Discrimination between paralogs using microarray analysis: Application to the Yap1p and Yap2p transcriptional networks

Barak A. Cohen, Yitzhak Pilpel, Robi D. Mitra, George M. Church

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

Ohno [Ohno, S. (1970) in Evolution by Gene Duplication, Springer, New York] proposed that gene duplication with subsequent divergence of paralogs could be a major force in the evolution of new gene functions. In practice the functional differences between closely related homologues produced by duplications can be subtle and difficult to separate experimentally. Here we show that DNA microarrays can distinguish the functions of two closely related homologues from the yeast Saccharomyces cerevisiae, Yap1p and Yap2p. Although Yap1p and Yap2p are both bZIP transcription factors involved in multiple stress responses and are 88% identical in their DNA binding domains, our work shows that these proteins activate nonoverlapping sets of genes. Yap1p, controls a set of genes involved in detoxifying the effects of reactive oxygen species, whereas Yap2p controls a set of genes over represented for the function of stabilizing proteins. In addition we show that the binding sites in the promoters of the Yap1p-dependent genes differ from the sites in the promoters of Yap2p-dependent genes and we validate experimentally that these differences are important for regulation by Yap1p. We conclude that while Yap1p and Yap2p may have some overlapping functions they are clearly not redundant and, more generally, that DNA microarray analysis will be an important tool for distinguishing the functions of the large numbers of highly conserved genes found in all eukaryotic genomes.

Original languageEnglish
Pages (from-to)1608-1614
Number of pages7
JournalMolecular biology of the cell
Volume13
Issue number5
DOIs
StatePublished - 2002

Fingerprint Dive into the research topics of 'Discrimination between paralogs using microarray analysis: Application to the Yap1p and Yap2p transcriptional networks'. Together they form a unique fingerprint.

Cite this