Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

50 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcription profiling of S. cerevisiae mRNA abundance following oxidative stress and DNA damage stress

ABSTRACT: We subjected yeast to two stresses, oxidative stress, which under current settings induces a fast and transient response in mRNA abundance, and DNA damage, which triggers a slow enduring response. Using microarrays we performed a conventional quantification of change in mRNA abundance. Experiment Overall Design: We used Affymetrix microarrays to quantify changes in mRNA abundance following oxidative stress (using hydrogen peroxide) and DNA damage stress (using methyl methanesulfonate) during a three-hour time course (0, 30 min, 60 min, 100 min, 140 min, 180 min).

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Ophir Shalem

PROVIDER: E-GEOD-12220 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Transcription profiling of S. cerevisiae mRNAs following oxidative stress and DNA damage

Project description:We subjected yeast to two stresses, oxidative stress, which under current settings induces a fast and transient response in mRNA abundance, and DNA damage, which triggers a slow enduring response. Using microarrays, we performed a transcriptional arrest experiment to measure genome-wide mRNA decay profiles under each condition. Genome-wide decay kinetics in each condition were compared to decay experiments that were performed in a reference condition (only transcription inhibition without an additional stress) to quantify changes in mRNA stability in each condition. We found condition-specific changes in mRNA decay rates and coordination between mRNA production and degradation. In the transient response, most induced genes were surprisingly destabilized, while repressed genes were somewhat stabilized, exhibiting counteraction between production and degradation. This strategy can reconcile high steady-state level with short response time among induced genes. In contrast, the stress that induces the slow response displays the more expected behavior, whereby most induced genes are stabilized, and repressed genes destabilized. Our results show genome-wide interplay between mRNA production and degradation, and that alternative modes of such interplay determine the kinetics of the transcriptome in response to stress. Experiment Overall Design: We used Affymetrix microarrays to measure the decay profiles of all genes following transcription inhibition in four separate experiments. In two reference experiments, only transcription inhibtion was applied. In two other experiments, an additional stress was applied prior to transcription inhibition: oxidative stress (0.3mM hydrogen peroxide) or DNA damage (0.1% methyl methanesulfonate).

2008-10-26 | E-GEOD-12221 | biostudies-arrayexpress

Changes in Saccharomyces cerevisiae mRNA abundance following oxidative stress and DNA damage stress

2008-10-01 | GSE12220 | GEO

Transcription profiling of S. cerevisiae reveals transient transcriptional responses to stress are generated by opposing effects of mRNA production and degradation

Project description:This SuperSeries is composed of the following subset Series:; GSE12220: Changes in Saccharomyces cerevisiae mRNA abundance following oxidative stress and DNA damage stress; GSE12221: Decay profiles of Saccharomyces cerevisiae mRNAs following oxidative stress and DNA damage Experiment Overall Design: Refer to individual Series

2008-10-26 | E-GEOD-12222 | biostudies-arrayexpress

Measurements of mRNA abundance and decay for two strains 211 (wt) and 212 (mutant)

Project description:For each strain two time courses for mRNA abundance: Oxidative and MMS and two time courses for decay: reference decay and following oxidative stress We used Affymetrix microarrays to quantify changes in mRNA abundance following oxidative stress and DNA damage stress and also decay following transcription inhibition with and without oxidative stress. Each of the experiments were done for both strains 211 (wt) and 212 (mutant)

2011-07-29 | E-GEOD-26829 | biostudies-arrayexpress

Decay profiles of Saccharomyces cerevisiae mRNAs following oxidative stress and DNA damage

2008-10-01 | GSE12221 | GEO

Saccharomyces cerevisiae

Project description:Changes in Saccharomyces cerevisiae mRNA abundance following oxidative stress and DNA damage stress

| PRJNA113853 | ENA

Surgical Resection Lowers Oxidative Stress Markers in Patients With Colorectal Cancer

Project description:Study of Oxidative stress Markers (F2 Isoprostanes for lipid peroxidation, Carbonyl groups for protein peroxidation, 3 Nitrotyrosine for damage by nitrogens, and 8-Hydroxyguanosine for RNA peroxidation)in patients with colorectal cancer undergo surgical treatment (preoperatively during the intervention and postoperatively) and controls.

| 2115584 | ecrin-mdr-crc

Saccharomyces cerevisiae

Project description:Oxidative Stress 30-min interval

| PRJNA93823 | ENA

Saccharomyces cerevisiae

Project description:Oxidative Stress 1-min interval

| PRJNA93833 | ENA

Pereira2020 - NRF2–p53 integrated-systems model of oxidative stress

Project description:Integrated-systems model of oxidative stress connecting NRF2 and p53 signaling pathways. Additional crosstalk linking oxidative stress to p53 inhibition, p53 to NRF2 through p21, and NRF2 to MDM2 was incorporated in this model. The NRF2 pathway was encoded as first- and second-order rate equations for KEAP1 oxidation and NRF2 stabilization; NRF2-mediated transcription of antioxidant enzymes was modeled as a Hill function. The p53 pathway was reconstructed from a delay differential equation model of p53 signaling in response to DNA damage. To adapt the p53 DNA-damage model to respond to oxidative stress, we used a first-order oxidation reaction of ATM/CHEK2 by intracellular H2O2. The integrated base model of NRF2–p53 oxidative-stress signaling contains 42 reactions and 22 ordinary differential equations (ODEs).

2021-10-29 | MODEL2110270001 | BioModels

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data