Functional Discovery via a Compendium of Expression Profiles

Rosetta Inpharmatics, Inc., Kirkland, Washington 98034, USA.
Cell (Impact Factor: 32.24). 08/2000; 102(1):109-26. DOI: 10.1016/S0092-8674(00)00015-5
Source: PubMed


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.

Download full-text


Available from: Christopher D Armour, Oct 06, 2015
37 Reads
  • Source
    • "A compendium of transcriptional profiles or signatures of gene-deletion strains under various growth conditions is useful for function discovery (Hughes et al. 2000). Hence, we wanted to investigate whether there was a unique transcriptional signature in kinase-deletion strains defective in iodine vapor staining or sexual development (hereafter sexual development) and G0 arrest. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Nitrogen starvation (NS) induces sexual development when mating partners are available or enter into quiescent state (G0) in heterothallic background in fission yeast. However, little is known whether the two processes share common signaling molecules or cells defective in the two processes share common transcriptional signatures. To address these questions, we first assessed 77 kinase-deletion strains for NS-induced G0-arrest phenotypes. Our result indicated that 10 out of 77 kinase-deletion strains exhibited defect in G0-arrest, only 3 of which were defective in sexual development based on a previous study, suggesting that the two processes hardly share common signaling components. We subsequently performed transcriptional profiling analysis. Our result indicated that NS-induced transcriptional change was so robust that it prevailed the alteration by individual kinase-deletion alleles. Based on comparison between kinase-deletion strains proficient and deficient in sexual development or G0-arrest, we identified subsets of genes that were associated with sexual development-deficient or G0-arrest-deficient kinase-deletion strains. Multiple pairing analyses allowed grouping of functional related kinases. Furthermore, we showed that Pka1-mediated pathways were required for upregulation of NS-induced genes upon NS and downregulation of the same set of genes under the N-replete conditions. Taken together, our analyses indicate that sexual development and NS-induced G0-arrest are unrelated; and sexual development-deficient and G0-arrest-deficient kinase-deletion strains possess distinct transcriptional signatures. We propose that Pka1 is a key regulator of nitrogen metabolic pathways and Pka1-mediated signaling pathways play roles in regulation of NS-induced genes under both N-depleted and N-replete conditions.
    Molecular Genetics and Genomics 12/2014; 290(3). DOI:10.1007/s00438-014-0966-6 · 2.73 Impact Factor
    • "A) The Sth1 protein was depleted by utilizing a conditional knock-down strain (STH1-TET) (Hughes et al., 2000) in which the endogenous promoter was replaced by a tetracycline titratable promoter. "
    [Show abstract] [Hide abstract]
    ABSTRACT: ATP-dependent chromatin remodelers regulate chromatin structure during multiple stages of transcription. We report that RSC, an essential chromatin remodeler, is recruited to the open reading frames (ORFs) of actively transcribed genes genome wide, suggesting a role for RSC in regulating transcription elongation. Consistent with such a role, Pol II occupancy in the ORFs of weakly transcribed genes is drastically reduced upon depletion of the RSC catalytic subunit Sth1. RSC inactivation also reduced histone H3 occupancy across transcribed regions. Remarkably, the strongest effects on Pol II and H3 occupancy were confined to the genes displaying the greatest RSC ORF enrichment. Additionally, RSC recruitment to the ORF requires the activities of the SAGA and NuA4 HAT complexes and is aided by the activities of the Pol II CTD Ser2 kinases Bur1 and Ctk1. Overall, our findings strongly implicate ORF-associated RSC in governing Pol II function and in maintaining chromatin structure over transcribed regions.
    Molecular Cell 12/2014; DOI:10.1016/j.molcel.2014.10.002 · 14.02 Impact Factor
  • Source
    • "The later is an important but complex question that is out of the scope of this study. Another goal of this work was to study whether the type of biological experiment underlying the data affects the functional content of inferred networks because different types of biological experiments are expected to capture somewhat complementary aspects of the cell (Jansen, 2001; Hughes et al., 2000). To our knowledge this is the first study explicitly comparing networks constructed from line cross data with networks constructed from treatment data. "
    [Show abstract] [Hide abstract]
    ABSTRACT: A fundamental goal of systems biology is to create models that describe relationships between biological components. Networks are an increasingly popular approach to this problem. However, a scientist interested in modeling biological (e.g., gene expression) data as a network is quickly confounded by the fundamental problem: how to construct the network? It is fairly easy to construct a network, but is it the network for the problem being considered? This is an important problem with three fundamental issues: How to weight edges in the network in order to capture actual biological interactions? What is the effect of the type of biological experiment used to collect the data from which the network is constructed? How to prune the weighted edges (or what cut-off to apply)? Differences in the construction of networks could lead to different biological interpretations. Indeed, we find that there are statistically significant dissimilarities in the functional content and topology between gene co-expression networks constructed using different edge weighting methods, data types, and edge cut-offs. We show that different types of known interactions, such as those found through Affinity Capture-Luminescence or Synthetic Lethality experiments, appear in significantly varying amounts in networks constructed in different ways. Hence, we demonstrate that different biological questions may be answered by the different networks. Consequently, we posit that the approach taken to build a network can be matched to biological questions to get targeted answers. More study is required to understand the implications of different network inference approaches and to draw reliable conclusions from networks used in the field of systems biology.
    08/2014; 2(02):139-161. DOI:10.1017/nws.2014.13
Show more