Ontology highlight
ABSTRACT:
PROVIDER: PRJNA830720 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18885540_1.fastq.gz | Fastqsanger.gz | |||
| SRR18885540_2.fastq.gz | Fastqsanger.gz | |||
| SRR18885541_1.fastq.gz | Fastqsanger.gz | |||
| SRR18885541_2.fastq.gz | Fastqsanger.gz |
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Project description:Our study involves a transcriptomic approach to the analysis of industrial yeast metabolism. Historically, among the hundreds of yeast species, Saccharomyces cerevisiae has played an important role in scientific investigations and industrial applications, and it is universally acknowledged as one of the model systems for eukaryotic organisms. Yeast is also an important component of the wine fermentation process and determines various attributes of the final product. Our research takes a holistic approach to the improvement of industrial yeast strains by integrating large data sets from various yeast strains during fermentation. This means that analysis can be done in such a way as to co-evaluate several parameters simultaneously to identify points of interest and target genes for metabolic engineering. Eventually we hope to construct an accurate information matrix and a more complete cellular map for the fermenting yeast. This will enable accurate model-building for industrial yeast and facilitated the design of intelligent yeast improvement strategies which can be applied via traditional avenues of molecular biology. Experiment Overall Design: Five different Saccharomyces cerevisiae strains used in industrial winemaking processes were used in synthetic must (MS300) fermentations. All fermentations were carried out in triplicate, so each sample is represented by three completely independent biological repeats. Samples for microarray analysis were taken at three different time points during fermentation, representative of the exponential (day2), early stationary (day5) and late stationary (day14) growth stages.
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