Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain

Autores
Bustelo Tejada, Martin; Bruno, Martin; Loidl, Cesar Fabian; Rey Funes, Manuel; Steinbusch, Harry W. M.; Gavilanes, Antonio W. D.; van den Hove, D. L. A.
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Real-time reverse transcription PCR (qPCR) normalized to an internal reference gene (RG), is a frequently used method for quantifying gene expression changes in neuroscience. Although RG expression is assumed to be constant independent of physiological or experimental conditions, several studies have shown that commonly used RGs are not expressed stably. The use of unstable RGs has a profound effect on the conclusions drawn from studies on gene expression, and almost universally results in spurious estimation of target gene expression. Approaches aimed at selecting and validating RGs often make use of different statistical methods, which may lead to conflicting results. Based on published RG validation studies involving hypoxia the present study evaluates the expression of 5 candidate RGs (Actb, Pgk1, Sdha, Gapdh, Rnu6b) as a function of hypoxia exposure and hypothermic treatment in the neonatal rat cerebral cortex–in order to identify RGs that are stably expressed under these experimental conditions–using several statistical approaches that have been proposed to validate RGs. In doing so, we first analyzed RG ranking stability proposed by several widely used statistical methods and related tools, i.e. the Coefficient of Variation (CV) analysis, GeNorm, NormFinder, BestKeeper, and the ΔCt method. Using the Geometric mean rank, Pgk1 was identified as the most stable gene. Subsequently, we compared RG expression patterns between the various experimental groups. We found that these statistical methods, next to producing different rankings per se, all ranked RGs displaying significant differences in expression levels between groups as the most stable RG. As a consequence, when assessing the impact of RG selection on target gene expression quantification, substantial differences in target gene expression profiles were observed. Altogether, by assessing mRNA expression profiles within the neonatal rat brain cortex in hypoxia and hypothermia as a showcase, this study underlines the importance of further validating RGs for each individual experimental paradigm, considering the limitations of the statistical methods used for this aim.
Fil: Bustelo Tejada, Martin. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Universiteit Maastricht.; Países Bajos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina
Fil: Bruno, Martin. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Loidl, Cesar Fabian. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina
Fil: Rey Funes, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina
Fil: Steinbusch, Harry W. M.. Universiteit Maastricht.; Países Bajos
Fil: Gavilanes, Antonio W. D.. Universiteit Maastricht.; Países Bajos. Universidad Católica de Santiago de Guayaquil; Ecuador
Fil: van den Hove, D. L. A.. Universiteit Maastricht.; Países Bajos. Universität Würzburg; Alemania
Materia
Reference genes
Hypoxia
Hypothermia
Newborn brain
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/153857
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brainBustelo Tejada, MartinBruno, MartinLoidl, Cesar FabianRey Funes, ManuelSteinbusch, Harry W. M.Gavilanes, Antonio W. D.van den Hove, D. L. A.Reference genesHypoxiaHypothermiaNewborn brainhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Real-time reverse transcription PCR (qPCR) normalized to an internal reference gene (RG), is a frequently used method for quantifying gene expression changes in neuroscience. Although RG expression is assumed to be constant independent of physiological or experimental conditions, several studies have shown that commonly used RGs are not expressed stably. The use of unstable RGs has a profound effect on the conclusions drawn from studies on gene expression, and almost universally results in spurious estimation of target gene expression. Approaches aimed at selecting and validating RGs often make use of different statistical methods, which may lead to conflicting results. Based on published RG validation studies involving hypoxia the present study evaluates the expression of 5 candidate RGs (Actb, Pgk1, Sdha, Gapdh, Rnu6b) as a function of hypoxia exposure and hypothermic treatment in the neonatal rat cerebral cortex–in order to identify RGs that are stably expressed under these experimental conditions–using several statistical approaches that have been proposed to validate RGs. In doing so, we first analyzed RG ranking stability proposed by several widely used statistical methods and related tools, i.e. the Coefficient of Variation (CV) analysis, GeNorm, NormFinder, BestKeeper, and the ΔCt method. Using the Geometric mean rank, Pgk1 was identified as the most stable gene. Subsequently, we compared RG expression patterns between the various experimental groups. We found that these statistical methods, next to producing different rankings per se, all ranked RGs displaying significant differences in expression levels between groups as the most stable RG. As a consequence, when assessing the impact of RG selection on target gene expression quantification, substantial differences in target gene expression profiles were observed. Altogether, by assessing mRNA expression profiles within the neonatal rat brain cortex in hypoxia and hypothermia as a showcase, this study underlines the importance of further validating RGs for each individual experimental paradigm, considering the limitations of the statistical methods used for this aim.Fil: Bustelo Tejada, Martin. