Single QTL mapping and nucleotide-level resolution of a physiologic trait in wine Saccharomyces cerevisiae strains

Abstract Natural Saccharomyces cerevisiae yeast strains exhibit very large genotypic and phenotypic diversity. However, the link between phenotype variation and genetic determinism is still difficult to identify, especially in wild populations. Using genome hybridization on DNA microarrays, it is no...

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Published inFEMS yeast research Vol. 7; no. 6; pp. 941 - 952
Main Authors Marullo, Philippe, Aigle, Michel, Bely, Marina, Masneuf-Pomarède, Isabelle, Durrens, Pascal, Dubourdieu, Denis, Yvert, Gaël
Format Journal Article
LanguageEnglish
Published Oxford, UK Blackwell Publishing Ltd 01.09.2007
Oxford University Press
Oxford University Press (OUP)
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Summary:Abstract Natural Saccharomyces cerevisiae yeast strains exhibit very large genotypic and phenotypic diversity. However, the link between phenotype variation and genetic determinism is still difficult to identify, especially in wild populations. Using genome hybridization on DNA microarrays, it is now possible to identify single-feature polymorphisms among divergent yeast strains. This tool offers the possibility of applying quantitative genetics to wild yeast strains. In this instance, we studied the genetic basis for variations in acetic acid production using progeny derived from two strains from grape must isolates. The trait was quantified during alcoholic fermentation of the two strains and 108 segregants derived from their crossing. A genetic map of 2212 markers was generated using oligonucleotide microarrays, and a major quantitative trait locus (QTL) was mapped with high significance. Further investigations showed that this QTL was due to a nonsynonymous single-nucleotide polymorphism that targeted the catalytic core of asparaginase type I (ASP1) and abolished its activity. This QTL was only effective when asparagine was used as a major nitrogen source. Our results link nitrogen assimilation and CO2 production rate to acetic acid production, as well as, on a broader scale, illustrating the specific problem of quantitative genetics when working with nonlaboratory microorganisms.
Bibliography:Editor: Monique Bolotin‐Fukuhara
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ISSN:1567-1356
1567-1364
DOI:10.1111/j.1567-1364.2007.00252.x