Large-scale prediction of Saccharomyces cerevisiae gene function using overlapping transcriptional clusters

Wu, Lani F.; Hughes, Timothy R.; Davierwala, Armaity P.; Robinson, Mark D.; Stoughton, Roland; Altschuler, Steven J.

doi:10.1038/ng906

Cited by 314 publications

(233 citation statements)

References 37 publications

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“…Clearly SHM2 is also a member of the regulon and does not cluster with the others only because of the lack of SHM2 transcript in the shm2⌬ strain. SHM2 showed very similar expression to the GCV genes over the compendium of publicly available genome-wide expression studies clustered by Hughes and co-workers (36). ADE4 demonstrated behavior clearly consistent with membership of the one-carbon regulon, whereas ADE6, ADE12, and ADE3 are also possible candidates.…”

Section: Co-regulation Of One-carbon Metabolism and Purine Biosynthesmentioning

confidence: 71%

Identification of a Novel One-carbon Metabolism Regulon in Saccharomyces cerevisiae

Gelling

Piper²,

Hong³

et al. 2004

Journal of Biological Chemistry

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Glycine specifically induces genes encoding subunits of the glycine decarboxylase complex (GCV1, GCV2, and GCV3), and this is mediated by a fall in cytoplasmic levels of 5,10-methylenetetrahydrofolate caused by inhibition of cytoplasmic serine hydroxymethyltransferase. Here it is shown that this control system extends to genes for other enzymes of one-carbon metabolism and de novo purine biosynthesis. Northern analysis of the response to glycine demonstrated that the induction of the GCV genes and the induction of other amino acid metabolism genes are temporally distinct. The genomewide response to glycine revealed that several other genes are rapidly co-induced with the GCV genes, including SHM2, which encodes cytoplasmic serine hydroxymethyltransferase. These results were refined by examining transcript levels in an shm2⌬ strain (in which cytoplasmic 5,10-methylenetetrahydrofolate levels are reduced) and a met13⌬ strain, which lacks the main methylenetetrahydrofolate reductase activity of yeast and is effectively blocked at consumption of 5,10-methylene tetrahydrofolate for methionine synthesis. Glycine addition also caused a substantial transient disturbance to metabolism, including a sequence of changes in induction of amino acid biosynthesis and respiratory chain genes. Analysis of the glycine response in the shm2⌬ strain demonstrated that apart from the one-carbon regulon, most of these transient responses were not contingent on a disturbance to onecarbon metabolism. The one-carbon response is distinct from the Bas1p purine biosynthesis regulon and thus represents the first example of transcriptional regulation in response to activated one-carbon status.

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Section: Co-regulation Of One-carbon Metabolism and Purine Biosynthesmentioning

confidence: 71%

Identification of a Novel One-carbon Metabolism Regulon in Saccharomyces cerevisiae

Gelling

Piper²,

Hong³

et al. 2004

Journal of Biological Chemistry

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“…To test whether the severe growth phenotype of Utp24 depletion is due to impaired ribosome biogenesis and to characterize the previously described 18S maturation defect for Utp23 in greater detail, we analyzed steady-state levels of pre-rRNAs and mature rRNAs in cells depleted of Utp23 or Utp24 (11). Depletion of either protein resulted in accumulation of the 35S pre-rRNA, which was accompanied by a decrease in the levels of the 27SA 2 and 20S pre-rRNAs and the mature 18S rRNA (Fig.…”

Section: Utp23 and Utp24 Are Essential For Ssu Biogenesismentioning

confidence: 99%

The PINc domain protein Utp24, a putative nuclease, is required for the early cleavage steps in 18S rRNA maturation

