Spotlight

Our widgets for functional genomics use Orange, a data mining and machine learning suite. Orange can be accessed through scripting in Python, or by visual programming in Orange Canvas.

In functional genomics, we have also designed a web-based tool for mutant data analysis called GenePath (also featured in Science's NetWatch).


FRI > Biolab > Supplements > Microarray Data Mining with Visual Programming > S. cerevisiae Example

Description and objective of analysis

We illustrate the use of widgets with an example of the budding yeast Saccharomyces cerevisiae cell cycle microarray data from the study of Spellman et al. (1998), which includes also data from Cho et al (1998).

The numerous biological changes associated with the cell cycle made this process one of the most attractive models to study the periodically expressed genes. Control at the level of transcription is thought to be the major type of control for the >10% of all of the yeast genes whose transcript levels change with the progression of the cell cycle. In the experiments by Spellman et al. (1998) and Cho et al. (1998), gene expression of virtually all (i.e. ca 6200) yeast genes was measured in total of 77 time points in four different experimental conditions, elucidating gene expression in different cell cycle phases. The study of Spellman et al. (1998) identified 800 genes with one peak of expression during the course of the cell cycle, and for reasons of speed only these were selected as input in the presented example.

The mechanism of cell cycle regulation is conserved from yeast to mammals and therefore data obtained from the studies using yeast can sometimes be useful even in fields such as cancer therapy development. Spellman and coworkers identified 800 cell cycle-regulated genes, and they could only explain the mechanism for the periodicity of expression for about a half of them. The basis of regulation of the remaining genes, as well as their exact functions in the cell cycle, remain to be explained. In addition, Cho and coworkers found that more than 25% of the genes displaying periodic trancript levels were positioned directly adjacent to another gene induced in the same cell cycle phase. This opened the questions of the effect of upstream regulatory sequence sharing and local positional effects on gene transcription.

We have designed a schema in which two "Scatter Plot" widgets are first used to isolate the genes whose expression is specifically induced in the M/G1 phase of the cell cycle, as shown in "Expression Profiles (2)" and "Heat Map" widgets. "Genome Map" widget is used to demonstrate the adjacent positioning of the coexpressed genes, as described in Cho et al. (1998). "GO Term Finder" widgets are used to show the functional (un)relatedness of the input genes and of the selected genes.

Input Data Files

The 800 cell cycle regulated genes (Spellman et al., 1998) were selected as the input for the scheme.

To rerun the analysis one needs all of the following data files. They come with the instalation of Orange, so there is no need to install them separately:

References

Ashburner M., Ball C.A., Blake J.A., Botstein D., Butler H., Cherry J.M., Davis A.P., Dolinski K., Dwight S.S., Eppig J.T. and others. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 25, 25-9.

Cho R.J., Campbell M.J., Winzeler E.A., Steinmetz L., Conway A., Wodicka L., Wolfsberg T.G., Gabrielian A.E., Landsman D., Lockhart D.J. and others. (1998) A genome-wide transcriptional analysis of the mitotic cell cycle. Mol Cell, 2, 65-73.

Dolinski K., Balakrishnan R., Christie K.R., Costanzo M.C., Dwight S.S., Engel S.R., Fisk D.G., Hirschman J.E., Hong E.L., Nash R. and others. (2003) Saccharomyces Genome Database (http://www.yeastgenome.org/).

Spellman P.T., Sherlock G., Zhang M.Q., Iyer V.R., Anders K., Eisen M.B., Brown P.O., Botstein D., Futcher B. (1998) Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell, 9, 3273-97.