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Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli.

Ståhlberg A, Elbing K, Andrade-Garda JM, Sjögreen B, Forootan A, Kubista M - BMC Genomics (2008)

Bottom Line: In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc.The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map.The technique also identifies genes that show perturbed expression in specific strains.

View Article: PubMed Central - HTML - PubMed

Affiliation: TATAA Biocenter, Odinsgatan 28, 411 03 Göteborg, Sweden. anders.stahlberg@neuro.gu.se

ABSTRACT

Background: The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions.

Results: We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition.

Conclusion: Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains.

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Matrix-augmented PCA for wild-type, HXT-HXT7 and HXT-TM6* yeast. Data matrices from the respective strains were catenated to a single matrix, followed by PCA. The following colors and symbols are used: Glucose-induced genes (blue), glucose-repressed genes (red), ADH3-6 (yellow), HSP12 (black), CYC1 (green), wild-type (circles), HXT-HXT7 (squares) and HXT-TM6* (triangles).
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Figure 5: Matrix-augmented PCA for wild-type, HXT-HXT7 and HXT-TM6* yeast. Data matrices from the respective strains were catenated to a single matrix, followed by PCA. The following colors and symbols are used: Glucose-induced genes (blue), glucose-repressed genes (red), ADH3-6 (yellow), HSP12 (black), CYC1 (green), wild-type (circles), HXT-HXT7 (squares) and HXT-TM6* (triangles).

Mentions: In traditional PCA (as performed above) the PC's are calculated for each strain separately, yielding strain specific score and loading vectors. As consequence, the loadings plots obtained for the different strains cannot be compared easily because the axes have different orientations in the original multidimensional measurement space. This problem is evident when comparing the HXT- above with any of the other strains: for all the other strains genes induced upon glucose addition are characterized by negative PC1 loadings, while for HXT- induced genes have positive PC1 loadings. The reason is that the PC1 loading vectors have (among other things) opposite orientations in the two cases. To deal with this problem the study must be treated as multiway. While multivariate methods are designed to study one set of samples, characterized by the response of many variables (= genes), multiway methods should be used to study several sets of samples, such as the four strains here. One multiway method is matrix-augmented PCA [37]. In matrix-augmented PCA the pre-processed data matrices can be either laminated or catenated (Figure 2). Since we here are primarily interested in the genes we catenate the data into an 8 × 60 matrix, with the genes as columns and samplings as rows. PCA is then performed on the augmented matrix, which produces common score vectors for all strains. These were used to construct the PC1 vs. PC2 loadings scatter plot in Figure 5. In the plot, the genes are color coded as before and the four strains are distinguished by symbols. The HXT- strain was omitted for clarity. A plot containing also HXT- is provided in Additional data 2. The two main PC's account for 87% of the variability in the catenated data set and the loading vectors have shapes similar to those of the wild-type strain shown in Figure 4D. Five main areas with genes are seen.


Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli.

Ståhlberg A, Elbing K, Andrade-Garda JM, Sjögreen B, Forootan A, Kubista M - BMC Genomics (2008)

Matrix-augmented PCA for wild-type, HXT-HXT7 and HXT-TM6* yeast. Data matrices from the respective strains were catenated to a single matrix, followed by PCA. The following colors and symbols are used: Glucose-induced genes (blue), glucose-repressed genes (red), ADH3-6 (yellow), HSP12 (black), CYC1 (green), wild-type (circles), HXT-HXT7 (squares) and HXT-TM6* (triangles).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2335116&req=5

Figure 5: Matrix-augmented PCA for wild-type, HXT-HXT7 and HXT-TM6* yeast. Data matrices from the respective strains were catenated to a single matrix, followed by PCA. The following colors and symbols are used: Glucose-induced genes (blue), glucose-repressed genes (red), ADH3-6 (yellow), HSP12 (black), CYC1 (green), wild-type (circles), HXT-HXT7 (squares) and HXT-TM6* (triangles).
Mentions: In traditional PCA (as performed above) the PC's are calculated for each strain separately, yielding strain specific score and loading vectors. As consequence, the loadings plots obtained for the different strains cannot be compared easily because the axes have different orientations in the original multidimensional measurement space. This problem is evident when comparing the HXT- above with any of the other strains: for all the other strains genes induced upon glucose addition are characterized by negative PC1 loadings, while for HXT- induced genes have positive PC1 loadings. The reason is that the PC1 loading vectors have (among other things) opposite orientations in the two cases. To deal with this problem the study must be treated as multiway. While multivariate methods are designed to study one set of samples, characterized by the response of many variables (= genes), multiway methods should be used to study several sets of samples, such as the four strains here. One multiway method is matrix-augmented PCA [37]. In matrix-augmented PCA the pre-processed data matrices can be either laminated or catenated (Figure 2). Since we here are primarily interested in the genes we catenate the data into an 8 × 60 matrix, with the genes as columns and samplings as rows. PCA is then performed on the augmented matrix, which produces common score vectors for all strains. These were used to construct the PC1 vs. PC2 loadings scatter plot in Figure 5. In the plot, the genes are color coded as before and the four strains are distinguished by symbols. The HXT- strain was omitted for clarity. A plot containing also HXT- is provided in Additional data 2. The two main PC's account for 87% of the variability in the catenated data set and the loading vectors have shapes similar to those of the wild-type strain shown in Figure 4D. Five main areas with genes are seen.

Bottom Line: In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc.The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map.The technique also identifies genes that show perturbed expression in specific strains.

View Article: PubMed Central - HTML - PubMed

Affiliation: TATAA Biocenter, Odinsgatan 28, 411 03 Göteborg, Sweden. anders.stahlberg@neuro.gu.se

ABSTRACT

Background: The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions.

Results: We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition.

Conclusion: Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains.

Show MeSH
Related in: MedlinePlus