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Universiteit Maastricht.; Países Bajos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Bruno, Martin. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Loidl, Cesar Fabian. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Rey Funes, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Steinbusch, Harry W. M.. Universiteit Maastricht.; Países BajosFil: Gavilanes, Antonio W. D.. Universiteit Maastricht.; Países Bajos. Universidad Católica de Santiago de Guayaquil; EcuadorFil: van den Hove, D. L. A.. Universiteit Maastricht.; Países Bajos. Universität Würzburg; AlemaniaPublic Library of Science2020-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/153857Bustelo Tejada, Martin; Bruno, Martin; Loidl, Cesar Fabian; Rey Funes, Manuel; Steinbusch, Harry W. M.; et al.; Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain; Public Library of Science; Plos One; 15; 5; 5-2020; 1-121932-6203CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://dx.plos.org/10.1371/journal.pone.0233387info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0233387info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:59:03Zoai:ri.conicet.gov.ar:11336/153857instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:59:03.33CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
title Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
spellingShingle Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
Bustelo Tejada, Martin
Reference genes
Hypoxia
Hypothermia
Newborn brain
title_short Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
title_full Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
title_fullStr Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
title_full_unstemmed Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
title_sort Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain
dc.creator.none.fl_str_mv Bustelo Tejada, Martin
Bruno, Martin
Loidl, Cesar Fabian
Rey Funes, Manuel
Steinbusch, Harry W. M.
Gavilanes, Antonio W. D.
van den Hove, D. L. A.
author Bustelo Tejada, Martin
author_facet Bustelo Tejada, Martin
Bruno, Martin
Loidl, Cesar Fabian
Rey Funes, Manuel
Steinbusch, Harry W. M.
Gavilanes, Antonio W. D.
van den Hove, D. L. A.
author_role author
author2 Bruno, Martin
Loidl, Cesar Fabian
Rey Funes, Manuel
Steinbusch, Harry W. M.
Gavilanes, Antonio W. D.
van den Hove, D. L. A.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Reference genes
Hypoxia
Hypothermia
Newborn brain
topic Reference genes
Hypoxia
Hypothermia
Newborn brain
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Real-time reverse transcription PCR (qPCR) normalized to an internal reference gene (RG), is a frequently used method for quantifying gene expression changes in neuroscience. Although RG expression is assumed to be constant independent of physiological or experimental conditions, several studies have shown that commonly used RGs are not expressed stably. The use of unstable RGs has a profound effect on the conclusions drawn from studies on gene expression, and almost universally results in spurious estimation of target gene expression. Approaches aimed at selecting and validating RGs often make use of different statistical methods, which may lead to conflicting results. Based on published RG validation studies involving hypoxia the present study evaluates the expression of 5 candidate RGs (Actb, Pgk1, Sdha, Gapdh, Rnu6b) as a function of hypoxia exposure and hypothermic treatment in the neonatal rat cerebral cortex–in order to identify RGs that are stably expressed under these experimental conditions–using several statistical approaches that have been proposed to validate RGs. In doing so, we first analyzed RG ranking stability proposed by several widely used statistical methods and related tools, i.e. the Coefficient of Variation (CV) analysis, GeNorm, NormFinder, BestKeeper, and the ΔCt method. Using the Geometric mean rank, Pgk1 was identified as the most stable gene. Subsequently, we compared RG expression patterns between the various experimental groups. We found that these statistical methods, next to producing different rankings per se, all ranked RGs displaying significant differences in expression levels between groups as the most stable RG. As a consequence, when assessing the impact of RG selection on target gene expression quantification, substantial differences in target gene expression profiles were observed. Altogether, by assessing mRNA expression profiles within the neonatal rat brain cortex in hypoxia and hypothermia as a showcase, this study underlines the importance of further validating RGs for each individual experimental paradigm, considering the limitations of the statistical methods used for this aim.
