Impact of combined wine-related stressors on Saccharomyces cerevisiae and mapping of the associated QTLs

Abstract

Ethanol, hyperosmotic stress, and certain levels of SO₂ are the main abiotic factors inhibiting the survival of Saccharomyces cerevisiae during winemaking, but how combinations of these stressors impact yeast growth and the underlying genetic basis are not well studied. To illustrate these questions, ten randomly selected Chinese indigenous haploid S. cerevisiae were first evaluated for multi-stressor tolerance using a three-factor, three-level orthogonal test. Great variation in growth was observed in a medium containing 6% v/v ethanol, 300 mg/L SO₂, and hyperosmotic stress equivalent to 200 g/L fructose. One hundred and eighteen haploids were further tested under the mentioned stress levels. Their growth shared common features of quantitative traits, which indicates the underlying mechanism can be investigated by quantitative trait locus (QTL) mapping. The parental haploids with opposite tolerance to the combined stressors were selected to generate the F1 hybrid and F2 segregants. Further characterization of the F2 population allowed the assembly of two pools, each composed of 15 individuals showing divergent tolerance to the multi-stressor. The associated major QTLs were mapped by genome-wide comparison of single-nucleotide polymorphism profiles between the two pools. Two regions located on Chromosomes III and XIV were identified to be associated with the multi-stressor tolerance. Based on GO and KEGG enrichment analysis, seven genes involved in nucleotide binding, methylation, and sterol synthesis were finally selected as potential quantitative trait genes that play a role in supporting yeast growth under the multi-stressor. The findings of this study expand current knowledge on the genetic determinants of variation in yeast tolerance to combined ethanol-hyperosmotic-SO₂ stressors.

Keywords

Saccharomyces cerevisiae / Ethanol-hyperosmotic-SO₂ stressors / Stress tolerance / Bulk segregant analysis / Quantitative trait loci

Author contributions

The authors confirm their contributions to the paper as follows: study conception and design: Jiang J, Yu H, Lei X; data collection: Jiang J, Yu H, Lei X, Yang H; analysis and interpretation of results: Jiang J, Yu H, Lei X, Yang H; writing - draft manuscript preparation: Jiang J, Yu H, Ye D; supervision: Liu Y, Qin Y, Jiang J; writing - review and editing: Jiang J, Yu H, Liu Y, Zhang J, Qin Y, Song Y. All authors reviewed the results and approved the final version of the manuscript.

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Acknowledgments

We extend our thanks to the College of Enology at Northwest A&F University. This work was financially supported by Ningxia Hui Autonomous Region Key R&D Project (Grant No. 2023BCF01027), the National Natural Science Foundation of China (Grant Nos U21A20269, 32372312, 32402163), the National Foreign Expert Program of China(Grant No. G2022172022L), Northwest A&F University (Grant No.Z2220221027), and the earmarked fund for CARS (CARS-29-jg-3)

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary information

accompanies this paper at (https://www.maxapress.com/article/doi/10.48130/fia-0025-0032)

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