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Expression Data from the Riesling grape must fermentation by industrial M2 and M2 nsf1M-bM-^HM-^F S. cerevisiae strains for functional characterization of the NSF1 (YPL230W) gene via Correlation Clustering-based method


ABSTRACT: The main objectives of this study were to expand our understanding of NSF1 gene function in industrial S. cerevisiae M2 strain during fermentation by finding the largest maximal clique of co-expressed genes (i.e. Interdependent Correlation Cluster), and to establish the impact of Nsf1p on genome-wide gene expression during the fermentation process with possible implications related to wine quality and S. cerevisiae adapation to stressful fermentation conditions The Affymetrix Yeast 2.0 microarrays were used to capture the global gene expression profile of M2 and M2 nsf1M-bM-^HM-^F grown under fermentation conditions in Riesling grape must at 18M-BM-0C with no shaking at various time points. The analysis of this microarray dataset expanded our understanding of the mechanism of action and the roles of NSF1 under fermentation stress conditions. The overall experimental setup consisted of 2 stains (M2 and M2 nsf1M-bM-^HM-^F) and 3 sample time points (24h post-innoculation, 20% and 85% of total glucose fermented) .

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Kyrylo Bessonov 

PROVIDER: E-GEOD-34117 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Functional analyses of NSF1 in wine yeast using interconnected correlation clustering and molecular analyses.

Bessonov Kyrylo K   Walkey Christopher J CJ   Shelp Barry J BJ   van Vuuren Hennie J J HJ   Chiu David D   van der Merwe George G  

PloS one 20131009 10


Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of co  ...[more]

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