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Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury

qRT-PCR still remains the most widely used method for quantifying gene expression levels, although newer technologies such as next generation sequencing are becoming increasingly popular. A critical, yet often underappreciated, problem when analysing qRT-PCR data is the selection of suitable referen...

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Autores principales: Fragoulis, Athanassios, Biller, Kristina, Fragoulis, Stephanie, Lex, Dennis, Uhlig, Stefan, Reiss, Lucy Kathleen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346155/
https://www.ncbi.nlm.nih.gov/pubmed/34360619
http://dx.doi.org/10.3390/ijms22157853
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author Fragoulis, Athanassios
Biller, Kristina
Fragoulis, Stephanie
Lex, Dennis
Uhlig, Stefan
Reiss, Lucy Kathleen
author_facet Fragoulis, Athanassios
Biller, Kristina
Fragoulis, Stephanie
Lex, Dennis
Uhlig, Stefan
Reiss, Lucy Kathleen
author_sort Fragoulis, Athanassios
collection PubMed
description qRT-PCR still remains the most widely used method for quantifying gene expression levels, although newer technologies such as next generation sequencing are becoming increasingly popular. A critical, yet often underappreciated, problem when analysing qRT-PCR data is the selection of suitable reference genes. This problem is compounded in situations where up to 25% of all genes may change (e.g., due to leukocyte invasion), as is typically the case in ARDS. Here, we examined 11 widely used reference genes for their suitability in commonly used models of acute lung injury (ALI): ventilator-induced lung injury (VILI), in vivo and ex vivo, lipopolysaccharide plus mechanical ventilation (MV), and hydrochloric acid plus MV. The stability of reference gene expression was determined using the NormFinder, BestKeeper, and geNorm algorithms. We then proceeded with the geNorm results because this is the only algorithm that provides the number of reference genes required to achieve normalisation. We chose interleukin-6 (Il-6) and C-X-C motif ligand 1 (Cxcl-1) as the genes of interest to analyse and demonstrate the impact of inappropriate normalisation. Reference gene stability differed between the ALI models and even within the subgroup of VILI models, no common reference gene index (RGI) could be determined. NormFinder, BestKeeper, and geNorm produced slightly different, but comparable results. Inappropriate normalisation of Il-6 and Cxcl1 gene expression resulted in significant misinterpretation in all four ALI settings. In conclusion, choosing an inappropriate normalisation strategy can introduce different kinds of bias such as gain or loss as well as under- or overestimation of effects, affecting the interpretation of gene expression data.
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spelling pubmed-83461552021-08-07 Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury Fragoulis, Athanassios Biller, Kristina Fragoulis, Stephanie Lex, Dennis Uhlig, Stefan Reiss, Lucy Kathleen Int J Mol Sci Article qRT-PCR still remains the most widely used method for quantifying gene expression levels, although newer technologies such as next generation sequencing are becoming increasingly popular. A critical, yet often underappreciated, problem when analysing qRT-PCR data is the selection of suitable reference genes. This problem is compounded in situations where up to 25% of all genes may change (e.g., due to leukocyte invasion), as is typically the case in ARDS. Here, we examined 11 widely used reference genes for their suitability in commonly used models of acute lung injury (ALI): ventilator-induced lung injury (VILI), in vivo and ex vivo, lipopolysaccharide plus mechanical ventilation (MV), and hydrochloric acid plus MV. The stability of reference gene expression was determined using the NormFinder, BestKeeper, and geNorm algorithms. We then proceeded with the geNorm results because this is the only algorithm that provides the number of reference genes required to achieve normalisation. We chose interleukin-6 (Il-6) and C-X-C motif ligand 1 (Cxcl-1) as the genes of interest to analyse and demonstrate the impact of inappropriate normalisation. Reference gene stability differed between the ALI models and even within the subgroup of VILI models, no common reference gene index (RGI) could be determined. NormFinder, BestKeeper, and geNorm produced slightly different, but comparable results. Inappropriate normalisation of Il-6 and Cxcl1 gene expression resulted in significant misinterpretation in all four ALI settings. In conclusion, choosing an inappropriate normalisation strategy can introduce different kinds of bias such as gain or loss as well as under- or overestimation of effects, affecting the interpretation of gene expression data. MDPI 2021-07-22 /pmc/articles/PMC8346155/ /pubmed/34360619 http://dx.doi.org/10.3390/ijms22157853 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fragoulis, Athanassios
Biller, Kristina
Fragoulis, Stephanie
Lex, Dennis
Uhlig, Stefan
Reiss, Lucy Kathleen
Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury
title Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury
title_full Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury
title_fullStr Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury
title_full_unstemmed Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury
title_short Reference Gene Selection for Gene Expression Analyses in Mouse Models of Acute Lung Injury
title_sort reference gene selection for gene expression analyses in mouse models of acute lung injury
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346155/
https://www.ncbi.nlm.nih.gov/pubmed/34360619
http://dx.doi.org/10.3390/ijms22157853
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