Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Trans-acting regulatory variation in Saccharomyces cerevisiae

ABSTRACT: Natural genetic variation can cause significant differences in gene expression, but little is known about the polymorphisms that affect gene regulation. We analyzed regulatory variation in a cross between laboratory and wild strains of Saccharomyces cerevisiae. Clustering and linkage analysis defined groups of coregulated genes and the loci involved in their regulation. Most expression differences mapped to trans-acting loci. Positional cloning and functional assays showed that polymorphisms in GPA1 and AMN1 affect expression of genes involved in pheromone response and daughter cell separation, respectively. We also asked whether particular classes of genes were more likely to contain trans-regulatory polymorphisms. Notably, transcription factors showed no enrichment, and trans-regulatory variation seems to be broadly dispersed across classes of genes with different molecular functions

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: G Yvert

PROVIDER: E-GEOD-617 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factors.

Yvert Gaël G Brem Rachel B RB Whittle Jacqueline J Akey Joshua M JM Foss Eric E Smith Erin N EN Mackelprang Rachel R Kruglyak Leonid L

Nature genetics 20030803 1

Natural genetic variation can cause significant differences in gene expression, but little is known about the polymorphisms that affect gene regulation. We analyzed regulatory variation in a cross between laboratory and wild strains of Saccharomyces cerevisiae. Clustering and linkage analysis defined groups of coregulated genes and the loci involved in their regulation. Most expression differences mapped to trans-acting loci. Positional cloning and functional assays showed that polymorphisms in ...[more]

PMID: 12897782

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Project description:The use of genome-wide RNA abundance profiling by microarrays and deep sequencing has spurred a revolution in our understanding of transcriptional control. However, changes in mRNA abundance reflect the combined effect of changes in RNA production, processing, and degradation, and thus, mRNA levels provide an occluded view of transcriptional regulation. To partially disentangle these issues, we carry out genome-wide RNA Polymerase II (“Pol2”) localization profiling in budding yeast in two different stress response time courses. While mRNA changes largely reflect changes in transcription, there remains a great deal of variation in mRNA levels that is not accounted for by changes in Pol2 abundance. We find that genes exhibiting “excess” mRNA produced per Pol2 are enriched for those with overlapping cryptic transcripts, indicating a pervasive role for nonproductive or regulatory transcription in control of gene expression. Finally, we characterize changes in Pol2 localization when Pol2 is genetically inactivated using the rpb1-1 temperature-sensitive mutation. We find that Pol2 is lost from chromatin after roughly an hour at the restrictive temperature, and that there is a great deal of variability in the rate of Pol2 loss at different loci. Together, these results provide a global perspective on the relationship between Pol2 and mRNA production in budding yeast. The array studies consisted of 4 time courses in which the genome-wide location of RNA Polymerase II was mapped via chromatin immunoprecipitation (ChIP) in BY4741 S. cerevisiae cells or in such cells bearing the temperature sensitive mutation rpb1, in response to heat shock at 37 degrees C and/or 1.5 mM diamide. All samples were hybridized as the ChIP sample (Cy3 labeled, channel 1) versus its cognate ChIP input sample (Cy5 labeled, channel 2). The first time course was a heat shock in wild-type BY4741 cells. The second time course was a heat shock in BY4741 rpd1 cells. The third time course was a diamide treatment of BY4741 rpd1 cells. The fourth time course was a 10 minute heat shock in BY4741 rpd1 cells followed by treatment from 15-60 minutes with diamide (3 samples). In the first three time courses the time range is 0-120 minutes (5 samples). A total of 18 arrays were used in this study. No additional replicates or dye-flip experiments were performed.

Project description:This 58 arrays are the basis of our hypoxia story published in PLoS Medicine. The cell type, oxygen tension and time points are indicated. Abstract: BACKGROUND: Inadequate oxygen (hypoxia) triggers a multifaceted cellular response that has important roles in normal physiology and in many human diseases. A transcription factor, hypoxia-inducible factor (HIF), plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1alpha protein. Despite the ubiquity and importance of hypoxia responses, little is known about the variation in the global transcriptional response to hypoxia among different cell types or how this variation might relate to tissue- and cell-specific diseases. METHODS AND FINDINGS: We analyzed the temporal changes in global transcript levels in response to hypoxia in primary renal proximal tubule epithelial cells, breast epithelial cells, smooth muscle cells, and endothelial cells with DNA microarrays. The extent of the transcriptional response to hypoxia was greatest in the renal tubule cells. This heightened response was associated with a uniquely high level of HIF-1alpha RNA in renal cells, and it could be diminished by reducing HIF-1alpha expression via RNA interference. A gene-expression signature of the hypoxia response, derived from our studies of cultured mammary and renal tubular epithelial cells, showed coordinated variation in several human cancers, and was a strong predictor of clinical outcomes in breast and ovarian cancers. In an analysis of a large, published gene-expression dataset from breast cancers, we found that the prognostic information in the hypoxia signature was virtually independent of that provided by the previously reported wound signature and more predictive of outcomes than any of the clinical parameters in current use. CONCLUSIONS: The transcriptional response to hypoxia varies among human cells. Some of this variation is traceable to variation in expression of the HIF1A gene. A gene-expression signature of the cellular response to hypoxia is associated with a significantly poorer prognosis in breast and ovarian cancer. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Using regression correlation

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Trans-acting regulatory variation in Saccharomyces cerevisiae

Publications

Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factors.

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