RNA-seq of Saccharomyces cerevisiae CEN.PK-113.5D (KiURA3) strain grown in different chemostat limitations
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ABSTRACT:
PROVIDER: PRJEB25957 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR2509020_1.fastq.gz | Fastqsanger.gz | |||
| ERR2509020_2.fastq.gz | Fastqsanger.gz | |||
| ERR2509030_1.fastq.gz | Fastqsanger.gz | |||
| ERR2509030_2.fastq.gz | Fastqsanger.gz | |||
| ERR2509040_1.fastq.gz | Fastqsanger.gz |
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Project description:Saccharomyces cerevisiae strain:CEN.PK Transcriptome or Gene expression
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Project description:High throughput sequencing is a powerful tool to investigate complex cellular phenotypes in functional genomics studies. Sequencing of transcriptional molecules, RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared to traditional expression analysis based on microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in analysis of RNA-seq data and to cross-compare the results with those obtained through a microarray platform. We used the well-characterized Saccharomyces cervevisiae strain CEN.PK 113-7D grown under two different physiological conditions (batch and chemostat) as a case study. In our work, we addressed the influence of genetic variability on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and Tophat), the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and noiSeq) and we explored the consistency between the two main approaches for RNA-seq: reference mapping and de novo assembly. High reproducibility in data generated through RNA-seq among different biological replicates (correlation ≥ 0.99) and high consistency with the results identified with RNA-seq and microarray data analysis (correlation ≥ 0.91) were observed. The results from differential gene expression identification as well as the results of integrated analysis based on the different methods are in good agreement. Overall, our study provides a useful and comprehensive comparison of the workflow for transcriptome analysis using RNA-seq technique.
2012-09-14 | GSE37599 | GEO
Project description:The global transcriptional response of Saccharomyces cerevisiae was investigated in low temperature chemostat cultures grown in carbon or nitrogen limitation. During steady state chemostats, the growth rates and in vivo fluxes were kept constant however the growth-limiting nutrient was significantly higher at 12oC than at 30oC and had significant effects on transcriptional responses. Growth at 12oC resulted in a rearrangement of transporters for the limiting nutrient, where hexose transporters (HXTs) and ammonium permeases (MEPs) were differentially expressed in cultures grown at 30oC in carbon and nitrogen limitations, respectively. In addition, we found repression of genes encoding proteins in reserve carbohydrates metabolism and metabolism of alternative carbon or nitrogen sources other than glucose or ammonia. However, there were also similar responses when the transcriptional response was evaluated regardless of the growth-limiting nutrient. In particular, induction of ribosome biogenesis genes emphasizes the significance of transcription and translational adaptation at low temperature. In contrast, genes encoding proteins during stress response were downregulated. This down-regulation of stress elements better known as environmental stress response (ESR) is in contradiction with previous low temperature transcriptome analyses. During continuous steady state low temperature cultivation, ESR no longer plays an integral role in S. cerevisiaeM-bM-^@M-^Ys response to temperature change. Similarly, trehalose accumulation, consistent with its gene expression, was not indispensable for growth at 12oC. This response, however, does not exclude that ESR may be required for transition phase in low temperature growth when cells are transferred from one temperature to another. Keywords: chemostat temperature 12 degree celsuis 30 degree celsius The global transcriptional response of Saccharomyces cerevisiae was investigated in low temperature chemostat cultures grown in carbon or nitrogen limitation at a dilution rate of 0.03h-1
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Project description:Saccharomyces cerevisiae strain:CEN.PK 2-1C Transcriptome or Gene expression
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Project description:The global transcriptional response of Saccharomyces cerevisiae was investigated in low temperature chemostat cultures grown in carbon or nitrogen limitation. During steady state chemostats, the growth rates and in vivo fluxes were kept constant however the growth-limiting nutrient was significantly higher at 12oC than at 30oC and had significant effects on transcriptional responses. Growth at 12oC resulted in a rearrangement of transporters for the limiting nutrient, where hexose transporters (HXTs) and ammonium permeases (MEPs) were differentially expressed in cultures grown at 30oC in carbon and nitrogen limitations, respectively. In addition, we found repression of genes encoding proteins in reserve carbohydrates metabolism and metabolism of alternative carbon or nitrogen sources other than glucose or ammonia. However, there were also similar responses when the transcriptional response was evaluated regardless of the growth-limiting nutrient. In particular, induction of ribosome biogenesis genes emphasizes the significance of transcription and translational adaptation at low temperature. In contrast, genes encoding proteins during stress response were downregulated. This down-regulation of stress elements better known as environmental stress response (ESR) is in contradiction with previous low temperature transcriptome analyses. During continuous steady state low temperature cultivation, ESR no longer plays an integral role in S. cerevisiae’s response to temperature change. Similarly, trehalose accumulation, consistent with its gene expression, was not indispensable for growth at 12oC. This response, however, does not exclude that ESR may be required for transition phase in low temperature growth when cells are transferred from one temperature to another. Keywords: chemostat temperature 12 degree celsuis 30 degree celsius
2007-01-20 | GSE6190 | GEO
Project description:We profiled total-mRNA from yeast cells grown in identical conditions to match samples submitted for proteome-wide absolute quantification. Matching mRNA profiles to absolute protein copies numbers enables a more accurate comparison of transcript to final protein levels. Here we were able to show direct comparison results in a correlation of Rsquared of 0.58, show suggesting as much as ~40% of final protein levels in yeast cannot be determined from mRNA levels alone. Reads were mapped to a reference genome of S. cerevisiae, downloaded from the Saccharomyces Genome Database (SGD), using Bowtie version 1 (74). Mapped sequences were then assembled into transcripts and quantified using Cufflinks version 2.0 (75) (using the SGD reference genome GTF file).
2015-10-10 | GSE73898 | GEO
Project description:Saccharomyces cerevisiae CEN.PK113-1A was grown in glucose-limited chemostat culture with 0%, 0.5%, 1.0%, 2.8% or 20.9% O2 in the inlet gas (D= 0.10 /h, pH5, 30C).
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Project description:Background Microorganisms adapt their transcriptome by integrating multiple chemical and physical signals from their environment. Shake-flask cultivation does not allow precise manipulation of individual culture parameters and therefore precludes a quantitative analysis of the (combinatorial) influence of these parameters on transcriptional regulation. Steady-state chemostat cultures, which do enable accurate control, measurement and manipulation of individual cultivation parameters (e.g. specific growth rate, temperature, identity of the growth-limiting nutrient) appear to provide a promising experimental platform for such a combinatorial analysis. Results A microarray compendium of 170 steady-state chemostat cultures of the yeast Saccharomyces cerevisiae is presented and analyzed. The 170 microarrays encompass 55 unique conditions, which can be characterized by the combined settings of 10 different cultivation parameters. By applying a regression model to assess the impact of (combinations of) cultivation parameters on the transcriptome, most S. cerevisiae genes were shown to be influenced by multiple cultivation parameters, and in many cases by combinatorial effects of cultivation parameters. The inclusion of these combinatorial effects in the regression model led to higher explained variance of the gene expression patterns and resulted in higher function enrichment in subsequent analysis. We further demonstrate the usefulness of the compendium and regression analysis for interpretation of shake-flask-based transcriptome studies and for guiding functional analysis of (uncharacterized) genes and pathways. Conclusions Modeling the combinatorial effects of environmental parameters on the transcriptome is crucial for understanding transcriptional regulation. Chemostat cultivation offers a powerful tool for such an approach. Keywords: chemostat steady state samples
2009-02-05 | GSE11452 | GEO