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Epistatic relationships reveal the functional organization of yeast transcription factors.

The regulation of gene expression is, in large part, mediated by interplay between the general transcription factors (GTFs) that function to bring about the expression of many genes and site-specific DNA-binding transcription factors (STFs). Here, quantitative genetic profiling using the epistatic miniarray profile (E-MAP) approach allowed us to measure 48 391 pairwise genetic interactions, both negative (aggravating) and positive (alleviating), between and among genes encoding STFs and GTFs in Saccharomyces cerevisiae. This allowed us to both reconstruct regulatory models for specific subsets of transcription factors and identify global epistatic patterns. Overall, there was a much stronger preference for negative relative to positive genetic interactions among STFs than there was among GTFs. Negative genetic interactions, which often identify factors working in non-essential, redundant pathways, were also enriched for pairs of STFs that co-regulate similar sets of genes. Microarray analysis demonstrated that pairs of STFs that display negative genetic interactions regulate gene expression in an independent rather than coordinated manner. Collectively, these data suggest that parallel/compensating relationships between regulators, rather than linear pathways, often characterize transcriptional circuits.

Pubmed ID: 20959818 RIS Download

Mesh terms: Cluster Analysis | Computational Biology | Epistasis, Genetic | Gene Expression Profiling | Gene Expression Regulation, Fungal | Gene Regulatory Networks | Genes, Fungal | Models, Genetic | Oligonucleotide Array Sequence Analysis | Saccharomyces cerevisiae | Transcription Factors

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Associated grants

  • Agency: NIGMS NIH HHS, Id: R01 GM070808
  • Agency: NIGMS NIH HHS, Id: GM081879
  • Agency: NIGMS NIH HHS, Id: GM084279
  • Agency: NIGMS NIH HHS, Id: P50 GM081879
  • Agency: NIGMS NIH HHS, Id: GM084448
  • Agency: NIGMS NIH HHS, Id: R01 GM084448
  • Agency: NIGMS NIH HHS, Id: GM70808
  • Agency: NIGMS NIH HHS, Id: R01 GM090293
  • Agency: NIGMS NIH HHS, Id: R01 GM084279
  • Agency: NIGMS NIH HHS, Id: GM90293

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European Bioinformatics Institute

A non-profit academic organization for research and services in bioinformatics that provides freely available data from life science experiments, performs basic research in computational biology, and offers an extensive user training programme, supporting researchers in academia and industry. The Institute manages databases of biological data including nucleic acid, protein sequences, and macromolecular structures.

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Krogan Lab Interactome Database

This database currently holds E-MAP scores (individual interactions and correlation coefficients) for budding yeast genes involved in the early secretory pathway and chromosome function (including DNA damage and repair, transcriptional control, chromosome segregation and telomere regulation). E-MAPs (Epistatic Mini Array Profiles) are formed by creating and quantifying high-density genetic interaction maps. With this method, observed double mutant colony sizes are compared to those that would be expected from a distribution of typical double mutant colonies of each strain. Each interaction is assigned a score, which indicates the magnitude of the difference from the expected value and the certainty of the score. Negative (or aggravating) scores (< -2.5) correspond to synthetic sick/lethal interactions while positive (or alleviating) scores (> +2.5) corresponds to epistatic or suppressor interactions.

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