Data from: QTL mapping of volatile compound production in Saccharomyces cerevisiae during alcoholic fermentation

Background: The volatile metabolites produced by Saccharomyces cerevisiae during alcoholic fermentation, which are mainly esters, higher alcohols and organic acids, play a vital role in the quality and perception of fermented beverages, such as wine. Although the metabolic pathways and genes behind yeast fermentative aroma formation are well described, little is known about the genetic mechanisms underlying variations between strains in the production of these aroma compounds. To increase our knowledge about the links between genetic variation and volatile production, we performed quantitative trait locus (QTL) mapping using 130 F2-meiotic segregants from two S. cerevisiae wine strains. The segregants were individually genotyped by next-generation sequencing and separately phenotyped during wine fermentation. Results: Using different QTL mapping strategies, we were able to identify 65 QTLs in the genome, including 55 that influence the formation of 30 volatile secondary metabolites, 14 with an effect on sugar consumption and central carbon metabolite production, and 7 influencing fermentation parameters. For ethyl lactate, ethyl octanoate and propanol formation, we discovered 2 interacting QTLs each. Within 9 of the detected regions, we validated the contribution of 13 genes in the observed phenotypic variation by reciprocal hemizygosity analysis. These genes are involved in nitrogen uptake and metabolism (AGP1, ALP1, ILV6, LEU9), central carbon metabolism (HXT3, MAE1), fatty acid synthesis (FAS1) and regulation (AGP2, IXR1, NRG1, RGS2, RGT1, SIR2) and explain variations in the production of characteristic sensorial esters (e.g., 2-phenylethyl acetate, 2-metyhlpropyl acetate and ethyl hexanoate), higher alcohols and fatty acids. Conclusions: The detection of QTLs and their 51 interactions emphasizes the complexity of yeast fermentative aroma formation. The validation of underlying allelic variants increases knowledge about genetic variation impacting metabolic pathways that lead to the synthesis of sensorial important compounds. As a result, this work lays the foundation for tailoring S. cerevisiae strains with optimized volatile metabolite production for fermented beverages and other biotechnological applications.Microsatellite-treeMicrosatellite dataset, R script and tree of 445 strains indicating the phylogenic position of 4CAR1 and T73 used for QTL mapping. Read me text is included in the compressed archivePhenotypic data for QTL analysisDescription: comma-seperated values file containing the phenotype data of 130 evaluated segregant strains (Id).results4QTLanalysis.csvGenotypes of all_finalDescription: genotype file at R-QTL format, containing the identities of 3457 markers for 125 segregant strains (Id) that were used for the QTL mapping. These makers have a minim distance of 2kb between them. Identity "A" corresponds to nucleotide contributed by parent 4CAR1, identity "B" corresponds to nucleotide contributed by parent T73. First line contains the Id of each marker : "chromosome_coordinates", line 2 indicates the chromosome, and line 3 indicates the coordinates in cm (coordinates / 3000)genotypesAll2000_final.csvSNPeffectDescription: comma-seperated values file listing all SNPs between the parent strains of the study, 4CAR1 and T73 with potential effect. The effects of SNPs on genes was predicted by SnpEff version 4.1.Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: FP7/2007-2013/ under REA grant agreement n° 60679