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Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling

Gene expression analysis by quantitative real-time polymerase chain reaction (RT-qPCR) is routinely used in biomedical studies. The reproducibility and reliability of the data fundamentally depends on experimental design and data interpretation. Despite the wide application of this assay, there is s...

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Autores principales: Brzeszczyńska, Joanna, Brzeszczyński, Filip, Samuel, Kay, Morgan, Katie, Morley, Steven D., Plevris, John N., Hayes, Peter C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140694/
https://www.ncbi.nlm.nih.gov/pubmed/32245194
http://dx.doi.org/10.3390/cells9030770
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author Brzeszczyńska, Joanna
Brzeszczyński, Filip
Samuel, Kay
Morgan, Katie
Morley, Steven D.
Plevris, John N.
Hayes, Peter C.
author_facet Brzeszczyńska, Joanna
Brzeszczyński, Filip
Samuel, Kay
Morgan, Katie
Morley, Steven D.
Plevris, John N.
Hayes, Peter C.
author_sort Brzeszczyńska, Joanna
collection PubMed
description Gene expression analysis by quantitative real-time polymerase chain reaction (RT-qPCR) is routinely used in biomedical studies. The reproducibility and reliability of the data fundamentally depends on experimental design and data interpretation. Despite the wide application of this assay, there is significant variation in the validation process of gene expression data from research laboratories. Since the validity of results depends on appropriate normalisation, it is crucial to select appropriate reference gene(s), where transcription of the selected gene is unaffected by experimental setting. In this study we have applied geNorm technology to investigate the transcription of 12 ‘housekeeping’ genes for use in the normalisation of RT-qPCR data acquired using a widely accepted HepaRG hepatic cell line in studies examining models of pre-clinical drug testing. geNorm data identified a number of genes unaffected by specific drug treatments and showed that different genes remained invariant in response to different drug treatments, whereas the transcription of ‘classical’ reference genes such as GAPDH (glyceralde- hyde-3-phosphate dehydrogenase) was altered by drug treatment. Comparing data normalised using the reference genes identified by geNorm with normalisation using classical housekeeping genes demonstrated substantial differences in the final results. In light of cell therapy application, RT-qPCR analyses has to be carefully evaluated to accurately interpret data obtained from dynamic cellular models undergoing sequential stages of phenotypic change.
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spelling pubmed-71406942020-04-13 Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling Brzeszczyńska, Joanna Brzeszczyński, Filip Samuel, Kay Morgan, Katie Morley, Steven D. Plevris, John N. Hayes, Peter C. Cells Article Gene expression analysis by quantitative real-time polymerase chain reaction (RT-qPCR) is routinely used in biomedical studies. The reproducibility and reliability of the data fundamentally depends on experimental design and data interpretation. Despite the wide application of this assay, there is significant variation in the validation process of gene expression data from research laboratories. Since the validity of results depends on appropriate normalisation, it is crucial to select appropriate reference gene(s), where transcription of the selected gene is unaffected by experimental setting. In this study we have applied geNorm technology to investigate the transcription of 12 ‘housekeeping’ genes for use in the normalisation of RT-qPCR data acquired using a widely accepted HepaRG hepatic cell line in studies examining models of pre-clinical drug testing. geNorm data identified a number of genes unaffected by specific drug treatments and showed that different genes remained invariant in response to different drug treatments, whereas the transcription of ‘classical’ reference genes such as GAPDH (glyceralde- hyde-3-phosphate dehydrogenase) was altered by drug treatment. Comparing data normalised using the reference genes identified by geNorm with normalisation using classical housekeeping genes demonstrated substantial differences in the final results. In light of cell therapy application, RT-qPCR analyses has to be carefully evaluated to accurately interpret data obtained from dynamic cellular models undergoing sequential stages of phenotypic change. MDPI 2020-03-21 /pmc/articles/PMC7140694/ /pubmed/32245194 http://dx.doi.org/10.3390/cells9030770 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Brzeszczyńska, Joanna
Brzeszczyński, Filip
Samuel, Kay
Morgan, Katie
Morley, Steven D.
Plevris, John N.
Hayes, Peter C.
Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling
title Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling
title_full Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling
title_fullStr Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling
title_full_unstemmed Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling
title_short Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling
title_sort validation of reference genes for gene expression studies by rt-qpcr in heparg cells during toxicity testing and disease modelling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140694/
https://www.ncbi.nlm.nih.gov/pubmed/32245194
http://dx.doi.org/10.3390/cells9030770
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