PMID:10929718
| Citation |
Hughes, TR, Marton, MJ, Jones, AR, Roberts, CJ, Stoughton, R, Armour, CD, Bennett, HA, Coffey, E, Dai, H, He, YD, Kidd, MJ, King, AM, Meyer, MR, Slade, D, Lum, PY, Stepaniants, SB, Shoemaker, DD, Gachotte, D, Chakraburtty, K, Simon, J, Bard, M and Friend, SH (2000) Functional discovery via a compendium of expression profiles. Cell 102:109-26 |
|---|---|
| Abstract |
Ascertaining the impact of uncharacterized perturbations on the cell is a fundamental problem in biology. Here, we describe how a single assay can be used to monitor hundreds of different cellular functions simultaneously. We constructed a reference database or "compendium" of expression profiles corresponding to 300 diverse mutations and chemical treatments in S. cerevisiae, and we show that the cellular pathways affected can be determined by pattern matching, even among very subtle profiles. The utility of this approach is validated by examining profiles caused by deletions of uncharacterized genes: we identify and experimentally confirm that eight uncharacterized open reading frames encode proteins required for sterol metabolism, cell wall function, mitochondrial respiration, or protein synthesis. We also show that the compendium can be used to characterize pharmacological perturbations by identifying a novel target of the commonly used drug dyclonine. |
| Links | |
| Keywords |
Cell Wall/physiology; Databases, Factual; Ergosterol/biosynthesis; Fungal Proteins/biosynthesis; Fungal Proteins/genetics; Gene Expression Profiling; Gene Expression Regulation, Fungal; Genes, Fungal; Genes, Reporter; Genetic Complementation Test; Genetic Variation; Humans; Mitochondria/metabolism; Models, Genetic; Mutagenesis; Open Reading Frames; Phenotype; Propiophenones/pharmacology; Receptors, sigma/genetics; Ribosomes; Saccharomyces cerevisiae/drug effects; Saccharomyces cerevisiae/genetics; Saccharomyces cerevisiae/physiology; Steroid Isomerases/genetics; Transcription, Genetic |
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This much-cited paper provides one of the early examples of using two-dimensional cluster analysis of microarray transcriptome data to infer gene function and identify the targets of antibiotics.
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