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RNA sequencing of pheromone stimulated and unstimulated MATa and MATα Saccharomyces cerevisiae

ABSTRACT: Haploid budding yeast has two mating types, defined by the alleles of the MAT locus, MATa and MATα. Mating occurs when two haploid cells of opposite mating types signal to each other using reciprocal pheromones and receptors, polarize and grow towards each other, and eventually fuse to form a single diploid cell. The pheromones and receptors are necessary and sufficient to define a mating type, but other mating type-specific proteins make mating more efficient. We examined the role of these proteins by genetically engineering “transvestite” cells that swap the pheromone, pheromone receptor, and pheromone processing factors of one mating type for another. These cells can mate with each other, but their mating is inefficient. By characterizing their mating defects and examining their transcriptomes, we found Afb1 (a-factor barrier), a novel MATα-specific protein that interferes with a-factor, the pheromone secreted by MATa cells. We show that strong pheromone secretion is essential for efficient mating and that the weak mating of transvestites can be improved by boosting their pheromone production. Using synthetic biology, it is possible to characterize the factors that control efficiency in biological processes. In the case of budding yeast mating, selection for increased mating efficiency is likely to have continually boosted pheromone levels and the ability to discriminate between partners who make more (potentially fitter) and less (potentially less fit) pheromones. This sensitivity to which partner makes more pheromone comes at a cost: it means mating is not robust in situations where all potential partners make less pheromone.

ORGANISM(S): Saccharomyces cerevisiae

PROVIDER: GSE49372 | GEO | 2014/01/07

SECONDARY ACCESSION(S): PRJNA213734

REPOSITORIES: GEO

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Project description:Fission yeast cells undergo sexual differentiation in response to nitrogen starvation. In this process haploid M and P cells first mate to form diploid zygotes, which subsequently enter meiosis and sporulate. Prior to mating, M cells secrete M-factor and P-cells secrete P-factor, and these diffusible mating pheromone can activate a signal transduction pathway in the opposite cell type. The pheromone response orchestrates mating and is also required for entry into meiosis. Here we use DNA microarrays to identify genes that are induced by M-factor in P cells and by P-factor in M-cells. The use of a cyr1 genetic background allowed us to study pheromone stimulation independently of nitrogen starvation. We identified a total of 163 genes that were consistently induced more than two-fold by pheromone stimulation. As expected, there was a substantial overlap between the genes induced by M- and P-factor. Surprisingly, we found that pheromone control extended to genes fulfilling their function well beyond the point of entry into meiosis, including numerous genes required for meiotic recombination. A direct comparison of the M- and P-factor induced expression pattern allowed us to identify cell-type specific transcripts, including three new M-specific genes and one new P-specific gene. Finally, our results support the notion that Ste11 is the key transcription factor activated by pheromone signalling. Keywords: dose response Gene expression profiling experiment in which gene expression in pheromone treated cultures was compared to that of untreated control cells. All cultures were growing exponentially in MSL minimal medium. S. pombe h+ cyr1- cells treated with M-factor mating pheromone for 2, 4 and 6 hrs respectively, were compared to non-treated cells. Similarly, S. pombe h- sax2- cyr1- cells treated with P-factor mating pheromone for 2, 4 and 6 hrs, were compared to non-treated cells. For identiofication of cell-type specific gene expression, h+ cyr1- cells were compaired to h+ sxa2- cyr1- cells. This was done both before pheromone treatment (0h/0h) and after 6 hours of pheromone treatment (6h/6h). RNA was extracted and subjected to cDNA expression profiling analysis using the established protocols (Xue et al, Yeast 21, 25-39, 2004).Data normalized with 'Lowess' per chip per spot normalization.

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RNA sequencing of pheromone stimulated and unstimulated MATa and MATα Saccharomyces cerevisiae

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