Dataset Information

Exposure to graphene oxide sheets alters the expression of reference genes used for real-time RT-qPCR normalization.

ABSTRACT: Studies unraveling the interactions between graphene oxide (GO) and the biological milieu, including cells and tissues, are multiplying quickly as the biomedical applications of this and other 2D materials continue to be explored. Many of such studies rely on real-time RT-qPCR as a powerful yet simple technique to assess gene expression. However, a systematic investigation of potential GO-induced changes in the expression of reference genes, crucial for appropriate qPCR data normalization, is still lacking. We aimed to cover this gap investigating the stability of the expression of ten candidate reference genes upon exposure to increasing, but subtoxic, GO concentrations, with two established algorithms (Bestkeeper and NormFinder). The study was performed in a human cancer cell line (MCF7) and in mouse, non-cancerous, primary cells (mouse embryonic fibroblasts, MEFs), to assess different behaviors between cell types. Both algorithms evidenced significant deviations in the expression of various reference genes. Ribosomal proteins scored among the most significantly dysregulated in both cell types. ACTB and GAPDH, the most frequent calibrators in real-time RT-qPCR, were also affected, although differences existed between cell lines. This study illustrates the need to validate reference genes for appropriate real-time RT-qPCR normalization, according to specific experimental conditions, when GO-cell interactions occur.

SUBMITTER: de Lazaro I

PROVIDER: S-EPMC6715796 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Exposure to graphene oxide sheets alters the expression of reference genes used for real-time RT-qPCR normalization.

de Lázaro Irene I Kostarelos Kostas K

Scientific reports 20190829 1

Studies unraveling the interactions between graphene oxide (GO) and the biological milieu, including cells and tissues, are multiplying quickly as the biomedical applications of this and other 2D materials continue to be explored. Many of such studies rely on real-time RT-qPCR as a powerful yet simple technique to assess gene expression. However, a systematic investigation of potential GO-induced changes in the expression of reference genes, crucial for appropriate qPCR data normalization, is st ...[more]

PMID: 31467336

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Project description:BackgroundA critical step in the RT-qPCR workflow for studying gene expression is data normalization, one of the strategies being the use of reference genes. This study aimed to identify and validate a selection of reference genes for relative quantification in Talaromyces versatilis, a relevant industrial filamentous fungus. Beyond T. versatilis, this study also aimed to propose reference genes that are applicable more widely for RT-qPCR data normalization in filamentous fungi.ResultsA selection of stable, potential reference genes was carried out in silico from RNA-seq based transcriptomic data obtained from T. versatilis. A dozen functionally unrelated candidate genes were analysed by RT-qPCR assays over more than 30 relevant culture conditions. By using geNorm, we showed that most of these candidate genes had stable transcript levels in most of the conditions, from growth environments to conidial germination. The overall robustness of these genes was explored further by showing that any combination of 3 of them led to minimal normalization bias. To extend the relevance of the study beyond T. versatilis, we challenged their stability together with sixteen other classically used genes such as β-tubulin or actin, in a representative sample of about 100 RNA-seq datasets. These datasets were obtained from 18 phylogenetically distant filamentous fungi exposed to prevalent experimental conditions. Although this wide analysis demonstrated that each of the chosen genes exhibited sporadic up- or down-regulation, their hierarchical clustering allowed the identification of a promising group of 6 genes, which presented weak expression changes and no tendency to up- or down-regulation over the whole set of conditions. This group included ubcB, sac7, fis1 and sarA genes, as well as TFC1 and UBC6 that were previously validated for their use in S. cerevisiae.ConclusionsWe propose a set of 6 genes that can be used as reference genes in RT-qPCR data normalization in any field of fungal biology. However, we recommend that the uniform transcription of these genes is tested by systematic experimental validation and to use the geometric averaging of at least 3 of the best ones. This will minimize the bias in normalization and will support trustworthy biological conclusions.

Dataset Information

Exposure to graphene oxide sheets alters the expression of reference genes used for real-time RT-qPCR normalization.

Publications

Exposure to graphene oxide sheets alters the expression of reference genes used for real-time RT-qPCR normalization.

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