Genome adaptation to chemical stress: clues from comparative transcriptomics in Saccharomyces cerevisiae and Candida glabrata
1 Equipe de Bioinformatique Génomique et Moléculaire, INSERM UMR S726, Université Paris 7, INTS, 6 rue Alexandre Cabanel, 75015 Paris, France
2 Laboratoire de Génétique Moléculaire, CNRS UMR 8541, Ecole Normale Supérieure, 46 rue d'Ulm, 75230 Paris cedex 05, France
3 Plate-forme transcriptome IFR 36, Ecole Normale Supérieure, 46 rue d'Ulm, 75230 Paris cedex 05, France
4 Current address: MTI, Bât. Lamarck, 35 rue Hélène Brion, 75205 Paris Cedex 13, France
Genome Biology 2008, 9:R164 doi:10.1186/gb-2008-9-11-r164Published: 24 November 2008
Recent technical and methodological advances have placed microbial models at the forefront of evolutionary and environmental genomics. To better understand the logic of genetic network evolution, we combined comparative transcriptomics, a differential clustering algorithm and promoter analyses in a study of the evolution of transcriptional networks responding to an antifungal agent in two yeast species: the free-living model organism Saccharomyces cerevisiae and the human pathogen Candida glabrata.
We found that although the gene expression patterns characterizing the response to drugs were remarkably conserved between the two species, part of the underlying regulatory networks differed. In particular, the roles of the oxidative stress response transcription factors ScYap1p (in S. cerevisiae) and Cgap1p (in C. glabrata) had diverged. The sets of genes whose benomyl response depends on these factors are significantly different. Also, the DNA motifs targeted by ScYap1p and Cgap1p are differently represented in the promoters of these genes, suggesting that the DNA binding properties of the two proteins are slightly different. Experimental assays of ScYap1p and Cgap1p activities in vivo were in accordance with this last observation.
Based on these results and recently published data, we suggest that the robustness of environmental stress responses among related species contrasts with the rapid evolution of regulatory sequences, and depends on both the coevolution of transcription factor binding properties and the versatility of regulatory associations within transcriptional networks.