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Open Access Research article

Combination of genomic approaches with functional genetic experiments reveals two modes of repression of yeast middle-phase meiosis genes

Michael Klutstein123, Zahava Siegfried1, Ariel Gispan1, Shlomit Farkash-Amar1, Guy Zinman4, Ziv Bar-Joseph4, Giora Simchen2* and Itamar Simon1*

Author Affiliations

1 Department of Microbiology and Molecular Genetics, The Institute for Medical Research - Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, 91120 Israel

2 Department of Genetics, The Hebrew University, Jerusalem, 91904 Israel

3 Telomere Biology Laboratory, Cancer Research UK, 44 Lincoln's Inn Fields, London WC2A 3PX, UK

4 School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA

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BMC Genomics 2010, 11:478  doi:10.1186/1471-2164-11-478

Published: 17 August 2010

Abstract

Background

Regulation of meiosis and sporulation in Saccharomyces cerevisiae is a model for a highly regulated developmental process. Meiosis middle phase transcriptional regulation is governed by two transcription factors: the activator Ndt80 and the repressor Sum1. It has been suggested that the competition between Ndt80 and Sum1 determines the temporal expression of their targets during middle meiosis.

Results

Using a combination of ChIP-on-chip and expression profiling, we characterized a middle phase transcriptional network and studied the relationship between Ndt80 and Sum1 during middle and late meiosis. While finding a group of genes regulated by both factors in a feed forward loop regulatory motif, our data also revealed a large group of genes regulated solely by Ndt80. Measuring the expression of all Ndt80 target genes in various genetic backgrounds (WT, sum1Δ and MK-ER-Ndt80 strains), allowed us to dissect the exact transcriptional network regulating each gene, which was frequently different than the one inferred from the binding data alone.

Conclusion

These results highlight the need to perform detailed genetic experiments to determine the relative contribution of interactions in transcriptional regulatory networks.