Dataset Information

Sex blind: bridging the gap between drug exposure and sex-related gene expression in Danio rerio using next-generation sequencing (NGS) data and a literature review to find the missing links in pharmaceutical and environmental toxicology studies

ABSTRACT: Abstract: The sex of both humans and Danio rerio has previously been shown to affect the way individuals respond to drug exposure. Genes which allow identification of sex in juvenile zebrafish show potential to reveal these confounding variables between sex in toxicological and preclinical trials but the link between these is so far missing. These sex-specific, early expressed genes where expression is not altered by drug exposure must be carefully selected for this purpose. We aimed to discover genes which can be used in pharmaceutical trials and environmental toxicology studies to uncover sex-related variations in gene expression with drug application using the model organism Danio rerio. Previously published early sex-determining genes from King et al. were evaluated as well as additional genes selected from our zebrafish Next-generation sequencing (NGS) data which are known from previously published works not to be susceptible to changes in expression with drug exposure. NGS revealed a further ten female-specific genes (vtg1, cyp17a1, cyp19a1a, igf3, ftz-f1, gdf9, foxl2a, Nr0b1, ipo4, lhcgr) and five male-related candidate genes (FKBP5, apobb1, hbaa1, dmrt1, spata6) which are also expressed in juvenile zebrafish, 28 days post fertilisation (dpf). Following this, a literature review was performed to classify which of these early-expressed sex-specific genes are already known to be affected by drug exposure in order to determine candidate genes to be used in pharmaceutical trials or environmental toxicology testing studies. Discovery of these early sex-determining genes in Danio rerio will allow identification of sex-related responses to drug testing to improve sex-specific healthcare and the medical treatment of human patients.

ORGANISM(S): Danio rerio

PROVIDER: GSE234104 | GEO | 2023/06/06

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

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.

Dataset Information

Sex blind: bridging the gap between drug exposure and sex-related gene expression in Danio rerio using next-generation sequencing (NGS) data and a literature review to find the missing links in pharmaceutical and environmental toxicology studies

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure