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Functional Discovery via a Compendium of Expression Profiles

Functional Discovery via a Compendium of Expression Profiles. Hughes et al. Questions. Can groups of coregulated genes be identified? Do mutations that affect similar processes have the same profiles? Can cellular functions of uncharacterized genes be predicted?. Approach.

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Functional Discovery via a Compendium of Expression Profiles

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  1. Functional Discovery via a Compendium of Expression Profiles Hughes et al.

  2. Questions • Can groups of coregulated genes be identified? • Do mutations that affect similar processes have the same profiles? • Can cellular functions of uncharacterized genes be predicted?

  3. Approach • All experiments were carried out under the same growth condition – SC media 2% glucose 30°C, mid-log phase • Did a parallel growth assay for the 198 bar-coded mutants (used custom-made arrays) • Identified biological noise using 63 control experiments • 276 deletion mutants (151 in duplicate) • 11 tetracycline-regulatable alleles of essential genes • 13 well-characterized compounds

  4. Distribution of mutants used

  5. Parallel growth assay • 198 mutants were pooled and grown. • Seven time points taken over 20 doublings. • Relative abundance of each strain was determined using a custom made microarray.

  6. Results

  7. Control experiments

  8. 300 experiment compendium data set • Major clusters include • Mating • Ergosterol biosynthesis • Mitochondrial respiration • PKC/calcineurin activated genes • Ribosome/Translation • MAPK signaling • Cell wall maintenance In general different mutants that affect the same cellular process display related transcript profiles

  9. Can cellular functions of uncharacterized ORF’s be predicted? • Compare profiles of knows with unknowns • Ergosterol biosynthesis • Cell wall maintenance • Mitochondrial respiration • Protein synthesis

  10. YER044c/ERG28 • ERG28 clusters with other ERG genes • ERG28 not essential exhibits slow growth • Sterols accumulate in the mutant • Mutant has reduced ergosterol • Mutant growth phenotype suppressed by ERG28 and hERG28 (novel gene)

  11. Dicyclonine, topical anesthetic • Profile mapped with sterol profiles • GC analysis indicated buildup of fecosterol, indicating inhibition of Erg2p • ERG2/erg2∆ mutant is hypersensitive • Overexpression of ERG2 increases resistance • Maybe inhibits phosphate transport in humans

  12. YER083c/Cell wall function • No transcripts could be identified that were induced only by mutants involved in cell wall function • However, when they look at known cell wall genes they found YER083c • YER083c exhibits characteristics of cell wall mutants • Slow growth • Hypersensitive to calcofluor white • Increased lysis rate

  13. Mitochondrial-mutant profiles • Two types • Compromise mitochondrial function • Involved in iron regulation • Three unclassified genes fell in these clusters • Co-regulated with mitochondrial ribosomal genes

  14. Mitochondrial-mutant profiles

  15. Protein synthesis • Can low magnitude changes be biologically significant? • Found 3 uncharacterized ORFs that cluster with ribosome subuints • Mutants exhibit slow growth and reduced protein synthesis

  16. Conclusions • In general different mutants that affect the same cellular process have similar transcript profiles, whether it is a direct or indirect interaction. • 4 of the 15 clusters were driven by transcriptional changes in the same genes that drove the clustering in the control experiments. • Low magnitude changes do contribute biologically significant results

  17. In the future • Because you are most likely to see differences if growth is affected under the conditions tested. A panel of conditions needs to be developed. • Pooled, bar-coded mutants • Phenotypic macroarrays

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