Regulation of mRNA translation by RNH1 in hematopoietic cells
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ABSTRACT:
PROVIDER: PRJNA994104 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25248664_1.fastq.gz | Fastqsanger.gz | |||
| SRR25248664_2.fastq.gz | Fastqsanger.gz | |||
| SRR25248665_1.fastq.gz | Fastqsanger.gz | |||
| SRR25248665_2.fastq.gz | Fastqsanger.gz | |||
| SRR25248666_1.fastq.gz | Fastqsanger.gz |
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Project description:Hematopoietic progenitors and lineage cells - mRNA
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Project description:Firczuk2013 - Eukaryotic mRNA translation machinery
This is a model of Saccharomyces cerevisiae
mRNA translation which includes the initiation, elongation and termination phases. The model is for 20 condon mRNAs. The building of a multi-factor complex in initiation and also the different processes in elongation and termination are modelled in detail. The model takes into account that ribosomes cover more than one codon of mRNA so that the movement of ribosomes are effectively blocked by other ribosomes several codons downstream. It is assumed that 15 codons are occupied by each ribosome. This blocking effect is considered in reaction R18 in initiation and also reaction R26, the reaction where translocation of ribosomes takes place in elongation. The kinetic functions of these two reactions are based on MacDonald et al. 1968 and Heinrich & Rapaport 1980. All other kinetic functions follow mass-action kinetics. The concentrations of transfer RNA species (Met-tRNA, aa-tRNA and tRNA in the model) are kept constant, while the other species' concentrations can change in the course of the simulation. The model describes the translation of a short mRNA with 20 codons. Therefore, all reactions in the elongation cycle (R22, R23, R25, R26, R28 and R29) and the corresponding species are replicated accordingly to model the species with ribosomes bound at different positions. In summary, the model contains 165 different species and 141 reactions.
The value of the 56 rate constant parameters were estimated by fitting the model against a series of experimental data consisting of modulation of the various translation factors (Figures 2, 3 and S3). Overall the parameter estimation was carried out over 212 different data points (steady states).
This model is described in the article:
An in vivo control map for the eukaryotic mRNA translation machinery
Helena Firczuk, Shichina Kannambath, Jürgen Pahle, Amy Claydon, Robert Beynon, John Duncan, Hans Westerhoff, Pedro Mendes and John EG McCarthy
Molecular Systems Biology. 9:635
Abstract:
Rate control analysis defines the in vivo control map governing yeast protein synthesis and generates an extensively parameterized digital model of the translation pathway. Among other non-intuitive outcomes, translation demonstrates a high degree of functional modularity and comprises a non-stoichiometric combination of proteins manifesting functional convergence on a shared maximal translation rate. In exponentially growing cells, polypeptide elongation (eEF1A, eEF2, and eEF3) exerts the strongest control. The two other strong control points are recruitment of mRNA and tRNAi to the 40S ribosomal subunit (eIF4F and eIF2) and termination (eRF1; Dbp5). In contrast, factors that are found to promote mRNA scanning efficiency on a longer than-average 5′untranslated region (eIF1, eIF1A, Ded1, eIF2B, eIF3, and eIF5) exceed the levels required for maximal control. This is expected to allow the cell to minimize scanning transition times, particularly for longer 5′UTRs. The analysis reveals these and other collective adaptations of control shared across the factors, as well as features that reflect functional modularity and system robustness. Remarkably, gene duplication is implicated in the fine control of cellular protein synthesis.
This model is hosted on BioModels Database
and identified by: BIOMD0000000457
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for more information.
