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Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis

BACKGROUND: Quantitative real-time PCR is a valuable tool for evaluating bacterial gene expression. However, in order to make best use of this method, endogenous reference genes for expression data normalisation must first be identified by carefully validating the stability of expression under exper...

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Autores principales: Bujold, Adina R, MacInnes, Janet I
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4369107/
https://www.ncbi.nlm.nih.gov/pubmed/25884823
http://dx.doi.org/10.1186/s13104-015-1045-8
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author Bujold, Adina R
MacInnes, Janet I
author_facet Bujold, Adina R
MacInnes, Janet I
author_sort Bujold, Adina R
collection PubMed
description BACKGROUND: Quantitative real-time PCR is a valuable tool for evaluating bacterial gene expression. However, in order to make best use of this method, endogenous reference genes for expression data normalisation must first be identified by carefully validating the stability of expression under experimental conditions. Therefore, the objective of this study was to validate eight reference genes of the opportunistic swine pathogen, Actinobacillus suis, grown in aerobic cultures with (Epinephrine) or without (Aerobic) epinephrine in the growth medium and in anoxic static cultures (Anoxic), and sampled during exponential and stationary phases. RESULTS: Using the RefFinder tool, expression data were analysed to determine whether comprehensive stability rankings of selected reference genes varied with experimental design. When comparing Aerobic and Epinephrine cultures by growth phase, pyk and rpoB were both among the most stably expressed genes, but when analysing both growth phases together, only pyk remained in the top three rankings. When comparing Aerobic and Anoxic samples, proS ranked among the most stable genes in exponential and stationary phase data sets as well as in combined rankings. When analysing the Aerobic, Epinephrine, and Anoxic samples together, only gyrA ranked consistently among the top three most stably expressed genes during exponential and stationary growth as well as in combined rankings; the rho gene ranked as least stably expressed gene in this data set. CONCLUSIONS: Reference gene stability should be carefully assessed with the design of the experiment in mind. In this study, even the commonly used reference gene 16S rRNA demonstrated large variability in stability depending on the conditions studied and how the data were analysed. As previously suggested, the best approach may be to use a geometric mean of multiple genes to normalise qPCR results. As researchers continue to validate reference genes for various organisms in multiple growth conditions and sampling time points, it may be possible to make informed predictions as to which genes may be most suitable to validate for a given experimental design, but in the meantime, the reference genes used to normalise qPCR data should be selected with caution.
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spelling pubmed-43691072015-03-22 Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis Bujold, Adina R MacInnes, Janet I BMC Res Notes Research Article BACKGROUND: Quantitative real-time PCR is a valuable tool for evaluating bacterial gene expression. However, in order to make best use of this method, endogenous reference genes for expression data normalisation must first be identified by carefully validating the stability of expression under experimental conditions. Therefore, the objective of this study was to validate eight reference genes of the opportunistic swine pathogen, Actinobacillus suis, grown in aerobic cultures with (Epinephrine) or without (Aerobic) epinephrine in the growth medium and in anoxic static cultures (Anoxic), and sampled during exponential and stationary phases. RESULTS: Using the RefFinder tool, expression data were analysed to determine whether comprehensive stability rankings of selected reference genes varied with experimental design. When comparing Aerobic and Epinephrine cultures by growth phase, pyk and rpoB were both among the most stably expressed genes, but when analysing both growth phases together, only pyk remained in the top three rankings. When comparing Aerobic and Anoxic samples, proS ranked among the most stable genes in exponential and stationary phase data sets as well as in combined rankings. When analysing the Aerobic, Epinephrine, and Anoxic samples together, only gyrA ranked consistently among the top three most stably expressed genes during exponential and stationary growth as well as in combined rankings; the rho gene ranked as least stably expressed gene in this data set. CONCLUSIONS: Reference gene stability should be carefully assessed with the design of the experiment in mind. In this study, even the commonly used reference gene 16S rRNA demonstrated large variability in stability depending on the conditions studied and how the data were analysed. As previously suggested, the best approach may be to use a geometric mean of multiple genes to normalise qPCR results. As researchers continue to validate reference genes for various organisms in multiple growth conditions and sampling time points, it may be possible to make informed predictions as to which genes may be most suitable to validate for a given experimental design, but in the meantime, the reference genes used to normalise qPCR data should be selected with caution. BioMed Central 2015-03-18 /pmc/articles/PMC4369107/ /pubmed/25884823 http://dx.doi.org/10.1186/s13104-015-1045-8 Text en © Bujold and MacInnes; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Bujold, Adina R
MacInnes, Janet I
Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis
title Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis
title_full Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis
title_fullStr Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis
title_full_unstemmed Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis
title_short Validation of reference genes for quantitative real-time PCR (qPCR) analysis of Actinobacillus suis
title_sort validation of reference genes for quantitative real-time pcr (qpcr) analysis of actinobacillus suis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4369107/
https://www.ncbi.nlm.nih.gov/pubmed/25884823
http://dx.doi.org/10.1186/s13104-015-1045-8
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