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      Dynamic transcriptome analysis measures rates of mRNA synthesis and decay in yeast

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          Abstract

          • Rates of mRNA synthesis and decay can be measured on a genome-wide scale in yeast by dynamic transcriptome analysis (DTA), which combines non-perturbing metabolic RNA labeling with dynamic kinetic modeling.

          • DTA reveals that most mRNA synthesis rates are around several transcripts per cell and cell cycle, and most mRNA half-lives range around a median of 11 min.

          • DTA realistically monitors the cellular response to osmotic stress with higher sensitivity and temporal resolution than transcriptomics, and can be used to follow changes in RNA metabolism in gene regulatory systems.

          Abstract

          Nascent transcriptome analysis reveals dynamics of mRNA synthesis and decay in yeast.

          The first step in the expression of the genome is the synthesis of messenger-RNA (mRNA). In all cells, the regulation of mRNA levels in response to changing environmental conditions is a fundamental process. Classical methods to study such changes in mRNA levels, however, fail to unravel whether such changes are due to changes in mRNA synthesis (transcription) or changes in mRNA decay, which both contribute to setting mRNA levels. Therefore, the regulation of mRNA stability and turnover is poorly understood, and new methods for a quantitative analysis of mRNA synthesis and decay are urgenlty sought.

          In this study, we describe a novel method termed dynamic transcriptome analysis (DTA), which can be used to determine synthesis and decay rates of mRNAs on a genome-wide level in yeast and other eukaryotic cells. We applied DTA to the model organism Saccharomyces cerevisiae and analyzed the dynamics of the transcriptome under standard growth conditions as well as under osmotic stress conditions. DTA relies on a combination of biochemistry, high-throughput data acquisition, and computational biology. It uses metabolic labeling of newly synthesised RNA with the nucleoside analogon 4-thiouridine (4sU), purification of labeled, newly synthesized RNA, and subsequent microarray hybridization. An improved mathematical model enables synthesis and decay rates of esentially all mRNAs in the cell to be determined with accuracy.

          In this study, we found that under normal growth conditions the synthesis rates for most mRNAs are low and that the decay rates are not correlated with synthesis. Addition of salt to the culture, however, induced three phases of changes in mRNA synthesis and decay. During the initial shock phase, there is a global repression of synthesis and a reduction of decay of most mRNAs. The subsequent induction phase involves strongly increased synthesis of stress mRNAs, which are also destabilized. Finally, the recovery phase restores decay rates, but leaves synthesis rates altered, apparently to allow for cellular growth under the new conditions.

          DTA shows a higher sensitivity and better temporal resolution than classical methods such as transcriptomics. Also, DTA is non-perturbing and allows for an unbiased monitoring of genomic regulatory systems in living cells. Previously used methods are invasive and likely alter cellular physiology and thereby mRNA dynamics. DTA has a high potential to become a standard technique in molecular biology that may replace standard transcriptomics to study gene regulatory systems. In the future, DTA may be used to study dynamic changes in cellular mRNA metabolism induced by chemical inhibitors or defined mutations or changes in the environment.

          Abstract

          To obtain rates of mRNA synthesis and decay in yeast, we established dynamic transcriptome analysis (DTA). DTA combines non-perturbing metabolic RNA labeling with dynamic kinetic modeling. DTA reveals that most mRNA synthesis rates are around several transcripts per cell and cell cycle, and most mRNA half-lives range around a median of 11 min. DTA can monitor the cellular response to osmotic stress with higher sensitivity and temporal resolution than standard transcriptomics. In contrast to monotonically increasing total mRNA levels, DTA reveals three phases of the stress response. During the initial shock phase, mRNA synthesis and decay rates decrease globally, resulting in mRNA storage. During the subsequent induction phase, both rates increase for a subset of genes, resulting in production and rapid removal of stress-responsive mRNAs. During the recovery phase, decay rates are largely restored, whereas synthesis rates remain altered, apparently enabling growth at high salt concentration. Stress-induced changes in mRNA synthesis rates are predicted from gene occupancy with RNA polymerase II. DTA-derived mRNA synthesis rates identified 16 stress-specific pairs/triples of cooperative transcription factors, of which seven were known. Thus, DTA realistically monitors the dynamics in mRNA metabolism that underlie gene regulatory systems.