2024-09-02 | BIOMD0000000457 | BioModels
Project description:Abscisic acid (ABA) is a crucial phytohormone involved in plant growth and stress responses. While the transcriptional regulation triggered by ABA is well-documented, its effects on translational regulation have been less studied. Through Ribo-seq and RNA-seq analyses, we find that ABA treatment not only influences gene expression at the mRNA level but also significantly impacts mRNA translation efficiency (TE) in Arabidopsis thaliana. ABA inhibits global mRNA translation via its core signaling pathway, which includes ABA receptors, protein phosphatase 2Cs (PP2Cs), and SNF1-related protein kinase 2s (SnRK2s). Upon ABA treatment, Glycine-rich RNA-binding proteins 7 and 8 (GRP7&8) protein levels decrease due to both reduced mRNA level and decreased TE, which diminishes their association with polysomes and leads to a global decline in mRNA TE. The absence of GRP7&8 results in a global impairment of ABA-regulated translational changes, linking ABA signaling to GRP7-dependent modulation of mRNA translation. The regulation of GRP7 on TE relies significantly on its direct binding to target mRNAs. Moreover, mRNA translation efficiency under drought stress is partially dependent on the ABA-GRP7&8 pathways. Collectively, our study reveals GRP7’s role downstream of SnRK2s in mediating translation regulation in ABA signaling, offering a model for ABA-triggered multi-route regulation of environmental adaptation.
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Project description:Cytoplasmic poly(A)-binding protein (PABPC, yeast Pab1) is involved in various stages of mRNA post-transcriptional control, including translation initiation, translation termination, and mRNA decay regulation. Due to the multi-functional properties of PABPC, attempts to define a specific role for PABPC in vivo by deleting, depleting, overexpressing, or mutating the protein has led to conflicting models of PABPC's function. To specifically assess direct and indirect consequences of deleting PABPC, we generated and analyzed RNA-Seq, ribosome profiling, and mass spectrometry data from yeast cells lacking Pab1.
2023-06-09 | PXD041495 | Pride
Project description:In vertebrates, lifelong supply of all the blood cell types in suitable numbers is maintained by the hematopoietic stem cells (HSCs). During development, these HSCs emerge in the aorta-gonad-mesonephros (AGM) from specialized vascular endothelium through a transdifferentiation process, called as endothelial-to-hematopoietic transition (EHT). During this process, select endothelial cells (CD31+c-kit- or CD31PCKITN) switch to a hematopoietic transcriptional program, undergo morphological changes and become hemogenic (CD31+c-kit+ or CD31PCKITP) and gives rise to hematopoietic cells (CD31-c-kit+ or CD31NCKITP). A complex interplay of key transcription factors and signaling pathways coordinates the whole process. Specific metabolic signature of a cell can precisely define its phenotype. Evidence has emerged that cellular phenotype and function can be driven according to the changes in cellular metabolism. Metabolic programs, which are stage specific, allow stem cells to adapt their function in different microenvironments. In the present study, we performed nano LC-MS/MS based proteomic analysis to understand the molecular program involved in the transdifferentiation of endothelial to hematopoietic cells.
2023-06-02 | MSV000092085 | GNPS
Project description:Translational regulation was investigated at the genome scale in Escherichia coli cells. Using the polysome profiling method, the ribosome occupancy (RO) and ribosome density (RD) of different mRNA copies were determined for several hundred mRNAs during the exponential and stationary phases, providing the most complete characterisation of such regulation in E. coli. Although for most genes, nearly all mRNAs (>90%) were undergoing translation, they were loaded with far fewer than the theoretical maximum number of ribosomes, suggesting translation limitation at the initiation step. Multiple linear regression was used to identify key intrinsic factors involved in the genome-wide regulation of RO and RD (i.e., open reading frame GC%, protein function and localisation). Unexpectedly, mRNA concentration, a factor that depends on cell physiology, was predicted to positively regulate RO and RD during the exponential and stationary phases. Using a set of selected genes controlled by an inducible promoter, we confirmed that increasing the mRNA concentration upon transcription induction led to increases in both RO and ribosome load. The fact that this relationship between mRNA concentration and translation parameters was also effective when E. coli cells naturally adapted to carbon source changes demonstrates its physiological relevance. This work demonstrates that translation regulation is positively controlled by transcript availability. This new mechanism contributes to the co-directional regulation of transcription and translation with synergistic effects on gene expression, and provides a systemic understanding of E. coli cell function.
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