E-MTAB-8621
Ontology highlight
ABSTRACT:
PROVIDER: E-MTAB-8621 | ExpressionAtlas | 2020-01-13
REPOSITORIES: ExpressionAtlas
Similar Datasets
Project description:RNA-seq of yeast cell cycle grown on ethanol, used for absolute gene expression quantification
| PRJEB35903 | ENA
Project description:Multi-omic absolute quantitative analysis of the yeast (Saccharomyces cerevisiae) mitotic cell cycle. Transcriptomics (RNA-Seq), proteomics (SILAC/ iBAQ), phosphoproteomics (SILAC/ iBAQ, enrichment with TiO2), and untargeted metabolomics (Metabolon, Inc.) were performed, all in biological triplicate. Three sub-projects from this central project were generated, in order of priority: (1) growth on glucose (n= 30 samples) (2) growth on ethanol (n= 21) and (3) pheromone effect (n= 51 samples; combined glucose and ethanol samples). For each sample, every omic type was analysed (n=4; transcriptomic, proteomic, phosphoproteomic, and metabolomic). Total omic samples generated for project = 204.
2020-03-26 | PXD016519 | Pride
Project description:RNA-seq of yeast cell cycle grown on glucose, synchronized with CDC15-2.
2020-01-10 | E-MTAB-8626 | ExpressionAtlas
Project description:RNA-seq of yeast cell cycle grown on glucose, synchronized with CDC15-2.
| PRJEB35940 | ENA
Project description:The sexual cycle of Ustilago maydis includes the succession of a saprophytic haploid yeast stage to a virulent hyphal dikaryotic stage, product of the mating of sexually compatible yeast cells. This dimorphic transition may be replicated in vitro by different means. Recently, it was shown that ethanol induced filamentous growth on solid medium, and we observed that this process also occurred in liquid media. Since the utilization of a six- or a two-carbon source involves different metabolic pathways, we considered that the morphogenetic process might be associated with this alteration. Accordingly, we analyzed the transcriptome of U. maydis grown in glucose or in ethanol using the Illumina RNA Seq. Around 18 million reads were obtained from each treatment. From the 6788 U. maydis genes, 542 were differentially expressed (158 upregulated and 384 downregulated) during incubation with ethanol compared to glucose-grown cells, revealing a noticeable alteration in the metabolism of the fungus through their adaptation to either carbon source. The present phenomenon is a further example of how an alteration in a two-dimensional mechanism (metabolism) can affect a three-dimensional process (cell morphogenesis).
2021-01-18 | GSE164981 | GEO
Project description:RNA-seq of yeast cell cycle, used for absolute gene expression quantification
| PRJEB35742 | ENA
Project description:We use Saccharomyces cerevisiae grown on ethanol to perform absolute quantitative multi-omics analysis to map interactions of different cellular processes during the yeast cell cycle.
2021-11-01 | E-MTAB-8621 | biostudies-arrayexpress
Project description:<p>Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12Ac ChIP-seq data for wild-type and mip6delta strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress.</p>
2020-02-14 | MTBLS1320 | MetaboLights
Project description:Flis2015 - Plant clock gene circuit
(P2011.1.2 PLM_71 ver 1)
This model is described in the article:
Defining the robust
behaviour of the plant clock gene circuit with absolute RNA
timeseries and open infrastructure.
Flis A, Fernández AP, Zielinski
T, Mengin V, Sulpice R, Stratford K, Hume A, Pokhilko A, Southern
MM, Seaton DD, McWatters HG, Stitt M, Halliday KJ, Millar
AJ.
Open Biol 2015 Oct; 5(10):
Abstract:
Our understanding of the complex, transcriptional feedback
loops in the circadian clock mechanism has depended upon
quantitative, timeseries data from disparate sources. We
measure clock gene RNA profiles in Arabidopsis thaliana
seedlings, grown with or without exogenous sucrose, or in
soil-grown plants and in wild-type and mutant backgrounds. The
RNA profiles were strikingly robust across the experimental
conditions, so current mathematical models are likely to be
broadly applicable in leaf tissue. In addition to providing
reference data, unexpected behaviours included co-expression of
PRR9 and ELF4, and regulation of PRR5 by GI. Absolute RNA
quantification revealed low levels of PRR9 transcripts (peak
approx. 50 copies cell(-1)) compared with other clock genes,
and threefold higher levels of LHY RNA (more than 1500 copies
cell(-1)) than of its close relative CCA1. The data are
disseminated from BioDare, an online repository for focused
timeseries data, which is expected to benefit mechanistic
modelling. One data subset successfully constrained clock gene
expression in a complex model, using publicly available
software on parallel computers, without expert tuning or
programming. We outline the empirical and mathematical
justification for data aggregation in understanding highly
interconnected, dynamic networks such as the clock, and the
observed design constraints on the resources required to make
this approach widely accessible.
cL_m_degr, param m1, modified to ensure light rate > dark rate.
This model is hosted on
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MODEL1510190000.
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2024-09-02 | BIOMD0000000597 | BioModels
Project description:Primary outcome(s): Cancer-related gene alteration, expression of protein, and expression of RNA
| 2645675 | ecrin-mdr-crc