Fil: Bustelo Tejada, Martin. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Universiteit Maastricht.; Países Bajos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina
Fil: Bruno, Martin. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Loidl, Cesar Fabian. Universidad Católica de Cuyo - Sede San Juan. Facultad de Ciencias Médicas. Departamento de Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina
Fil: Rey Funes, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina
Fil: Steinbusch, Harry W. M.. Universiteit Maastricht.; Países Bajos
Fil: Gavilanes, Antonio W. D.. Universiteit Maastricht.; Países Bajos. Universidad Católica de Santiago de Guayaquil; Ecuador
Fil: van den Hove, D. L. A.. Universiteit Maastricht.; Países Bajos. Universität Würzburg; Alemania
description Real-time reverse transcription PCR (qPCR) normalized to an internal reference gene (RG), is a frequently used method for quantifying gene expression changes in neuroscience. Although RG expression is assumed to be constant independent of physiological or experimental conditions, several studies have shown that commonly used RGs are not expressed stably. The use of unstable RGs has a profound effect on the conclusions drawn from studies on gene expression, and almost universally results in spurious estimation of target gene expression. Approaches aimed at selecting and validating RGs often make use of different statistical methods, which may lead to conflicting results. Based on published RG validation studies involving hypoxia the present study evaluates the expression of 5 candidate RGs (Actb, Pgk1, Sdha, Gapdh, Rnu6b) as a function of hypoxia exposure and hypothermic treatment in the neonatal rat cerebral cortex–in order to identify RGs that are stably expressed under these experimental conditions–using several statistical approaches that have been proposed to validate RGs. In doing so, we first analyzed RG ranking stability proposed by several widely used statistical methods and related tools, i.e. the Coefficient of Variation (CV) analysis, GeNorm, NormFinder, BestKeeper, and the ΔCt method. Using the Geometric mean rank, Pgk1 was identified as the most stable gene. Subsequently, we compared RG expression patterns between the various experimental groups. We found that these statistical methods, next to producing different rankings per se, all ranked RGs displaying significant differences in expression levels between groups as the most stable RG. As a consequence, when assessing the impact of RG selection on target gene expression quantification, substantial differences in target gene expression profiles were observed. Altogether, by assessing mRNA expression profiles within the neonatal rat brain cortex in hypoxia and hypothermia as a showcase, this study underlines the importance of further validating RGs for each individual experimental paradigm, considering the limitations of the statistical methods used for this aim.
publishDate 2020
dc.date.none.fl_str_mv 2020-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/153857
Bustelo Tejada, Martin; Bruno, Martin; Loidl, Cesar Fabian; Rey Funes, Manuel; Steinbusch, Harry W. M.; et al.; Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain; Public Library of Science; Plos One; 15; 5; 5-2020; 1-12
1932-6203
CONICET Digital
CONICET
url http://hdl.handle.net/11336/153857
identifier_str_mv Bustelo Tejada, Martin; Bruno, Martin; Loidl, Cesar Fabian; Rey Funes, Manuel; Steinbusch, Harry W. M.; et al.; Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain; Public Library of Science; Plos One; 15; 5; 5-2020; 1-12
1932-6203
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0233387
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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