical power. Emerging genome resources and technologies are enabling systematic identification of genes underlying these complex traits. We propose standards for proof of gene discovery in complex traits and evaluate the nature of the genes identified to date. These proof-of-concept studies demonstrate the insights that can be expected from the accelerating pace of gene discovery in this field.
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                Author and article information

                Journal
                Genetics
                Genetics
                Genetics Society of America
                0016-6731
                1943-2631
                March 23 2007
                March 2007
                March 2007
                December 28 2006
                : 175
                : 3
                : 1479-1487
                Article
                10.1534/genetics.106.065292
                1840089
                17194785
                08574f80-d49d-4293-b662-18dcbf48b25b
                © 2006
                History

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