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          Most cited references42

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          Genomic expression programs in the response of yeast cells to environmental changes.

          We explored genomic expression patterns in the yeast Saccharomyces cerevisiae responding to diverse environmental transitions. DNA microarrays were used to measure changes in transcript levels over time for almost every yeast gene, as cells responded to temperature shocks, hydrogen peroxide, the superoxide-generating drug menadione, the sulfhydryl-oxidizing agent diamide, the disulfide-reducing agent dithiothreitol, hyper- and hypo-osmotic shock, amino acid starvation, nitrogen source depletion, and progression into stationary phase. A large set of genes (approximately 900) showed a similar drastic response to almost all of these environmental changes. Additional features of the genomic responses were specialized for specific conditions. Promoter analysis and subsequent characterization of the responses of mutant strains implicated the transcription factors Yap1p, as well as Msn2p and Msn4p, in mediating specific features of the transcriptional response, while the identification of novel sequence elements provided clues to novel regulators. Physiological themes in the genomic responses to specific environmental stresses provided insights into the effects of those stresses on the cell.
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            Dissecting the regulatory circuitry of a eukaryotic genome.

            Genome-wide expression analysis was used to identify genes whose expression depends on the functions of key components of the transcription initiation machinery in yeast. Components of the RNA polymerase II holoenzyme, the general transcription factor TFIID, and the SAGA chromatin modification complex were found to have roles in expression of distinct sets of genes. The results reveal an unanticipated level of regulation which is superimposed on that due to gene-specific transcription factors, a novel mechanism for coordinate regulation of specific sets of genes when cells encounter limiting nutrients, and evidence that the ultimate targets of signal transduction pathways can be identified within the initiation apparatus.
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              Normalization of cDNA microarray data.

              Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a well-tested general purpose normalization method which has given good results on a wide range of arrays. The method may be refined by using quality weights for individual spots. The method is best combined with diagnostic plots of the data which display the spatial and intensity trends. When diagnostic plots show that biases still remain in the data after normalization, further normalization steps such as plate-order normalization or scale-normalization between the arrays may be undertaken. Composite normalization may be used when control spots are available which are known to be not differentially expressed. Variations on loess normalization include global loess normalization and two-dimensional normalization. Detailed commands are given to implement the normalization techniques using freely available software.
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                Author and article information

                Journal
                Mol Syst Biol
                Molecular Systems Biology
                Nature Publishing Group
                1744-4292
                2011
                04 January 2011
                04 January 2011
                : 7
                : 458
                Affiliations
                [1 ]simpleGene Center and Department of Biochemistry, Center for Integrated Protein Science CIPSM, Ludwig-Maximilians-Universität München , Munich, Germany
                [2 ]simpleMax von Pettenkofer-Institute, Ludwig-Maximilians-Universität München , Munich, Germany
                Author notes
                [a ]Max von Pettenkofer-Institute, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany. Tel.: +49 8921 807 6852; Fax: +49 8921 807 6899; doelken@ 123456lmb.uni-muenchen.de
                [b ]Gene Center and Department of Biochemistry, Center for Integrated Protein Science CIPSM, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany. Tel.: +49 8921 807 6965; Fax: +49 8921 807 6999; E-mail: tresch@ 123456lmb.uni-muenchen.de
                [c ]Gene Center and Department of Biochemistry, Center for Integrated Protein Science CIPSM, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany. Tel.: +49 8921 807 6965; Fax: +49 8921 807 6999; E-mail: cramer@ 123456lmb.uni-muenchen.de
                [*]

                These authors contributed equally to this work

                Article
                msb2010112
                10.1038/msb.2010.112
                3049410
                21206491
                bea232fd-8e39-4e1a-8245-a7dde082b806
                Copyright © 2011, EMBO and Macmillan Publishers Limited

                This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial Share Alike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.

                History
                : 23 July 2010
                : 29 November 2010
                Categories
                Article

                Quantitative & Systems biology
                mrna transcription,mrna turnover,gene regulation,salt stress response,gene expression

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