Construction of Danio rerio Asymmetrical Maps (DreAM)
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1092581 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR28471021_1.fastq.gz | Fastqsanger.gz | |||
| SRR28471021_2.fastq.gz | Fastqsanger.gz | |||
| SRR28471022_1.fastq.gz | Fastqsanger.gz | |||
| SRR28471022_2.fastq.gz | Fastqsanger.gz | |||
| SRR28471023_1.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: Construction of 3D zebrafish spatial transcriptomics data for studying the establishment of AP axis. Methods: We performed serial bulk RNA-seq data of zebrafish embryo at three development points. Using the published spatial transcriptomics data as references, we implemented Palette to infer spatial gene expression from bulk RNA-seq data and constructed 3D embryonic spatial transcriptomics. The constructed 3D transcriptomics data was then projected on zebrafish embryo images with 3D coordinates, establishing a spatial gene expression atlas named Danio rerio Asymmetrical Maps (DreAM). Results: DreAM provides a powerful platform for visualizing gene expression patterns on zebrafish morphology and investigating spatial cell-cell interactions. Conclusions: Our work used DreAM to explore the establishment of anteroposterior (AP) axis, and identified multiple morphogen gradients that played essential roles in determining cell AP positions. Finally, we difined a hox score, and comprehensively demonstrated the spatial collinearity of Hox genes at single-cell resolution during development.
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Project description:Bekaert2012 - Reconstruction of D.rerio Metabolic Network
Danio rerio
metabolic model accounting for subcellular compartmentalisation (ZebraGEM)
This SBML representation of the D. rerio
(zebrafish) metabolic network is made available under the Creative Commons Attribution-Share Alike 3.0 Unported Licence (see www.creativecommons.org
).
This model is described in the article:
Reconstruction of Danio rerio Metabolic Model Accounting for Subcellular Compartmentalisation.
Bekaert M.
PLoS One. 2012;7(11):e49903.
Abstract:
Plant and microbial metabolic engineering is commonly used in the production of functional foods and quality trait improvement. Computational model-based approaches have been used in this important endeavour. However, to date, fish metabolic models have only been scarcely and partially developed, in marked contrast to their prominent success in metabolic engineering. In this study we present the reconstruction of fully compartmentalised models of the Danio rerio (zebrafish) on a global scale. This reconstruction involves extraction of known biochemical reactions in D. rerio for both primary and secondary metabolism and the implementation of methods for determining subcellular localisation and assignment of enzymes. The reconstructed model (ZebraGEM) is amenable for constraint-based modelling analysis, and accounts for 4,988 genes coding for 2,406 gene-associated reactions and only 418 non-gene-associated reactions. A set of computational validations (i.e., simulations of known metabolic functionalities and experimental data) strongly testifies to the predictive ability of the model. Overall, the reconstructed model is expected to lay down the foundations for computational-based rational design of fish metabolic engineering in aquaculture.
This model is hosted on BioModels Database
and identified by: MODEL1204120000
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. PMID: 20587024
.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to [CC0 Public Domain Dedication>http://creativecommons.org/publicdomain/zero/1.0/] for more information.
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Project description:It is generally assumed that all estrogen receptor positive (ER+) breast cancers proliferate in response to estrogen and therefore examples of estrogen-induced regression of ER+ cancers are paradoxical. This review reexamines the estrogen regression paradox for the Luminal A subtype of ER+ breast cancers. The proliferative response to estrogen is shown to depend on the level of ER. Mechanistically, a window of opportunity study of pre-operative estradiol suggested that with higher levels of ER, estradiol could activate the DREAM-MMB (Dimerization partner, Retinoblastoma-like proteins, E2F4, and MuvB – MYB-MuvB) pathway to decrease proliferation. The response of breast epithelium and the incidence of breast cancers during hormonal variations that occur during the menstrual cycle and at the menopausal transition respectively suggest that a single hormone, either estrogen, progesterone or androgen could activate the DREAM pathway leading to reversible cell cycle arrest. Conversely, the presence of two hormones, could switch the DREAM-MMB complex to a pro-proliferative pathway. Using publicly available data, we examine the gene expression changes after aromatase inhibitors and ICI 182,780 to provide support for the hypothesis. This review suggests that it might be possible to integrate all current hormonal therapies for Luminal A tumors within a single theoretical schema.
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