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Regena (Rga), a Drosophila homolog of the global negative transcriptional regulator CDC36 (NOT2) from yeast, modifies gene expression and suppresses position effect variegation.

ABSTRACT: A mutation in Regena (Rga) was isolated in screens for modifiers of white eye color gene expression. The reduction in the level of the Rga product results in a complex modulation of white mRNA both positively and negatively, depending on the developmental stage. In addition to white, Rga also affects the expression of several other tested genes, with one of them, Vinculin, being regulated in a strong sex-specific manner. Rga was cloned by transposon tagging. Its predicted product lacks any recognized nucleic acid-binding motif but is homologous to a global negative transcriptional regulator, CDC36 (NOT2), from yeast. Rga also acts as a suppressor of position effect variegation, suggesting that a possible function of Rga could be mediation of an interaction between chromatin proteins and the transcriptional complex.

SUBMITTER: Frolov MV

PROVIDER: S-EPMC1459787 | biostudies-other | 1998 Jan

REPOSITORIES: biostudies-other

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Regena (Rga), a Drosophila homolog of the global negative transcriptional regulator CDC36 (NOT2) from yeast, modifies gene expression and suppresses position effect variegation.

Frolov M V MV Benevolenskaya E V EV Birchler J A JA

Genetics 19980101 1

A mutation in Regena (Rga) was isolated in screens for modifiers of white eye color gene expression. The reduction in the level of the Rga product results in a complex modulation of white mRNA both positively and negatively, depending on the developmental stage. In addition to white, Rga also affects the expression of several other tested genes, with one of them, Vinculin, being regulated in a strong sex-specific manner. Rga was cloned by transposon tagging. Its predicted product lacks any recog ...[more]

PMID: 9475742

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Project description:Genome sequencing dramatically increased our ability to understand cellular response to perturbation. Integrating system-wide measurements such as gene expression with networks of protein-protein interactions and transcription factor binding revealed critical insights into cellular behavior. However, the potential of systems biology approaches is limited by difficulties in integrating metabolic measurements across the functional levels of the cell despite their being most closely linked to cellular phenotype. To address this limitation, we developed a model-based approach to correlate mRNA and metabolic flux data that combines information from both interaction network models and flux determination models. We started by quantifying 5,764 mRNAs, 54 metabolites, and 83 experimental (13)C-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator Gcn4p. Although mRNA expression alone did not directly predict metabolic response, this correlation improved through incorporating a network-based model of amino acid biosynthesis (from r = 0.07 to 0.80 for mRNA-flux agreement). The model provides evidence of general biological principles: rewiring of metabolic flux (i.e., use of different reaction pathways) by transcriptional regulation and metabolite interaction density (i.e., level of pairwise metabolite-protein interactions) as a key biosynthetic control determinant. Furthermore, this model predicted flux rewiring in studies of follow-on transcriptional regulators that were experimentally validated with additional (13)C-based flux measurements. As a first step in linking metabolic control and genetic regulatory networks, this model underscores the importance of integrating diverse data types in large-scale cellular models. We anticipate that an integrated approach focusing on metabolic measurements will facilitate construction of more realistic models of cellular regulation for understanding diseases and constructing strains for industrial applications.

Dataset Information

Regena (Rga), a Drosophila homolog of the global negative transcriptional regulator CDC36 (NOT2) from yeast, modifies gene expression and suppresses position effect variegation.

Publications

Regena (Rga), a Drosophila homolog of the global negative transcriptional regulator CDC36 (NOT2) from yeast, modifies gene expression and suppresses position effect variegation.

Similar Datasets

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