Bleichert

Granneman

Osheim

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

104

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Ribosome biogenesis is a complex process that requires >150 transacting factors, many of which form macromolecular assemblies as big and complex as the ribosome itself. One of those complexes, the SSU processome, is required for pre-18S rRNA maturation. Although many of its components have been identified, the endonucleases that cleave the pre-18S rRNA have remained mysterious. Here we examine the role of four previously uncharacterized PINc domain proteins, which are predicted to function as nucleases, in yeast ribosome biogenesis. We also included Utp23, a protein homologous to the PINc domain protein Utp24, in our analysis. Our results demonstrate that Utp23 and Utp24 are essential nucleolar proteins and previously undescribed components of the SSU processome. In that sense, both Utp23 and Utp24 are required for the first three cleavage steps in 18S rRNA maturation. In addition, single-point mutations in the conserved putative active site of Utp24 but not Utp23 abrogate its function in ribosome biogenesis. Our results suggest that Utp24 might be the elusive endonuclease that cleaves the pre-rRNA at sites A 1 and͞or A2.ribosome biogenesis ͉ small subunit processome ͉ endonuclease ͉ yeast ͉ RNA processing R ibosomes translate mRNA into proteins and, thereby, govern cell growth and survival. In Saccharomyces cerevisiae, ribosome biogenesis starts with the transcription of the rDNA into a polycistronic rRNA precursor by RNA polymerase I in the nucleolus. The primary transcript, the 35S pre-rRNA, encodes the small subunit (SSU) rRNA, 18S, the large subunit rRNAs, 25S and 5.8S, and also external and internal transcribed spacer regions (5ЈETS, ITS1, ITS2, and 3ЈETS; Fig. 1). This precursor is extensively endoand exonucleolytically cleaved to mature the rRNAs. Maturation begins with endonucleolytic cleavages at sites A 0 , A 1 , and A 2 , the latter separating the 20S pre-rRNA, the direct precursor to the mature 18S rRNA, and the 27SA 2 pre-rRNA, the precursor to the large subunit rRNAs. The 20S pre-rRNA is exported into the cytoplasm as part of the 43S preribosome, where the 18S rRNA is matured by cleavage at site D.The A 0 , A 1 , and A 2 pre-rRNA cleavages require a large ribonucleoprotein complex, the SSU processome͞90S preribosome, which contains at least 40 different proteins and numerous small nucleolar RNAs (snoRNAs) (1-4). This complex likely corresponds to the terminal knobs seen in Miller chromatin spreads (1, 5). Depletion of essential SSU processome components prevents cleavages at sites A 0 -A 2 but not A 3 . Although this results in accumulation of the 23S pre-rRNA and inhibition of 18S synthesis, maturation of the 25S and 5.8S rRNAs can occur normally (Fig. 1).Despite the identification of numerous proteins involved in early pre-18S rRNA processing by large-scale purifications, the endonuclease(s) and possible candidates that carry out these cleavages have remained elusive. Recently, an interesting group of proteins possessing a PIN domain (PilT N terminus, PINc domain in SMART database) has been impl...

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“…Hypothesis testing was used to determine whether biologically related genes were statistically overrepresented in the expression clusters. Although Cho et al did not explore the possible use of their clusters for classification of genes, this has recently been reported by Wu et al (2002) using a similar semisupervised methodology. Statistically significant overlapping clusters were annotated with biological process and subsequently used for prediction of the involvement of 1644 of 3020 uncharacterized yeast genes.…”

Section: Discussionmentioning

confidence: 99%

Predicting Gene Ontology Biological Process From Temporal Gene Expression Patterns

Lægreid¹,

Hvidsten²,

Midelfart³

et al. 2003

Genome Res.

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The aim of the present study was to generate hypotheses on the involvement of uncharacterized genes in biological processes. To this end, supervised learning was used to analyze microarray-derived time-series gene expression data. Our method was objectively evaluated on known genes using cross-validation and provided high-precision Gene Ontology biological process classifications for 211 of the 213 uncharacterized genes in the data set used. In addition, new roles in biological process were hypothesized for known genes. Our method uses biological knowledge expressed by Gene Ontology and generates a rule model associating this knowledge with minimal characteristic features of temporal gene expression profiles. This model allows learning and classification of multiple biological process roles for each gene and can predict participation of genes in a biological process even though the genes of this class exhibit a wide variety of gene expression profiles including inverse coregulation. A considerable number of the hypothesized new roles for known genes were confirmed by literature search. In addition, many biological process roles hypothesized for uncharacterized genes were found to agree with assumptions based on homology information. To our knowledge, a gene classifier of similar scope and functionality has not been reported earlier.

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Large-scale prediction of Saccharomyces cerevisiae gene function using overlapping transcriptional clusters

Cited by 314 publications

References 37 publications

Identification of a Novel One-carbon Metabolism Regulon in Saccharomyces cerevisiae

Identification of a Novel One-carbon Metabolism Regulon in Saccharomyces cerevisiae

The PINc domain protein Utp24, a putative nuclease, is required for the early cleavage steps in 18S rRNA maturation

Predicting Gene Ontology Biological Process From Temporal Gene Expression Patterns

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